Farmers who are motivated by sustainability are also likely to seek out these programs

Examples include cover cropping, water conservation, erosion control, integrated pest management, or organic certification. Although the level of abstraction might be conceptualized as a continuum, this simple categorization is useful for analysis. Another way of thinking about this categorization is that goals are value-driven outcomes of sustainability and strategies represent beliefs about the means to achieving those goals . Hypothesis 2 is that mental models of sustainable agriculture will reflect geographic variation and local context. Differences in farmer knowledge and the practice of agriculture reflect regional biophysical and social differences . In particular, although abstract goals of sustainability are likely to be more universal across geographies, the concrete strategies used to achieve those goals may reflect geographical variation in terms of challenges and opportunities for realizing the goals . For example, achieving the goal of environmental responsibility in the Napa Valley requires water management and cover-crop strategies for reducing soil erosion by surface water runoff on steep hillsides. In Lodi, strategies for wind-born soil erosion control are more relevant across the gentle valley floor topography of the region. Hypothesis 3 is that farmers who subscribe to more central concepts in the mental model are also more likely to engage in a range of sustainability behaviors. In particular, the sophistication of a farmer’s definition of sustainability should be correlated with their participation in extension programs and adoption of sustainability practices. The extension programs in California viticulture explicitly train farmers in the idea of sustainability and also identify specific sustainability practices. Thus, participation, practices,dutch bucket hydroponic and mental models represent a set of coevolving and synergistic processes.We constructed a mental model based on responses to surveys of wine grape growers in all three study regions.

Using content analysis of farmersself-reported definitions of sustainability , we classified 56 concepts into 19 abstract goals of sustainability and 37 more concrete strategies. We operationalized the mental model as a network where the concepts are nodes and valued ties represent the number of times two concepts co-occur together in a single definition of sustainable agriculture . We first identified an overall mental model by taking the union of the regional concept networks. A union network is defined as the combination of nodes and ties from two or more networks . The union network provides a comprehensive picture of farmer thinking about sustainable agriculture. The overall mental model from the union network is visualized in Fig. 1. Nodes are scaled by a measure of centrality we call prominence,which indicates a concepts importance in the mental model. Prominent concepts are widely recognized among farmers as legitimate dimensions of sustainability and they are cognitively associated with many other central concepts. Technically, prominence combines the frequency that a concept appears in the network with its centrality . Because prominent concepts are linked to many other concepts, they are effective cognitive entry points for leveraging farmer thinking about sustainability. Ties are unscaled. Nodes are shaded by classification, with yellow-colored nodes representing goals of sustainable agriculture and aqua-colored nodes representing strategies. Table S1 lists all of the concepts, examples of coded text for each concept, classification as goal or strategy , and three measures of centrality: prominence, occurrence probability, and eigenvector centrality. We chose the examples of coded text that best illustrate the core ideas of the concept.Our mental model analysis identified key concepts that are factored into a practitioners decision-making process. The goals of economic viability, environmental responsibility, continuation into the future, and crop value are powerful drivers of decision making, with relevance across different social-ecological contexts. The hierarchical structure of the overall mental model suggests that although practitioners focus on achieving a common set of broad goals, the strategies they associate with realizing them are numerous and diverse.

Key strategies include practice adoption, stewardship of resources, reduction or elimination of agrochemicals, and water conservation and quality enhancement. Because of their association with many other goals and strategies, central concepts are potential cognitive entry points for leveraging practitioner thinking about sustainability.Sustainability is notoriously difficult to define for the reason that it is a relative concept , which varies widely across space, time, and scale . Furthermore, diverse stakeholders often have divergent and even conflicting values and goals . Practitioners must grapple with the questions of what is to be sustained, for how long, for whose benefit, at what cost, over what geographical area, and measured by what criteria . We argue that definitions of sustainability that are grounded in practitionersviewpoints will have greater relevance to real-world contexts and therefore be more useful for guiding actions . Empirically measuring mental models of sustainability is crucial to know whether the normative ideas about sustainability discussed within academic, policy, and public circles are relevant to on-the-ground decisions. Our study of mental models provided two main insights into practitionersdefinitions of sustainability. First, mental models of sustainability are organized hierarchically along a continuum of abstractness from general goals of sustainability to concrete strategies for achieving those goals. At least among wine grape growers, the overall mental model is sophisticated and reflects many of the concepts discussed in the academic literature and among policymakers . Definitions that focus on central goals are likely to prompt practitioner thinking about their linked strategies, and are more likely to resonate with a greater number and diversity of practitioners. To the extent these goals and strategies are grounded in more general environmental values and norms, the network approach used here emphasizes the interdependent and relational aspects of sustainability thinking. Second, more central abstract concepts are universal across geography, with only anecdotal evidence that strategies are customized to specific social-ecological contexts.

This may be a feature of our study system because sustainability extension programs are advanced within California viticulture and wine grape-growing regions that have more similarities than differences. Mental models from social-ecological systems with more stark differences may show larger differences in how goals are linked to strategies. More research is needed to confirm or disconfirm the hypothesis that concrete strategies are more sensitive to geographic and other contextual variation.Managing knowledge systems to link knowledge and action is a core goal in sustainability science . Knowledge systems include the institutional arrangements, organizations, and social networks that facilitate the transmission of knowledge among decision makers. Our results suggest that knowledge about sustainability, participation in extension programs, and practice adoption are mutually reinforcing processes. In agriculture, local extension programs and partnerships have played a crucial role in managing knowledge systems . In the case of California viticulture specifically, there is a substantial body of literature demonstrating that these programs have had a positive influence on farmer adoption of sustainability practices . The positive association we found between farmer sustainability cognition, participation in extension activities, and practice adoption indicates that knowledge systems do help expand practitioner understanding of social-ecological systems and influence their management behaviors. Extension programs can accelerate the development of knowledge and understanding about sustainability by clarifying the linkages among central sustainability goals and the associated strategies and practices for achieving them. An important component of this learning process may be the explicit use of the concept of sustainability,dutch buckets system as it can serve as a heuristic for guiding practitioner decision making with a framework for balancing economic, ecological, and social costs and benefits. Thinking in terms of sustainability does track with behavior, and knowledge systems have the ability to support this process by providing opportunities for learning.Sustainability and climate-focused initiatives announced by the United States federal government, states, and private sector entities could have meaningful impacts on land use sectors by affecting trends in land use and management as well as shifting commodity markets. Recent policy announcements include potential land-based greenhouse-gas mitigation strategies associated with ambitious new climate targets as part of rejoining the Paris Agreement , as well as a recent presidential executive order protecting 30% of U.S. lands and waters by 2030. The US Department of Agriculture Innovation Initiative has established ambitious targets for the next three decades to increase agricultural productivity by 40%, reduce food waste by 50%, reduce nutrient loss to run of by 30%, reduce carbon emissions, and increase biofuel and biomass production.Other policies may not have a primary objective that is environmental or sustainability-focused, but could nonetheless support policies in this domain by shifting resource demands and improving environmental outcomes. Two examples of indirect policy objectives that could interact with sustainability and climate initiatives include enhancing agricultural productivity growth and promoting healthier diets. If widely adopted, U.S. government recommendations for healthier diets could alter protein consumption away from beef and pork and toward plant-based foods, which could indirectly benefit climate and sustainability goals . Furthermore, previous research suggests that agricultural productivity growth can complement climate change mitigation . However, it is unclear how these policy targets could be achieved in isolation, what role market adjustments will play, and how healthier diet transitions and agricultural productivity enhancement might interact.While there have been several recent studies examining combinations of sustainability-related U.S. policy targets , the literature modeling U.S. agriculture and forestry is currently lacking in its representation of demand-side sustainability policies, including transitions to healthier diets.

While shifting to healthier diets is critical to reducing the noncommunicable disease burden , understanding how dietary change could shift resource-intensive commodity production, land use and ecosystem services can help inform complementary sustainability and climate policy actions. U.S. food systems are characterized by high levels of grain and oil seed production to support a highly productive domestic livestock sector and domestic diets that are relatively rich in meat-based proteins and oils , as well as international demands for U.S.-sourced agricultural products. Sustainability priorities such as increasing biodiversity protection or ecosystem service provision could benefit from dietary shifts that reduce pressure on U.S. agriculture’s intensive and extensive margins. Simultaneously, increasing productivity growth in U.S. agriculture could increase incomes and increase comparative advantage for international trade, which may or may not have land sparing effects. The literature on environmental impact of human diets has converged on the multiple sustainability benefits of diets lower in animal-based foods and higher in plant-based foods . These studies have either examined the global impacts of all countries adopting more sustainable or healthier diets or the domestic impacts of changes to a single country’s dietary preferences . Rarely have studies quantified both domestic and global sustainability metrics of a single county’s dietary changes or the country-specific sustainability impacts of the rest of the world adopting healthier diets. In addition, many studies focus on quantifying the impacts of specific personal dietary preferences , rather than a healthier average national diet. Several studies in the U.S. have quantified the sustainability impacts of omnivorous healthy diets recommended by the Dietary Guidelines for Americans . However, there is significant disagreement about whether the DGA diets have lower GHG, land use, or water use than the average American diet today . A handful of these studies have reported slightly lower land use requirements , and three out of four available studies showed similar or greater GHG emissions . The majority of studies quantifying the sustainability of alternative diets and dietary shifts in the U.S. use life-cycle assessments to measure environmental impacts of food production chains . However, LCA studies are limited in being able to quantify land use and land use change and allow for regional variation . Moreover, for projecting the environmental impacts of future dietary changes, it is critical to provide estimates that represent dynamic, rather than steady-state, industry and economic conditions.Alternative approaches such as economic partial-equilibrium models represent the agricultural, forestry, and other land use sectors in detail, and are deliberately designed to estimate land-use-related impacts, a key gap in the existing literature on the sustainability of U.S. diets . The global scale of many of these models allows representation of international trade and thus evaluation of leakage effects of domestic policies. Indirect sustainability levers such as shifting dietary preferences have received substantially less attention in the land use modeling literature relative to carbon pricing , bioenergy, and traditional conservation incentives. However, recent analysis has started to move in this direction . Partial-equilibrium models of the land sectors, such as GLOBIOM, which we employ in this study, are designed to maintain empirically observed market relationships between supply, demand, and prices. These models endogenously determine the demand for certain foods, productivity of specific crops, and the productivity of the livestock sector.

The isotope-labeling was reversed in replicate experiments to minimize false positives

In order to elucidate the biochemical mechanism of BZS1 function, we performed a SILIAIP-MS analysis of the BZS1 protein complex. We transformed Arabidopsis with a construct that over expresses a BZS1 protein fused with the yellow fluorescence protein at the C-terminus driven by the constitutive 35S promoter . A transgenic line that showed mild dwarf and dark-green-leaf phenotypes, resembling the bzs1-D mutant , was selected for the analysis. Pair-wised comparison was designed to seperately compare BZS1-YFP and 35S::YFP transgenic plants with non-transgenic wild type, to determine proteins associated with BZS1-YFP and YFP alone, respectively. To obtain complete 15nitrogen labeling of young seedlings, we first grew BZS1-YFP, YFP and wild-type plants hydroponically in medium containing 15N, and obtained stable isotope-labeled seeds . These 15N-labeled seeds and regular 14N seeds were grown again on corresponding 15N or 14N medium to obtain 5-day-old seedlings for further analysis . For each pair of isotope-labeled sample and control, equal amount of tissues was mixed, and the protein extract was used for immuno precipitation using the GFPtrap beads. The immuno precipitated proteins were separated in SDS-PAGE, gel bands were in-gel digested, and the tryptic peptides were analyzed by mass spectrometry . Mass spectrometry analyses of the two BZS1-YFP immuno precipitation experiments identified 514 and 383 proteins, respectively, with 279 proteins identified in both repeats . A smaller number of proteins were identified in the YFP experiments . Quantitation of isotope ratios showed median ratios of 1.16 and 1.23 for the two BZS1-YFP experiments,planting gutter and 1.0 and 0.92 for the two YFP control experiments. The protein ratios of the YFP control datasets had standard deviation of 0.23 and 0.57 .

Using 2× median as cutoff, 16 proteins were enriched in BZS1-YFP compared to wild-type control in the two repeat experiments. The YFP and wild type comparison identified 2 proteins that were enriched over 2× median, presumably due to association with YFP or false discovery, suggesting a false discovery rate <0.8% . The 15 proteins enriched by BZS1-YFP were not enriched by YFP alone, and thus were considered BZS1-associated proteins . Among the BZS1-associated proteins are COP1 and HY5, two key regulators of the light signaling pathways, as well as BZS1/BBX20’s homologs STH2/BBX21 and STO/BBX24 . To verify the interaction between BZS1 and COP1 in vivo, we performed immuno precipitation of BZS1-YFP from the BZS1-YFP transgenic Arabidopsis seedlings using anti-GFP antibody, and probed the immunoblot with anti-COP1 antibody. The results showed that COP1 co-immuno precipitates with BZS1-YFP , confirming that BZS1 interacts with COP1 in plants. Consistent with BZS1’s interaction with the COP1 E3 ubiquitin ligase, the immuno precipitated BZS1-YFP can be detected by anti-ubiquitin antibody, and the level of ubiquitination was increased by treatment with proteasome inhibitor MG132 . We further confirmed the direct interaction of BZS1 and HY5 by yeast two-hybrid assays . Further, when transiently co-expressed in Nicotiana benthamiana, the BZS1-myc protein was co-immuno precipitated by the HY5-YFP protein , confirming their interaction in plant cells. Similarly, the STH2-myc protein was co-immuno precipitated by BZS1-YFP . These results confirmed the SILIA-IP-MS results that BZS1 interacts with COP1, HY5, and STH2/BBX21. To determine the functional relationship between BZS1 and HY5, we first compared previously published transcriptomic data from BZS1-overexpression plants with chromatin immuno precipitation-microarray data of HY5 direct target genes . The result showed that 56.3% of BZS1-activated genes are HY5 targets while only 13% of BZS1-repressed genes are HY5 targets . Such significant overlap betweenBZS1-activated and HY5-bound genes suggests that BZS1 interacts with HY5 to activate gene expression.

Fusing a transcription repressor domain, such as the SRDX domain, to a transcription activator has been shown to have a dominant negative effect . Over expression of the BZS1-SRDX fusion sequence driven by 35S promotor in Arabidopsis caused a long-hypocotyl phenotype and reduced anthocyanin accumulation , which were similar to the phenotypes of loss-of-function mutant hy5-215 but opposite to the phenotypes caused by BZS1 over expression, further supporting that BZS1 functions as a transcription activator together with HY5. The BZS1-SRDX plants grown in the dark did not show any obvious phenotype , consistent with HY5 and BZS1 being degraded in the dark. To further investigate whether BZS1 function requires HY5, we crossed BZS1-YFP with hy5-215. The BZS1-YFP/hy5-215 plants showed similar phenotypes of long hypocotyls and low anthocyanin accumulation as hy5-215 , demonstrating that BZS1 activity requires HY5. Interestingly, the BZS1-YFP protein accumulates at a higher level in the hy5-215 mutant than in wild-type background , suggesting that HY5 negatively regulates BZS1 accumulation while required for BZS1 function. On the other hand, the RNA levels of HY5 and HYH are higher in BZS1-YFP line but lower in BZS1-SRDX seedlings as compared with those in wild type . Immunoblot analysis also confirmed that the HY5 protein level was increased in the BZS1-YFP line and reduced in the BZS1-SRDX line . These results indicated that BZS1 and HY5 proteins not only interact directly, but also influence each other’s protein abundance. A previous study showed that HY5 is required for SL inhibition of hypocotyl elongation. The HY5 protein level is increased by SL treatment and the hypocotyl elongation of hy5 is partially insensitive to SL . Since BZS1’s function is dependent on HY5 in the light, we examined if BZS1 is also involved in SL signaling. As reported previously , treatment with 1 μM GR24, an analog of SL, dramatically inhibited the hypocotyl elongation of wild-type seedlings but had no effect on the SL insensitive mutant max2-3 . We found that the hypocotyl elongation of BZS1-SRDX seedlings was partially insensitive to GR24, similar to the hy5-215 mutant.

The GR24 treatment decreased the hypocotyl length of wild-type seedlings by about 72% compared to the untreated control, but only by about 17% for hy5-215 and 30% for the BZS1-SRDX seedlings . GR24 also increased the chlorophyll content in wild-type plants by about 24%, but had no significant effect in max2-3, hy5-215 and BZS1- SRDX seedlings . Additionally, GR24 induced HY5 accumulation in wild-type background but not in the BZS1-SRDX seedlings . These results indicated that, like HY5, BZS1 also plays an important role in SL regulation of hypocotyl elongation and chlorophyll accumulation. We then tested if SL regulates the expression of BZS1/BBX20 and its homologs. Real-time reverse transcription PCR analysis showed that GR24 increased the expression level of BZS1/BBX20 mRNA in wild type, but not in the max2-3 mutant . Interestingly, expression levels of other members of BBX IV family, including STH2/ BBX21, were not dramatically affected by GR24. Immunoblot analysis confirmed that GR24 treatment increased the levels of the BZS1-myc protein expressed from the BZS1 native promoter and the BZS1-YFP protein expressed from the constitutive 35S promoter, suggesting that SL regulates BZS1 at both transcriptional and post transcriptional levels . These results indicated that BZS1 plays a positive role in SL signaling downstream of MAX2 at the early stage of seedling development. Seedling development is crucial for establishment of life for a plant, and is thus highly responsive to a wide range of environmental and hormonal signals. The signaling pathways that transduce these signals are highly integrated at the molecular level to ensure coherent cellular responses and optimal growth according to environmental condition and endogenous physiology . This study uncovers additional mechanisms for such signal integration. Our quantitative proteomic analysis of the BZS1 complex reveals BZS1’s interaction with HY5,gutter berries as well as provides direct evidence for in planta BZS1-COP1 interaction. Genetic analyses using over expression and dominant negative loss-of-function transgenic plants demonstrate that BZS1 interacts with HY5 to activate gene expression and promote photomorphogenesis. Further, we find that BZS1 also mediates SL regulation of HY5 level and hypocotyl elongation. Together with previous finding of BZS1 function downstream of the BR pathway , our study establishes BZS1 as a key integrator of light, BR, and SL signals for regulating seedling morphogenesis. IP-MS is a powerful method for identification of interacting proteins, which has been widely used in dissecting signal transduction pathways . With increased sensitivity of modern mass spectrometers, IP-MS tends to identify not only specific interacting proteins but also large numbers of non-specific proteins. Under our experimental conditions, over 300 proteins were identified in each IP-MS analysis. Distinguishing specific from non-specific interactors is challenging without quantitative measurement. SILIA-IP-MS provides an ideal quantitative method for this purpose, as the sample and negative control can be mixed at an early step of the immuno precipitation experiment to avoid technical variations. Indeed, among the large numbers of proteins identified by mass spectrometry, only 29 showed enrichment by the BZS1-YFP fusion protein, and thus were considered BZS1-associated proteins. The interactions of BZS1 with HY5, COP1, and its homolog STH2/BBX21 were confirmed by yeast two-hybrid or coimmuno precipitation assays. Consistent with COP1-mediated ubiquitination of BZS1, our BZS1-interactome data includes ubiquitin and one proteasome activating protein PA200 .

In theory, the ratio between sample and negative control should be infinite for proteins that specifically interact with the bait protein in SILIA-IP-MS. However, due to background signals in the control samples, either from non-specific binding of proteins in immuno precipitation or interfering signals in MS1, the ratios actually distribute within a wide range. For example, Hubner et al. observed that pull-down with Aly-GFP leads to only moderate enrichment because Aly itself binds to control beads as well. In our study, only 2 of the 254 proteins identified in the YFP sample were enriched over 2× median, suggesting that even 2-fold cutoff yields low false discovery rate when two reverse-labeled replicates are used. Our genetic analyses support that BZS1 interacts with HY5 to activate gene expression and promote photomorphogenesis. First, comparison of genome-wide data shows that BZS1 tends to activate, rather than repress, HY5 direct target genes . Second, dominant inactivation of BZS1 causes similar phenotypes as the hy5-215 mutant , supporting that BZS1 and HY5 act in the same or overlapping pathway. Third, the phenotypes of BZS1-YFP plants are suppressed by hy5-215 , confirming that BZS1 functions in a HY5-dependent manner. These results together provide strong evidence for a model that BZS1 interacts with HY5 to activate HY5-bound target genes. BBX proteins contain one or two B-box zinc finger motifs in their N-terminal regions, and are organized into five subfamilies . The fourth subfamily includes eight B-box proteins containing two tandem B-boxes without CCT domain . Our study together with previous studies show that five members of the BBX subfamily IV interact with COP1 and HY5 . Thus, interaction with HY5 seems to be a common mechanism for these B-box proteins to regulate gene expression. Interestingly, BZS1/BBX20, STH2/BBX21 and LZF1/STH3/BBX22 are positive regulators in photomorphogenesis, while BBX19, STO/BBX24 and STH/BBX25 are negative regulators . Our finding of STH2/BBX21 and STO/BBX24 as interactors of BZS1/BBX20 suggests that these factors form hetero-dimers. The dominant negative effect of the BZS1-SRDX fusion indicates that BZS1/BBX20 normally functions as a transcription activator, which is consistent with previous finding that STH2/BBX21 functions as a transcription activator . It has been reported that STO/BBX24 and STH/BBX25 interact with HY5 and most likely inhibit HY5 function by forming inactive heterodimers . Our identification of STO/BBX24 as a BZS1-associated protein suggests another possibility that STO/BBX24 may form a non-functional heterodimer with BZS1/BBX20 and hence inhibit BZS1/BBX20 activity. In addition to direct interaction between BZS1 and HY5 proteins in regulating target gene expression, BZS1 and HY5 also regulate each other’s expression level. BZS1 positively regulates the RNA and protein levels of HY5 . Recent studies have shown that HY5 binds to its own promoter to regulate its own level , thus BZS1 may regulate HY5 transcription through interaction with HY5 protein. In contrast, the BZS1 protein level is increased in hy5-215, suggesting a negative regulation by HY5 at the protein level. HY5 may promote BZS1 degradation by interacting with COP1. Similarly, a previous study showed that the degradation of BBX22 is also promoted by both COP1 and HY5 , whereas BBX22 transcription is directly activated by HY5 and repressed by BBX24 . Such positive and negative regulation between interacting partners potentially contributes to the signaling dynamics during dark-to-light transition and fluctuating light intensities.Our study uncovers a major role for BZS1 in SL response.

Abiotic stress alters the susceptibility of plants to many pathogens

As sessile organisms, plants are presented with numerous biotic challenges such as herbivory and pathogen attack. Plants initiate responses to these challenges by harnessing tightly regulated phytohormone networks. Salicylic acid levels increase in plants following pathogen infection and SA is critical for the development of systemic acquired resistance . There are two enzymatic pathways for the generation of SA: one via phenylalanine ammonia lyase and the other via isochorismate synthase . In tomato , Arabidopsis and Nicotiana benthamiana, most pathogen-induced SA appears to be synthesized via the ICS pathway . Plants with compromised SA synthesis or signaling have greatly diminished defenses against pathogens, as is the case with SA-deficient transgenic plants expressing a bacterial salicylate hydroxylase or ICS mutants like sid2 , and mutants in downstream targets of SA such as npr1 . SAR induction by biotic agents coincides with increases in SA levels and a systemic transcriptional reprograming that primes the plant to respond rapidly to minimize the spread or severity of further infections . This transcriptional reprograming includes the expression of pathogenesis-related genes and deployment of peroxidases and other defense factors. In addition to induction by biotic agents, SAR responses are induced by exogenous application of SA to the foliage or roots . Plant activators are chemicals that have no direct antimicrobial activity but induce disease resistance . A number of synthetic compounds have been developed that induce SAR by increasing SA accumulation and/or by acting on downstream targets of SA . For example, the plant activator, probenazole, effective against bacterial, fungal, and oomycete diseases, stimulates SAR by increasing SA levels . 1,2,3-Benzothiadiazole-7-thiocarboxylic acid-S-methyl-ester , sold under the trade name, Actigard,grow bucket stimulates SAR in many plant species without inducing SA accumulation . Tiadinil [TDL; N–4-methyl-1,2,3-thiadiazole-5-carboxamide] is a plant activator that was registered in Japan in 2003 under the trade name, V-GET. TDL was developed for disease management in rice where it is applied to nursery-grown seedlings for transplanting to production fields . TDL is very effective for control of rice blast disease caused by Magnaporthe oryzae and appears to induce resistance in a manner similar to BTH by acting on downstream targets of SA .

The TDL metabolite,4-methyl-1,2,3-thiadiazole-5-carboxylic acid, is responsible for the SAR activation .The effect of brief episodes of root stress such as salinity and water deficit at levels that commonly occur in agriculture is well documented in plant–oomycete interactions, wherein stress events predispose plants to levels of inoculum they would normally resist . The phytohormone abscisic acid accumulates rapidly in roots and shoots as an adaptive response to these abiotic stresses, but also contributes to the increased disease proneness of the plants . Antagonism between SA and ABA is well documented in relation to plant defense responses to pathogens . Previously, ABA was found to have an antagonistic effect on SAR which was induced by 1,2-benzisothiazol-3-one1,1-dioxide and BTH in Arabidopsis and tobacco . However, it is not known if plant activators that target SA signaling impact the ABA-mediated susceptibility to root pathogens that occurs following predisposing root stress in tomato. Because of the potential for unwanted trade offs and signaling conflicts in plants exposed to different stresses, as can occur in the field, we investigated how predisposing root stress impacts chemically induced resistance in tomato. The objective of this study was to determine the effect of pretreatment of tomato seedlings with TDL and BTH on salt-induced predisposition to the foliar bacterial pathogen Pseudomonas syringae pv. tomato and to the soil borne oomycete pathogen Phytophthora capsici. TDL is of particular interest in the context of soil borne pathogens such as Phytophthora capsici because it is often applied to plants as a root dip. We also determined the impact of SA, TDL and BTH on ABA accumulation during a predisposing episode of salt stress. The results show that TDL applied to roots strongly protects the leaves from disease caused by Pst in both non-stressed and salt-stressed plants. In contrast, neither TDL nor BTH protects roots from Phytophthora capsici.

The protection induced by plant activators against Pst does not result from reduced ABA accumulation and, although overall disease is less in both non-stressed and salt-stressed plants by chemically induced SAR, plant activators do not reverse the salt-induced increment in disease severity.To determine the effect of SA on ABA accumulation during salt stress, ABA levels were measured in WT plants pre-treated with SA, TDL, or BTH. Following salt stress treatment for 18 h, roots and shoots were collected and immediately frozen in liquid N2.The tissues were lyophilized and placed at −20◦C until extraction. The lyophilized tissue was ground in liquid N2 to a fine powder with a mortar and pestle, 50–100 mg samples were collected, and each sample transferred to a micro-fuge tube. Cold 80% methanol containing butylated hydroxytoluene at 10 μg ml−1 was added to each tube, which was then vortexed. The extracts were placed on ice and agitated occasionally for 30 min. The tubes were centrifuged for 5 min at 10,000 × g, and the supernatants collected. The pellet was extracted with 0.5 ml of 80% methanol and centrifuged to collect the supernatant. This step was repeated, all three supernatants were combined, and the methanol concentration of the extract adjusted to 70%. The extracts were applied to pre-wetted Sep-pak C18 columns and eluted with 5 ml of 70% methanol. The eluate containing ABA was concentrated to near dryness at 37◦C under vacuum and the volume adjusted to 300 μl with deionized water. The samples were analyzed by competitive immuno assay with an ABA immuno assay kit according to the manufacturer’s directions. Results are expressed as nanomoles of -ABA per gram dry weight of tissue. To determine the effect of the nahG transgene on ABA levels, roots and shoots from WT and NahG plants were processed using the same procedure as above.To determine if plant activators induce resistance to Pst under different stress regimes in our experimental format, roots of hydroponically grown seedlings of cv. “New Yorker” were treated with TDL and then either not salt-stressed or exposed to 0.2 M NaCl for 18 h prior to inoculation.

In preliminary experiments, several concentrations of TDL were evaluated for phytotoxicity and for efficacy against bacterial speck disease with 10 ppm TDL selected as this concentration provided an optimal response. Concentrations higher than 10 ppm of TDL caused a slight bronzing of the roots and depressed growth of the seedlings, suggesting a mild phytotoxicity of the chemical in our experimental format at these higher levels. Inoculated salt-stressed seedlings had more severe disease symptoms and a significantly higher titer of pathogen than non-stressed, inoculated plants. Pretreatment with TDL at 10 ppm significantly reduced Pst colonization and symptom severity in “New Yorker” plants in both non-stressed and salt-treated seedlings . However, TDL did not prevent the proportional increase in Pst colonization observed in salt-stressed plants relative to the non-stressed controls.Since TDL harnesses SA-mediated defenses, we treated SA deficient NahG plants to see if TDL induces resistance under the different stress regimes in this highly susceptible background. As expected, NahG plants were more susceptible to Pst and accumulated significantly less SA following Pst infection than the WT background “New Yorker.” However, TDL provided strong protection in the NahG plants and mitigated the predisposing effect of salt-stress on bacterial speck disease.In a previous study we showed that ABA-deficient tomato mutants displayed a much reduced predisposition phenotype to salt stress . To determine if the protective effect of TDL is altered within an ABA-deficient tomato mutant,dutch bucket for tomatoes seedlings of WT and an ABA-deficient mutant within this background, sitiens, were treated in the same format and stress regimes as above. TDL significantly reduced Pst symptoms and colonization in both non-stressed and salt-treated plants of “Rheinlands Ruhm.” However, 3.6- and 5.4-fold increases in pathogen titer as a result of salt-stress were observed in both the control and TDL-treated plants, respectively, indicating that TDL did not prevent the proportional increase in Pst colonization in salt-stressed plants, similar to the results with “New Yorker” and NahG plants. In contrast, the sitiens mutant was not predisposed to Pst by salt stress and had significantly reduced symptoms and colonization by the pathogen than the background “Rheinlands Ruhm” . Nonetheless, TDL pretreatment of sitiens provided further protection against Pst .To determine if plant activators protect tomato roots and crowns against the oomycete pathogen, Phytophthora capsici, and predisposing root stress, tomato seedlings were treated with TDL or BTH , not stressed or salt-stressed as above, and then inoculated. There was no protection provided by the plant activators against disease caused by Phytophthora capsici in either the control or salt-treated plants, as reflected in symptom severity and pathogen colonization .Because elevated levels of ABA in tomato can enhance susceptibility to Pst and Phytophthora capsici, the effect of SA, TDL, and BTH on ABA levels was determined in roots and shoots. ABA concentrations in either shoots or roots at the time selected for inoculation in our treatment sequence were not altered by SA . However, a trend of increasing ABA accumulation was observed in TDL- and BTH treated “New Yorker” plants relative to the corresponding control plants . Although the increase in ABA accumulation in the plants treated with these plant activators is not statistically significant at P ≤ 0.05, it can be said that SA, TDL, and BTH do not reduce ABA content relative to untreated plants . In addition, salt stress did not further increase the levels of ABA in plants that had been pretreated with TDL or BTH, which were similar to the salt stressed controls.In a previous study, we demonstrated the predisposing effect of salt stress and a role for ABA as a determinative factor in predisposition in the tomato–Phytophthora capsici interaction .

The present study is the first report of salt-induced predisposition to the bacterial speck pathogen, Pst, in tomato. Furthermore, the results with the ABA-deficient sitiens mutant are consistent with the salt-induced susceptibility to Pst being mediated by ABA . These results conform to studies in Arabidopsis where ABA has been reported to promote susceptibility to Pst .Because SA has been shown to protect tomato against salt stress, possibly by an ABA-dependent mechanism , plant activators that operate via the SA pathway were evaluated for effect on salt-induced predisposition. Protection of tomato against bacterial speck disease by BTH is well documented , and TDL has previously been shown to reduce the severity of bacterial and fungal infections without inducing SA accumulation . Here, TDL was shown to protect against Pst in both non-stressed and salt-stressed tomato plants. TDL pretreatment strongly reduced disease and colonization by Pst in both “New Yorker” and SA-deficient NahG plants. TDL, or more likely its biologically active metabolite, SV-03, presumably allows the NahG plants to mount an SAR response to Pst infection in the absence of SA accumulation . TDL provided protection in both non-stressed and salt-stressed plants, but did not reverse the predisposing effect of salt stress. An increase in Pst colonization was observed in the salt-stressed, TDL-pretreated plants of both genotypes, with comparable percentage increases relative to the corresponding non-stressed controls in “New Yorker” and NahG plants. This indicates that TDL does not reverse the salt-stress effect on disease, per se, and likely targets stress network signaling independently of an ABA-mediated process that conditions the salt-induced susceptibility observed in this system . “Rheinlands Ruhm” also displayed salt-induced predisposition to Pst. Pretreatment with TDL significantly reduced Pst colonization in both “Rheinlands Ruhm” and sitiens . Similarly, TDL provided protection in both non-stressed and saltstressed plants, but did not reverse the predisposing effect of salt stress in “Rheinlands Ruhm” plants. The salt-induced increment in colonization by the pathogen was comparable in both the untreated and TDL-treated plants . The ABA-deficient mutant, sitiens, is considerably less susceptible to Pst than its background “Rheinlands Ruhm,” and does not exhibit salt-induced predisposition .Protection by plant activators against foliar pathogens is well established . However, relatively few studies have examined these compounds against soilborne pathogens and so TDL and BTH were evaluated for protection against root infection by Phytophthora capsici. Neither TDL nor BTH induced resistance or impacted salt-induced predisposition to Phytophthora capsici . Phytophthora capsici is an aggressive root and crown pathogen with a hemibiotrophic parasitic habit that triggers both SA- and jasmonic acid-mediated responses during infection of tomato .

Soil water extracts were prepared according to a published method with some modifications

The whole-plant N2 fixation potential was calculated by multiplying the total dry nodule biomass of each plant and the N2 fixation potential, which had been normalized to dry nodule biomass. To understand how plant effects were related to CNM concentration-dependent agglomeration in moist soils, the short- and long-term stabilities of CNMs were studied in soil water extracts. Briefly, control soil was weighed into separate 50 mL centrifuge tubes with 1:5 w/v Nanopure water . The centrifuge tubes were sealed securely and shaken horizontally on a shaker for 3 h . The extract was centrifuged to separate large solids, and the supernatant was decanted. The supernatant was vacuum filtered through a 0.22 μm membrane filter , and the filtrate was collected as the final soil extract and stored prior to use. A CNM stock solution was prepared by weighing dry CNM powder into the filtered soil extract, then mixing by brief sonication using a Branson 1510 bath sonicator . Aliquots of the dispersed CNM stock solution were further diluted by the filtered soil extract to yield a final lower concentration of 10 mg L−1. These two CNM concentrations were chosen for comparing the effect of lower versus higher CNM concentrations on CNM agglomeration in moist soil; both concentrations are relevant to the CNM doses used in the plant exposure experiment . The CNM suspensions were bathsonicated immediately before use in static agglomeration and sedimentation studies, hydroponic nft channel which were performed over a long time period . The changes of CNM hydrodynamic diameter and derived count rate with time were measured using dynamic light scattering in a Zetasizer NanoZS90 . DLS measurements were made every 15 s for the first 12 h, then daily from 1 to 7 d, and finally weekly until 56 d.

Meanwhile, dynamic CNM sedimentation in the soil extract was monitored by measuring the suspension absorbance at 600 nm using a UV-1800 spectrophotometer . Sedimentation patterns were inferred from the time course of normalized suspension absorbance at 600 nm . The UV-1800 spectrophotometer was zeroed using Nanopure water. The absorbance of the filtered soil extract alone was monitored over time as well, to confirm there was no interfering absorbance from the soil extract in the CNM suspensions. The zeta potential and electrophoretic mobility of the filtered soil extract and of 10 mg L−1 CNMs were also obtained using the Zetasizer NanoZS90. For either DLS, absorbance, ζ potential, or EPM, at least three replicate measurements were performed. Environmental scanning electron microscopy was performed to visualize the agglomerate morphologies of 10 and 300 mg L−1 CNMs in the soil extract, against a clean quartz sand substrate. Specimens were prepared by dispensing approximately 100 μL of the CNM suspensions onto clean quartz sand overlaying a 10 mm stainless steel conical-well Peltier stub. Imaging was by an FEI Co. XL30 field emission gun microscope , operated at 15 kV accelerating voltage, in a 3.5-torr chamber pressure with a gaseous secondary electron detector in environmental mode. Data are shown as the mean ± SE . For each CNM type, one-way analysis of variance with Tukey’s or Games-Howell post hoc multiple comparisons was used to determine significant differences between treatments . Homogeneity of variance was tested with Levene’s test. To explore dose–response relationships, correlations were performed between plant growth and end point metrics with soil CNM concentrations, using both two-tailed linear and power regression models. Correlation analyses were conducted both with and without the control data. Statistical analyses were performed using Microsoft Excel 2013, IBM SPSS Statistics 23, and SigmaPlot 12.3.P. vulgaris is characterized by a particular evolutionary history.

Recent analyses based on sequence data presented clear evidence of the Mesoamerican origin of common bean, which was most likely located in México . The expansion of this species to South America resulted in the development of two ecogeographic distinct genetic pools with partial reproductive isolation . After the formation of these genetic pools -between 500,000 and 100,000 years ago – domestication took place, independently in the Mesoamerican and the southern Andean regions of the American continent . Genome analysis of BAT93 and G19833 , P. vulgaris sequenced model genotypes, has initially revealed interesting differences, for example between their genome size and number of annotated genes . The common bean is the most important legume for human consumption. In less favored countries from Latin America and Africa, common bean are staple crops serving as the primary source of protein in the diet. Soil acidity in these tropical regions is a major constraint for crop productivity, usually resulting in a combination of nutrient deficiency and metal toxicity . In acidic soils, aluminum toxicity is the primary factor of growth restriction, resulting in the inhibition of root growth and function, as well as in the increased risk of plants to perish of drought and mineral deficiencies, thus decreasing crop production . High Al levels mainly affect roots causing an arrest of the growth of the principal and lateral roots . In Arabidopsis, the regulation of root growth is modulated by an ABC transporter‐like protein, annotated as ALUMINUM SENSITIVE PROTEIN 3 , which is localized in the tonoplast, suggesting a role in Al vacuolar sequestration . The LOW PHOSPHATE ROOT 1 ferroxidase, an ALS3– downstream protein of the phosphate-deficiency signaling pathway, is involved in root growth inhibition, by modulating iron homeostasis and ROS accumulation in root apical meristem and elongation zone . In root cells, AlT can affect multiple areas, as the plasma membrane, the cell wall and symplastic components .

Common bean is known to be highly sensitive to AlT but this sensitivity is genotype-dependent . In 2010, the evaluation of the root morphological traits related to AlT of 36 P. vulgaris genotypes revealed that Andean genotypes were more resistant to Al than Mesoamerican ones . Mendoza-Soto et al. reported that Mesoamerican common-bean plants subjected to high Al levels for short periods showed decreased root length as well as characteristic symptoms of AlT, such as ROS accumulation, callose deposition, lipoperoxidation and cell death in roots. Along other regulators, plant response to metal toxicity involves also microRNAs as part of the regulatory mechanisms. These molecules are a class of non-coding small RNAs of about 21 nucleotides in length, regulating gene expression at post-transcriptional level, guided by sequence complementarity, inducing cleavage or translational inhibition of the corresponding target transcript . The relevance of miRNA regulation in heavy metal tolerance is well documented; it has been demonstrated that heavy metal-responsive miRNAs show differential expression according to the toxicity level. Target genes of these miRNAs generally encode transcription factors that transcriptionally regulate networks relevant for the response to heavy metals. Additionally these encode transcripts for proteins that participate in metal absorption and transport, protein folding, antioxidant system, phytohormone signaling, or miRNA biogenesis and feedback regulation . High-throughput small RNA sequencing analyses have identified miRNAs that respond to AlT in roots of different plants species, however their function in response to AlT is largely unknown. Some of the target genes cleaved by AlT-responsive miRNAs encode disease resistance proteins, transcription factors or auxin signaling proteins . Our previous research indicated that P. vulgaris is no exception to this phenomenon. We identified common-bean miRNAs that respond to Al, these include conserved miRNAs that are Al-responsive in other plant species -i.e. miR319, miR390, miR393- and also miR1511 . miRNAs from the miR1511 family have been identified in non-legume plants like strawberry and poplar tree ,nft growing system although in the latter its nature as a miRNA has been discussed as it has been considered as part of a retrotransposon . Regarding legumes, miR1511 has been identified in Medicago truncatula and soybean . Also, miR1511 was identified in Mesoamerican common-bean cultivars, being more abundant in flowers and roots . However, this miRNA was not identified when analyzing the Andean G19833 reference genome . Genetic variation in MIR1511 has been reported in a comparative genotyping analysis of different Asian accession of domesticated soybean as well as its wild type progenitor Glycine soja. While sequences of mature miR1511 and miR1511* were found in G. max accessions, the sequences of annual wild G. soja showed insertion/deletion in the stem-loop region of MIR1511 that included complete or partial deletions of mature miR1511 sequence . Updated research indicates that the miR1511 target gene is not conserved in the different plants where it has been identified. In strawberry, the miR1511 targets an LTR retrotransposon gene .

Inconsistencies about the nature of miR1511 target gene also hold for legume species. For instance, different targets have been proposed for soybean ranging from genes coding for proteins involved in the regulation of nitrogen metabolism to proteins relevant in plant cell development . While in other species such as M. truncatula target genes have been searched but have not been identified. The SP1L1 transcript has been proposed as the common-bean miR1511 target , however despite several efforts from our and other groups this prediction could not be experimentally validated. These results suggested a species-specific selection of the corresponding target thus it was essential to experimentally validate the nature and possible function of the miR1511 target gene in common bean. Recent analyses led us to predict an ABC-2-type transporter-related gene, annotated as Aluminum Sensitive Protein 3 , as the target for miR1511. In this work we present its experimental validation. In addition, we genotyped MIR1511 in ecogeographically different common-bean cultivars and investigated the role of miR1511 and its corresponding target in the regulation of plant response to AlT. The comparison of MIR1511 sequence from BAT93 vs. G19833 P. vulgaris reference sequences showed a 58-bp deletion in the G19833 genotype. Such deletion comprised around 57% of pre-miR1511 sequence and included 7-bp and 10-bp of mature and star miR1511, respectively . To explore this phenomenon at a larger scale within the Phaseolus genus, we analyzed Genotyping-By-Sequencing data from 87 genotypes originated from a single genetic population , called non-admixed genotypes. These included genotypes from three Phaseolus species and different populations of wild P. vulgaris: three populations from the Mesoamerican , one from the Andean , and one from the Northern Peru–Ecuador gene pools . All the genotypes belonging to the Andean gene pool and part of the Mesoamerican genotypes displayed a truncated MIR1511, in contrast to the Northern Peru– Ecuador genotypes and the other Phaseolus species that presented a complete version of the MIR1511 in their genome. A population clustering of P. vulgaris genotypes confirmed these results and showed that in the three Mesoamerican populations only a part of the MW1 cluster presented the MIR1511 deletion . Predicted target genes for P. vulgaris miR1511 include SP1L1-like  and isopentyl-diphosphate delta-isomerase , previously reported , and a protein with unknown function and the Aluminum Sensitive Protein 3 , from our recent bio-informatic analysis. From these predicted targets, ALS3 is the only one possibly related to AlT, as reported for Arabidopsis , and showing an adequate binding-site penalty score , thus the 5’RLM-RACE assay was used to experimentally validate the ALS3 mRNA cleavage site. As shown in Figure 3a, a significant number independently cloned transcripts mapped to the predicted site of cleavage, between the nucleotides at positions 457 and 458 of the transcript, which corresponds to position 9 and 10 of the predicted miR1511 binding site, thus confirming a miR1511-induced degradation. The other two degradation events mapped to 7 nucleotides upstream and 17 nucleotides downstream of the miRNA-associated degradation site, suggesting random degradation. An additional action of miR1511 to induce translation inhibition of ALS3 mRNA in common bean, cannot be excluded. miR1511 target genes differ among plant species . In order to evaluate the specificity of the miR1511/ALS3 regulatory node in common bean, we analyzed the miR1511/ALS3 binding site sequence alignment from eight model plant species, including five legumes, which contain a precursor gene of miR1511 in their genome . Because of the deletion in MIR1511 from the G19833 genotype, we used the mature miR1511 and the corresponding ALS3 binding site sequences from the BAT93 Mesoamerican genotype, as representative of P. vulgaris. Among plant species analyzed, P. vulgaris was the only one that showed a binding-site penalty score lower than 5, corresponding to a score recommended to consider a small RNA-target binding as probably functional. For other species, the high penalty scores, ranging from 7.5 to 9, indicate a very low probability for the existence of a functional miR1511/ALS3 regulatory node .

Hydroponic Agriculture: Cultivating the Future of Sustainable Farming

Interestingly, suppression of endodermal ABA signalling seems to contribute to the inactivation of aquaporin-mediated Lpr in a wild-type Scheduling low but frequent NO3 − applications, at-tuned to crop demand, allows the crop to take up most of the NO3 − before it passes through the low-salinity zone into the saline fringes. Figure 7 simulates continuous NO3 − application and a scenario which applies NO3 − only every 10 d, while the total amount of NO3 − applied is the same for both simulations. High-frequency applications of NO3 − using drip irrigation in-creased N uptake efficiency in some cases .Both Casparian strips and suberin lamellae, two extracellular hydrophobic barriers located in the wall of endodermal cells of the root, are thought to play important roles in restricting the free diffusion of solutes and water . Casparian strips act as apoplastic barriers not only to block solutes moving into the xylem through the free space between cells, but also to prevent their backfow from the stele to the apoplast of the cor-tex. Suberin lamellae, due to their deposition between the endodermal plasma membrane and secondary cell wall, do not block aploplastic transport but rather limit transcellular transport of nutrients and possibly water at the endodermis. Cross talk between the Casparian strip and suberin lamellae exists, with suberin being deposited in response to disruption of Casparian strips . Tese extracellular barriers are therefore at a cross-road between control of mineral nutrient and water uptake. However, the mechanisms that allow plants to integrate both these barrier functions to enable the simultaneous uptake of sufcient water and mineral nutrients remain under explored. Te dirigent-like protein Enhanced Suberin1 functions in the correct formation of Casparian strips by allowing the lignin, deposited at the Casparian Strip Domain through the action of Peroxidase64 and the Respiratory Burst Oxidase Homolog F ,blueberry packaging to form into a continuous ring. In the absence of this dirigent-like protein defective Casparian strips are formed along with enhanced and early deposition of suberin in the endodermis.

A similar pattern of Casparian strip disruption and response is also observed when the Casparian Strip Domain is disrupted through the loss of Casparian Strip Domain Proteins. Tese changes lead to systematic alterations in the profile of mineral nutrients and trace elements accumulating in leaves, and this phenotype provided the first tool for identification of genes involved in Casparian strip development. Detection of the diffusible vasculature-derived peptides CASPARIAN STRIP INTEGRITY FACTORS 1 & 2 through interaction with the SCHENGEN3 receptor-like kinase is what drives this endodermal response to loss of Casparian strip integrity. Here, we report that detection of a loss of Casparian strip integrity at the root endodermis by the CIFs/SGN3 pathway leads to an integrated local and long-distance response. This response rebalances water and mineral nutrient uptake, compensating for breakage of the Casparian strip apoplastic seal between the stele and the cor-tex. This rebalancing involves both a reduction in root hydraulic conductivity driven by deactivation of aquapor-ins, and limitation of ion leakage through deposition of suberin in endodermal cell walls. This local root-based response is also coupled to a reduction in water demand in the shoot driven by ABA-mediated stomatal closure.Te dirigent-like protein Enhanced Suberin1 functions in the formation of Casparian strips by allowing the correct deposition of lignin at the Casparian strip domain. Te enhanced deposition of suberin in the esb1-1 mutant with disrupted Casparian strips can clearly be observed using the lipophilic stain Fluorol Yellow 088 close to the root tip , and this can be quantified by counting the number of endodermal cells afer the onset of cell expansion to the first appearance of yellow fuorescence . This early deposition of suberin is also verifed by the clear correspondence of FY 088 staining with enhanced promoter activity of known suberin biosynthetic genes, including GPAT5 monitored through both GUS staining and GFP fuorescence , and also others through GUS staining . This is further reinforced by the enhanced expression of known suberin biosynthetic genes in esb1-1 relative to wild-type . To better understand the causal link between Casparian strip integrity and enhanced deposition of suberin, we performed a reciprocal grafing experiment that revealed that the esb1-1 mutation is only required in the root to drive enhanced deposition of suberin at the endodermis, placing the function of ESB1 and the driver for increased suberin in the same tissue .

To determine the cause and effect rela-tionship between damaged Casparian strips and enhanced suberin we carefully monitored the first appearance of both Casparian strips and enhanced suberin in esb1-1. Using lignin staining in the Casparian strip marker line pCASP1::CASP1::GFP, we are able to observe that damaged Casparian strips are visible 2.5 days afer sowing . This is at least 12hr before the first indication of enhanced suberin biosynthesis, which we monitor using promoter activity of suberin biosynthetic genes GPAT5, FAR4, FAR1 and FAR5 . This was also verified by the direct observation of suberin deposition with FY 088 . Te observation that treatment with the CIF2 peptide, normally leaked from the stele through loss of Casparian strip integrity, can enhance suberin deposition in wild-type plants supports our interpretation that enhanced suberin deposition is a response to loss of integrity of the Casparian strip-based apoplastic diffusion barrier. Furthermore, loss-of-function of the receptor-like kinase SGN3, required for sensing of CIFs, blocks the enhanced deposition of suberin in esb1-1 and casp1-1casp3-1 based on a chemical analysis of suberin in esb1-1 , and also on FY 088 staining. We conclude that Casparian strip defects sensed by the CIFs/SGN3 surveillance system lead to enhanced deposition of suberin in the endodermis.Te observation that enhanced suberin is deposited as a response to loss of integrity of the endodermal-based diffusion barrier between stele and cortex, raises the question, what is the function of this increased suberin deposition? Previously, the extent of endodermal suberin has been shown to be part of the response to nutrient status . We therefore tested the selectivity to solutes σNaCl, in roots varying in the extent of suberin deposition and the functionality of Casparian strips. For this, we measured solute leakage into xylem sap of pressurized roots at increasing sodium chloride concentrations in the solution bathing the roots. Taken individually, σNaCl of roots of esb1-1, sgn3-3 and wild-type were not significantly different from one another , which is surprising given the disruption of the Casparian strip-based apoplastic diffusion barrier in both mutants.

However, removal of suberin in esb1-1, by endodermal-specific ectopic expression of a cutinase ,blueberry packaging box caused a significant decrease in σNaCl compared to wild-type plants , and a similar tendency when compared to esb1-1 . This supports the notion that enhanced suberin deposition at the endodermis helps prevent passive solute leakage caused by defects in the Casparian strips of the esb1-1 mutant. We also observed a significant decrease in σNaCl in the double mutant esb1-1sgn3-3 compared to both wild-type and sgn3-3 . It is known that SGN3 is required for the enhanced deposition of suberin that occurs at the endodermis in esb1-1 . Our observation that removal of this enhanced suberin in esb1-1sgn3-3 decreases σNaCl further supports our conclusion that the role of this increased suberin deposition is to limit solute leakage where Casparian strip barriers are disrupted.It has also been suggested that endodermal suberin may impact water permeability, though how is still unclear. To further address the role of enhanced endodermal suberin, we investigated root hydraulic conductivity of esb1-1 and observed a significant reduction by 62% with respect to wild-type . Importantly, this difference in esb1-1 Lpr originates mainly from a reduction in an aquaporin-mediated water transport pathway . We also observed that the azide-resistant water transport pathway was lower in esb1-1 than in wild-type , yet to a lesser extent than the aquaporin mediated pathway. Te dra-matic reduction in aquaporin-mediated Lpr in esb1-1 we observe is an intriguing fnding, which led us to consider if this lack of aquaporin activity in esb1-1 roots is due to a direct output from the CIFs/SGN3 signalling pathway, or if it represents an efect downstream of enhanced suberin deposition. We found that removal of endodermal suberin in esb1-1 through expression of CDEF1 in the endodermis had no further efect on Lpr . This rules out a role for suberin in the reduced aquaporin-mediated Lpr of esb1-1. However, in the esb1-1sgn3-3 dou-ble mutant, as compared to esb1-1, we observed a full recovery of Lpr back to wild-type levels . Loss of Casparian strip integrity in esb1-1 therefore appears to be sensed by the CIFs/SGN3 signalling pathway, which leads to the inactivation of aquaporins, thereby reducing Lpr . To support this conclusion, we show that exogenous application of CIF2 to wild-type plants for 3h induces a reduction in Lpr, and only in the presence of a functional SGN3 . We have established the existence of two critical outputs of the CIFs/SGN3 diffusion-barrier surveillance system. Tese are enhanced deposition of endodermal suberin limiting solute leakage, and the inactivation of root aquaporin activity reducing Lpr. Do these two independent outputs of the CIFs/SGN3 diffusion barrier surveillance system work in parallel, or in series with one response leading to the other? Te fact that removal of endodermal suberin in esb1-1 does not compensate for its reduced Lpr suggests that enhanced suberin deposition is not the cause of the reduced aquaporin-mediated Lpr. However, reduced activity of aquaporins through loss-of-function of the two major aquaporins PIP2;1 and PIP2;2 in the pip2;1pip2;2 double mutant, does cause significant increases in endodermal suberin deposition . A similar increase in suberin is also observed afer treatment with the aquaporin inhibitor sodium azide through observation of the activity of the transcriptional reporter pGPAT5::mCITRINE-SYP122 for suberin biosynthesis. GPAT5 expression is observed to expand toward the root tip after 6 hours only of sodium azide treatment .

Based on this evidence, we propose the following sequence of events. Casparian strip defects are detected by the apoplastic leakage of CIFs from the stele, being sensed by SGN3. Once activated, SGN3 signals the inactivation of aqua-porins thereby reducing Lpr which in turn leads to the early and enhanced deposition of endodermal suberin. Insuch a model, SGN3 would inhibit aquaporin function, which may appear at variance with the usual activation of aquaporins through phosphorylation. Yet, such an inhibition was recently described in the case of FERONIA, a protein kinase inactivating PIP2; 1 function through an as yet unknown mechanism.Abscisic acid has been shown to be involved in regulating both aquaporin activity reviewed in and suberin deposition, making ABA an interesting can-didate worth exploring for a role in downstream CIFs/SGN3 signalling. To probe this possibility we expressed the dominant negative allele of the regulator of ABA signalling ABA-INSENSITIVE 1 in the endoder-mis of esb1-1 using pELTP::abi1. This abi1 construct specifically blocks ABA signalling at the endodermis and delays suberisation in a wild-type background as previously shown in . In esb1-1, we observed abi1 to have no effect on either the inactivation of aquaporins or the enhanced deposition suberin . We also observe that aquaporin inhibition with sodium azide in the pELTP::abi1-1 line still induces expression of the suberin biosynthesis gene GPAT5 toward the root tip in the pGPAT::mCITRINE-SYP122 line, as observed in wild-type . Based on this, activation of ABA signalling in the endodermis does not link perception of Casparian strip defects with the downstream responses of reduced aquaporin-mediated Lpr or suberin deposition. Suppbackground .The esb1-1 mutant is known to have reduced stomatal apertures and enhanced wilting resistance. This suggests that the CIFs/SGN3 sensing system not only initiates a local root response to Casparian strip integrity but is also involved in initiating long-distance responses in the shoot. We observe reduced stomatal apertures in esb1-1 , and an analysis of the expression of a set of known ABA signalling and response genes in leaves suggest that this stomatal closure is part of an ABA driven response. The aba1 mutation confers a strong ABA deficiency.By generating an esb1-1aba1 double mutant, we investigated the ABA-dependent component in the leaf response we observe in esb1-1. ABA-defciency in esb1-1aba1 suppressed both the reduced stomatal aperture and the activation of expression of ABA signalling and response genes that we observe in esb1-1 .

Processing efforts congruent to the cloud infrastructure cannot be provided by the farm server

This documentation directly needs to fit for cross-compliance procedures with public authorities and personal calculations of the farm which requires a standardized format.Furthermore, the billing of tasks shall be processed simultaneously for contractors.To enable task or route planning for the MR or contractor a RRN is required which allows communication to the farmers also without internet.A digitally managed farm becomes resilient if it is characterized by utter independence of external internet connection and power supply.Like this, the FDFS is able “to prevent disasters and crises as well as to anticipate, absorb, accommodate or recover from them in a timely, efficient and sustainable manner”.Nonetheless, all online features and functions are used comprehensively in normal conditions but are replaceable by farm particular systems in case of intermitted power and internet connection.Consequently, a hybrid system was developed, combining cloud-based systems and farm-specific solutions.Likewise, it is for power supply, backed up by an emergency power generator, which is already mandatory for livestock farming.By its installation on the farm, it ensures the decentrality of the data repository.Storing data redundantly on different servers is the main aspect of configuring an FDFS in a resilient manner.Moreover, decentrality results in a higher level of data safety by securing data against external access and loss.All necessary data for the applied precision farming solutions are available in any circumstance.To ensure the connection of sensors, machinery, farm server, and farm management, during an internet outage, an LWN is installed.Less mechanized farms obtain digital farming technology through contractors or machinery rings.When a task is ordered by such latter farmer the contractor’s machinery connects to the LWN of the farm when it is in reach.Data transfer of e.g.prescription maps or documentation of tasks is then enabled.Communication between farm and contractor/machinery ring for task disposition can proceed before task execution with a minimum amount of data within an RRN of long-range like LoRaWAN.The single components of the FDFS in Fig.2 are explained in detail in the following sections.First a farm managed by an FDFS needs a power generator for a redundant power supply.

With technical hardware solutions,ebb and flow table it has to be guaranteed that in case of a power failure no voltage drop occurs.This can be achieved by bridging voltage drops with a UPS implementable for edge computing applications.Its capacities need to be selected according to the data and processing rates of digital sensors and devices running on the farm and the needed degree of resilience of the farm.Farmers have to decide which digital functionalities are fundamental for a similarly effective and sustainable maintained production without the internet thus balancing investment cost and necessary level of resilience.Fig.3 summarizes the general functions which could be covered by the farm server.The first main function of the farm server is to store relevant data for farm management.different data partitions are to mention: Basic data like field boundaries for guidance and calculations, AB-lines for controlled traffic, management zones for variable rate application, flight plans for drones, machinery settings, etc.Open Geodata, provided by public authorities, can be stored in an automated updated version or even several older versions if necessary for specific applications of farmers.Needed versions of satellite images are stored automatically corresponding to actual calculations of e.g.management zones.In level five this function can be conducted via AI, selecting and downloading the currently available satellite images according to the needs of the planned crop rotation.Depending on the cache function of each machine or sensor the server also is supposed to be used as a cache in case machinery or sensor has lost internet connection to send data to the cloud.Data sets of tasks that got interrupted by internet outages are completed in the cloud with cache data from the farm server when an internet connection is reset or over the landline.Some specific data, individual for every farm, might be needed in real-time where no delay by internet connection is acceptable.By receiving and storing these data, redundant to the proprietary cloud service, on the farm server ensures constant access to it.The format of these in real-time needed backup data on the farm server must be read- and processible for offline desktop software.Here ISOXML, JSONLD, and for some applications, Shapeles are the suggested formats.Shapefile and ISOXML are the most common in the actual applications of OEMs.

Data for later use could also be stored in manufacturer proprietary formats and be processed after reconnection to the internet in the proprietary cloud.When purchasing technology, which disadvantageously only offers proprietary formats it is favourable to see if there exists a plugin for converters like ADAPT.Generally, here a clear farm specific definition of necessary data has to be made by farmers because the duration of internet blackouts is never predictable.Among others because of a lack of interacting functionalities between different clouds.Nevertheless, some applications of predictions, machine learning, or simple AI algorithms are possible.In this case, farmers are reliant on the offline performances of their OEMs which evince a great deficit in this sector.Accordingly, secondary processing software needs to be chosen wisely.Focusing on long-term internet interruptions each farm needs to decide about which processed data in which time gap is indispensable.These diagnoses will reveal which proprietary raw data are expected to be made available by manufacturers in open and standardized formats for farmers to be able to use the data in secondary software while the usual FMIS is not available and a desktop version does not exist.Within the suggested FDFS, a desktop version of the FMIS is intended.This is a decisive contribution for maintaining effective, efficient, and sustainable crop production during any internet outage.The FMIS desktop version maintains the necessary functionalities of the specific farm needs.The ideal case of a resilient FMIS would be redundant to the online version which is closely linked to the processing efforts in the former section.Furthermore, interfaces to the LWN connect FMIS and machinery and ensure data transmission and documentation.The FMIS of the presented FDFS provides export functions of common, standardized, and open-source formats which ensures interoperability to secondary software like a GIS for example.When investing in a FMIS farmers need to consider which services their FMIS needs to fulfil in a situation when no internet connection is available.Data communication in between farm server and sensors/ machinery during internet outages is maintained by an LWN.Depending on farm size , topography, data traffic , and required latency of executed applications a corresponding network gets installed.

Farmers who depend on contractors or MRs additionally need to be able to receive and send a radio signal to communicate tasks while internet communication is not available.Otherwise, machinery rings or contractors cannot manage their orders to maintain maximum service capacity.This network does not necessarily need high bandwidth because for management purposes the contractor or machinery ring only needs basic information about the task.The range of this signal is defined by the catchment area of the contractor and MR.To establish and ease the installation of such systems only view standards with low installation costs should be taken into consideration.MRs and contractors, who work for the farmers, need to be able to connect with their machinery and sensors to the LWNs of their customers.When the executing vehicle is in reach of the LWN, the task data can be completely uploaded for task execution.When the job is completed, as-applied and further documentation data are sent to the FMIS through the farm server over the LWN.To complete the independence of the FDFS from external signals, the LWN also covers an alternative for positioning signals.That means all items on a farm, which use position data can navigate or track their position by calculating with signals of the LWN.In case the area covered by the LWN is too small for the farm extension, georeferenced marker points can be distributed on the farm area or mobile antenna stations can be set up.The main use case in the project MRdigital in Germany was in the field of slurry application by a subsidiary company of two machinery rings,flood table which acts as a contractor.A self-propelled slurry applicator is used.Via NIRS technology nutrient contents of the substrate can be measured which enables the system to conduct variable rate application using prescription maps.Such an applicator in addition to digital nutrient measurement is seldom purchased by single farmers and a fortiori, not by small and middle scaled farms.The business model to run such a machine within the organization and the management of machinery rings makes precision farming technology accessible and affordable also for small and middle scaled farms.According to the latter sections, usually, tasks and prescription maps are sent via the internet from the FMIS to the machinery ring or directly to the machine and vice versa.Farmers using an FDFS at their needed level can create and send tasks and prescription maps also during internet connectivity problems.The RRN enables the transmission of simple task data in advance.The prescription map and the as applied documentation data get transferred when the slurry applicator is in reach of the LWN of the farm.The machinery can read data from any kind of FMIS and write it back in the same format.The approach of categorizing farmers’ needs of resilience into five levels tried to meet the majority of conditions farms are exposed to.Nevertheless, many farms might prioritize another sequence of upscaling their level of resilience.For example, a farm with many sensors in the field acquiring low-volume data might prioritize the installation of an LWN before investing in a farm server.The five-level classification is supposed to give orientation for digitizing farms to prepare for crises.Technical setups are very individual and require therefore adapted solutions securing the most important digitized applications from failure.To set up an individual FDFS and choosing the right technical components might over strain the IT skills of most of the farmers, simply because it’s not their profession.Lachia et al.for example, found that the infield use of yield maps is too complex for over 50% of French farmers.

Assembling the components of an FDFS might be even more challenging.But having once set up an FDFS, the maintenance of its components, in addition, can also be expected as very demanding for farmers alone.Consulting and support from independent institutions are needed.A farm server as a central component of the FDFS covers many functionalities from storage to processing and AI to the management of access rights for third parties.This is also supposed to guarantee data ownership and control by farmers on whom has access and uses their data for which purposes.The more extensive these server functionalities get, the harder it can be for farmers to overview and control them.A lot of time might be needed for farmers to incorporate extensive server functionalities.But this should balance itself, the more functionalities the server covers, the more farmers will profit and the more time and money they might be willing to invest and vice versa.Considering that sensors and machinery have cache storage capacities to store raw data when cloud connection is lost, a large on-farm storage server might not be needed, especially if the farm is located in an area with a rather reliable internet supply.But here too, it depends on the applications farmers deploy.Areal imaging for example needs much storage capacities and sometimes low latency which makes it necessary to store and process the images on the farm server to be in time with the following application.The proposed FDFS can be a chance for small and middle scaled farmers in employing digital farming technologies.Only the investment of administrative components, like an FMIS, is sufficient and can, under certain circumstances, be built up modularly according to farmers’ needs and investment possibilities.Machinery and technology are rented or ordered from MRs and contractors.Here we meet the problem of lacking interoperability.When choosing digital components, farmers need to look out for solutions that use international standards on semantics and ontologies, in addition, to open APIs and data formats to ensure interoperability with future or external solutions.Developing such customer- or branch-specific solutions remains the responsibility of established agricultural software developers and solution providers.Solutions including proprietary data formats should be avoided.Also, the MRs and contractors need to take this into account when investing in new technologies.What is not defined in this paper is the detailed organization of data flow at the moment of an interruption of cloud connection.

Applying AI to the agricultural sector is not a homogenous challenge since the sector varies substantially

All interviews were held through digital meeting platforms and all but two were recorded with the permission of each respondent.The codes mentioned in Table 1 are used throughout this article to refer to the respective interview respondents.Remote sensing technology enables detection and monitoring of physical characteristics of the earth’s surface.Remote sensing data is collected from a distance, commonly from satellites and drones.The three most common properties of remote sensing data are spatial, spectral, and temporal resolutions.Spatial resolution is the pixel size of an image, a property that affects the ability to detect objects through imagery.differently, spectral resolution refers to the spectral sampling intervals size and number which affect the ability of the sensors to detect objects in electromagnetic regions.The temporal resolution regards the frequency of acquired data.The availability and economics of using remote sensing data collection is addressed by Khanal et al., which present remote sensing technology alternatives both open-accessed and for some cost.However, the resolution of the data varies, where the trend is that medium-resolution data is free whereas the prices for high resolution and very high resolution data increase in proportion to their increasing quality.Regarding data resolution, Meier et al. opine that site-specific smart farming depends on high resolution, as detection of anomalies are impossible or insipid with too large pixel sizes.Of course, depending on what kind of analysis the data aims to contribute to, the need for resolution varies.For example, predicting the crop yield within a field can accomplish a high accuracy despite a coarse resolution while detection of plant diseases through hyperspectral imaging requires a detailed resolution.Internet-of-Things is a collective concept for objects with incorporated electronics and connections that enable remote control and information sharing.In agriculture, IoT is mainly used for collecting data through different types of sensors.

By further data analysis,flower pot valuable information can be derived as decision support, e.g.for farmers.Kamienski et al. define four main challenges for IoT development in smart farming.First, the IoT system must have a high level of adaptability.Since the needs of farmers often significantly vary, the IoT system must be customizable to local circumstances but still not increase the required work for the farmer.Secondly, the IoT deployment must be efficient.As Kamienski et al. write, “there is no ‘one size fits all’ in IoT systems”.Thus, each system needs to be configured, the Internet connection and farm infrastructure must be reliable, and the farmer must deploy enough human and economic resources into this process.Furthermore, the scalability is affected by the previous factors but also depends on whether the system, and the models learned, are supposed to work for just one farm or entire agricultural consortiums.Lastly, the complexity of the IoT system can be interpreted as a trade-off between making the middleware broker complex and the software application simple, or the reverse.Another aspect to IoT in smart farming is security.Since the data often is valuable for the farmer and is regarded as a business secret, Kleinschmidt et al.describe the need for end-to-end encrypted communication from the sensor to the application.In practice, this means that the IoT sensor network must have a synced security strategy to the cloud database and the potential fog computing network.By ensuring security, the probability that the farmer trusts the IoT system increases.Still, trust in IoT systems does not just depend on security but also on the precision of the sensors.Without ensuring that there are no systematic measurement errors in the sensors, few farmers would trust the learned model or the real-time data.The potential of smart farming in animal husbandry, such as dairy-, beef- and fur production, is largely constituted by increasing productivity and profitability by streamlining and automating tasks and information.Much research consists of ways to monitor and look after the animals automatically or semi-automated.These articles suggest that devices, both wearable and non-wearable, may be incorporated in the animal stable and that these devices can gather data that can give indicators on the health of the animals.The data that may be gathered through these devices vary, but the wearable devices can measure heat, hormone levels, rut etc.The non-wearable devices more typically are 3D cameras for body condition scoring and infrared imaging, sensors that monitor environment and weather as well as automatic weighing scales and gates.In arable farming, an important feature of smart farming is to be able to calculate the vegetation index of fields or areas to be able to monitor when it is time for harvest and other activities.This may be done by both remote sensing and IoT solutions.

Viljanen et al. train a machine learning model aimed to optimize the “balance between the highest possible yield quantity and an adequately high digestibility for feeding”.By using an inexpensive drone system that can get multi-spectral data from an RGB camera and an infrared camera, traditional physical tools for predicting ley yield can be replaced by smart machine-learned models with higher accuracy.Furthermore, the research of predicting yield and quality of silage can also be accomplished through satellite data, as presented by Griffiths et al..The study shows that it is possible to detect mowing events of grasslands, and therefore characterize the land use intensity by looking at satellite imagery.In terms of yield prediction, Feng et al. stress the importance of incorporating biophysical characteristics of the crop in machine learning algorithms.This means that to learn a model with high precision, it is important to simulate the growing process of the crop to ensure that the model learns the crop characteristics in different stages of the growing process.Furthermore, Matos-Moreira et al.uses manual soil samples to further improve their model.By including manual sampling and analysis with a variety of existing data sources one may learn a model to predict the quality of a crop or the concentration of some matter at a given place and time.Another application of precision farming is to detect sickness or pests among crops.Torai et al. study how diseases can be detected in crops by classifying, or labeling, areas in pictures as “healthy”, “infected”, “diseased” or “aged”.Thereafter, methods such as hyperspectral imaging, Bayesian networks, and an analysis through probabilistic latent semantics are applied to detect the diseases .This study is a good example of a remote sensing technology applied to agriculture which needs a very high resolution of data, preferably on a scale of centimeters.One dilemma when applying artificial intelligence to arable challenges is how to use the different types of available data.Kerkow et al. use fuzzy mathematical modeling to solve this problem.This approach allows for mixing machine learned climate models with wind data and expert knowledge of the landscapes to build precise models .The literature review also brings up some interesting aspects regarding the implementation of AI in agriculture.Medvedev and Molodyakov highlight both theoretical and practical knowledge of smart farming as requirements for successful implementation.Unfortunately, seldom farmers have either the economic resources or the time to attend longer educations within the subject.To meet the lack of technical education within smart farming, Medvedev and Molodyakov propose smaller model-based courses that should cover technical, economic and management aspects to smart farming.

A crucial part of the education is that the courses are on-demand, so that busy farmers can access it whenever it suits them.Both business cases and clear driving forces are named as critical components to spreading the use of smart farming technologies in society.Barriers that hinder the drive towards smart farming are categorized as economic, institutional behavioral, and organizational as well as market.Furthermore, they identify social and moral drivers to play a key role in terms of creating a societal demand for smart farming.Without the support from society at large, innovations will not be adopted by key actors, they conclude.Other research aims to map the barriers to implementing and diffusing smart farming technologies.Kernecker et al., describe that farmers approach smart farming technologies differently given how much smart farming technologies the farmers have already adopted.The so-called adopters perceive the barriers to adopt smart farming technology as high investment costs, a difficulty in interpreting data, a lack of interoperability or precision in devices, that farmers cannot see the added value of the new technology or the relative advantage of the system, as well as a lack of neutral advice from advisors and other actors.The non-adopters also perceive high investment costs and unclear added value as barriers.Additionally, they regard too demanding complexity of use, that the technology is not appropriate for their context or farm size, as well as a lack of access to proof of concept from a neutral point of view, as obstacles.Finally, the literature review highlights the importance of data presentation and visualization, both in arable farming and livestock farming.Beside identifying possible applications of the technology in agriculture, several research groups argue that methods within machine learning and AI require decision support tools that visualize the data in comprehensive ways.One pattern, stated by a farmer respondent,berry pots is that farmers of different agricultural sectors almost always believe that the implementation of smart farming technologies has come further in other sectors than in their own.The agricultural sector that most farmers highlight as currently the most technologically advanced is the milk production.Milk robots were introduced to the commercial market decades ago, and with the milk robots the fodder of an individual cow can be customized, increasing its health status and production capacity.Due to the milk robots, the dairy industry is regarded notably data driven.One important aspect to consider when evaluating the success of the milk robots is the short feedback loop.Since cows are both fed and milked daily, the machines can adjust quickly depending on the latest input.Furthermore, Swedish dairy farmers have a long history of collecting data by being part of the so-called Kokontrollen, a cow data collection application owned by Växa Sverige.Even if Kokontrollen today is web-based, Swedish dairy farmers have been reporting to it for more than 100 years.Previously, all data was collected manually but today almost all data connected to milk production is automatically gathered by the milking robots.Contrasting to milk production, arable farming is diverse with different crops requiring distinct machines and technologies.Hence, a single successful machine is difficult to implement for the entire arable farming sector, making its technological development more complex.

However, it is possible to create effective technology for specific crops.As a rule of thumb, crops with high manual work, such as vegetables, use lots of technology since they operate on small, more controlled areas.In such environments, such as green houses, the feedback loop is faster and there are less uncontrollable factors, such as weather or wild hogs, which makes the application of new technology and AI easier.Of the three agricultural sectors compared in this study, beef production is considered by the respondents as the least technologically developed.Nevertheless, one respondent at a major company believes that meat production will have a central role in the development of the Swedish primary food production.The list of possible innovations includes making the value chain digital by automatically transferring information to the slaughterhouses regarding characteristics of the animals they will receive.By mandatory RFID tags for all cattle, the respondent argues there is an enormous potential, since the development of the animals could be followed in real time throughout the value chain.With such a system, the slaughterhouse could plan far in advance for incoming meat quality and volume.Simultaneously, a grocery store could send data to the farmers regarding the current popularity of different kinds of meat, enabling the farmers to adjust their production to the current consumer behavior.Furthermore, if one could autonomously and automatically weigh the cattle, their growth curves can be predicted which would enable optimization of the timing for sending animals to slaughter.By this optimization, one could avoid having full-grown animals that both drain economical resources and emit environmentally damaging methane gas.Regarding data and the activity of collecting data, the responses from the interviews reflects different realities within the agricultural sector.On the one hand, some respondents say that farmers generally are positive towards gathering data on their farm.On the other hand, some responding farmers state that they collect almost no data on their farms, although they say that they understand that data could add value to them.In-between is a spectrum of attitudes towards data gathering and implementation of technology in the farms.

Consequently both the rate of successful introductions and the volume of susceptible crops rise

Most of the land trusts in our study were created through the grassroots efforts of a few community leaders or environmental activists, organizing effectively to pursue shared conservation goals. Other land trusts and open space districts originated more directly through local government action, including voter approval.Few of the established programs in California enjoy a steady revenue stream for building large agricultural easement portfolios. Programs with substantial acquisitions have relied largely on fluctuating and opportunistic revenue sources, primarily state government funds and foundation grants. They generally lack the certainty that an ongoing, dedicated local tax source could provide. As a result, most programs acquire easements in fits and starts, limiting their ability to plan and work quickly with interested landowners.Landowners cannot be compelled to enter into an easement transaction by government regulation or eminent domain; selling or donating an easement is entirely voluntary. This means that programs must rely on each landowner’s understanding of the technique and personal estimate of benefits and costs. For many landowners, easements are a foreign or confusing concept. They offer the unwelcome prospect of having less control over their land and create uncertainties about the long-term consequences for immediate heirs and later generations of owners. Landowners located near rapidly urbanizing areas are especially reluctant to consider the easement option, as they believe that they will be able to prosper by selling their parcels for residential or commercial development sometime in the future. Finally, even with a supply of willing landowners, there is the challenge of fitting the available properties into a program’s criteria for location,ebb and flow agricultural quality and easement price. Nonetheless, the successful programs demonstrate that a few early transactions with landowners respected in the local farm community can break the ice for subsequent deals .

Primarily because they are non-regulatory and voluntary, easements on farmland increasingly appeal to landowners and communities attempting to protect open space and agriculture. With about 120,000 farm acres covered statewide, agricultural easements have become an important farmland protection tool in California in less than two decades. A small number of local land trusts and open space districts, assisted by funding opportunities and entrepreneurship, have established successful programs. Yet the active programs operate in only a minority of California’s major agricultural counties. Many of these areas lack easement programs because of the absence of citizen interest and mobilization combined with local government inaction. Most established programs also are limited in their easement acquisitions, largely because of unsteady revenues, limited entrepreneurship and reluctant landowners. Undoubtedly, the few successful programs will continue to grow and expand their easement holdings. But expanding agricultural easements to major agricultural regions is the key to making optimal use of the technique in California.Introductions of non-indigenous species of plants, animals, and microbes cause significant ecological and economic damage worldwide. A 1993 report from the Office of Technology Assessment estimates the monetary costs associated with biological invasions in the US alone is between $4.7 and $6.5 billion annually ; subsequent research revises that estimate for the US upward to over a hundred billion dollars a year . Moreover, since these estimates derive mostly from costs calculated for agriculture1 , there is consensus that these numbers are lower bounds. There are numerous pathways by which non-indigenous species enter a country: contaminated agricultural products, timber, potted plants, ballast water and packing materials are primary conduits for unintentional introductions2. We focus on introductions facilitated by commodities trade and explore how changes in agricultural protection affect patterns of trade and subsequent damage to local agricultural and ecological systems from exotic species introductions. In our stochastic model, exotic species introductions, success, and damage are functions of the volume of trade and agricultural production.

The model is coupled with results from international trade theory that link volumes of production and trade to agricultural policies such as output subsidies. This simple structure generates several compelling insights. First, we show that increases in agricultural subsidies may improve overall ecosystem health despite common opposition to agricultural protectionism by environmental advocates. This arises because protectionist trade policies in agriculture importing countries reduces imports, often from species-rich tropical regions, such that the rate of exotic species introductions will likely fall with reduced subsidies. Second, we establish that crop damages are a poor proxy for overall damages associated with biological invasions. Crop damage arising from biological invasions may rise as a result of increased protectionism, either because there are more crops available to be damaged or because there is more agricultural land available on which non-native species can gain a foothold. But because increased protectionism will reduce the volume of imports in agriculture importing countries, ecological—and hence total—invasion-related damage may nonetheless fall. Third, we argue that the ecological impacts of increasing agricultural subsidies may be markedly different for agriculture exporting versus agriculture importing countries. For countries that initially export agricultural products, increases in production subsidies will lead to an increase in both the volume of agricultural output and in the volume of trade, with unambiguously negative consequences for overall ecological health. In sum, the ecological consequences of raising agricultural subsidies are reversed in agriculture importing countries. In section 2 we discuss the relevant economic and ecological literatures. We then describe our model in section 3, derive results in section 4, and briefly conclude in section 5. Ecologists have studied the consequences of invasive species extensively; see Drake et al. , di Castri , Parker et al. , and Shogren for overviews. This research has established several patterns governing successful exotic species introductions.

For example, successfully introduced exotic species tend to be native to nonisolated habitats within continents and their success is enhanced with the similarity in physical environments between the original and exotic locations . Furthermore, species that inhabit disturbed environments tend to be successful at invading human-modified environments . These and other empirical observations suggest that predictions of the frequency and severity of exotic species introductions can be made on the basis of factors such as similarity in physical environments between trading partners, trade volume, and the extent to which the home country modifies its natural environment. Despite the extensive study of the ecological impacts of non-indigenous species, rigorous economic treatment of the problem is lacking. The little attention paid by economists to the problem of invasive species has focused largely on case studies and analysis of control and risk reduction methods . With the exception of Dalmazzone , none explicitly incorporate the role of commodity trade in their analysis. Using a linear regression model, Dalmazzone finds a strong, positive and statistically significant relationship between the ratio of exotic to native species in a region and both its GDP/capita and its population density. Indicators of disturbance such as percentage of land devoted to agriculture and pasture are also positively correlated . Dalmazzone finds weaker evidence of a link between susceptibility to biological invasions and engagement in trade: although she finds a negative and statistically significant relationship between import duties and presence of non-native species, the influence of other measure of openness such as trade as a percentage of GDP, volume of merchandise imports and tourism are all statistically insignificant. We believe these results underplay the importance of trade volumes for rates of exotic species introduction. Given the biological rules of thumb governing invasions, a superior econometric specification would decompose imports by type and country of origin, as recognized by Dalmazzone. Moreover, we believe empirical testing would benefit from a more thorough understanding of the mechanisms in which trade policies and flows affect introduction and damage rates. The present paper serves as a first pass at establishing these relationships theoretically. We explore the effects of agricultural protectionism,greenhouse benches via an increase in subsidies to domestic agricultural producers, on expected damage arising from biological invasions. It is shown that the magnitude of change in expected damage depend critically on two things: the responsiveness of damages to changes in agricultural output and the response of imports to agricultural subsidies. We show that offering subsidies in an agriculture importing country will reduce both its rate of introductions and the ecological damage caused by the introductions. We further demonstrate that changes in crop damage are a misleading proxy for the effects of protectionist policy on ecological and total damages arising from biological invasions. This latter claim is particularly important if we believe pecuniary losses to agricultural production are more easily observed than ecological damage from exotic pests and hence form the basis for policy decisions.

Proposition 1 makes the simple point that increased support for Home’s agriculture industry may reduce the rate at which exotic species are introduced because of the effects agricultural subsidies have on the volume of trade. For countries that import agricultural goods, production subsidies lead increased output of locally produced agricultural goods to displace imports, thereby reducing the overall volume of trade as the country moves toward self-sufficiency. As reduced volume of trade reduces the size of the platform for non-native species introductions into a country, the expected rate of introductions N, and consequently the number of non-native species that take hold J, is thereby reduced. Alternately, if a country instead initially exports agricultural goods, an increase in S raises the volume of trade since it induces greater agricultural output, exports of which finance greater imports of manufactured goods. Although there is a tendency to equate species introductions with imports of agricultural goods, trade in non-agricultural goods also frequently serves as a conduit for biological introductions, either through contaminated ballast water from ships, or infestations of packing materials and manufactured goods themselves. It is possible that λ may depend differently on imports of different types—we abstract from this issue in the interest of simplicity—nonetheless the larger volume of trade arising from subsidies in agriculture exporting countries increases the platform for introductions and so raises the expected values of N and J. Some simple interpretations of these classifications are useful at this point. Damages arising from loss of crops —either through infiltration of crop and pasture land by weeds or predation on crops and livestock by pests— increase as the level of agricultural activity increases. Commonly referred to as crop damage, these types fall under the definition of Augmented damage. Other types of invasion related damage are unlikely to depend directly on the level of agricultural activity. Introductions affecting marine and aquatic systems are good examples of this: invading mollusks foul water intake systems at power generation facilities; introduced fish out compete native species, creating losses to recreational activities such as sport fishing. In addition, there are numerous examples of exotic species displacing native species, with consequences for non-monetized assets such as ecosystem health and biodiversity. These examples meet the definition of Neutral damage. In subsequent discussion we will also refer to these types as ecological damage. If instead introduction rates are sufficiently sensitive to the volume of trade, then an increase in agricultural subsidies may instead reduce expected invasion related damage. This latter possibility raises an interesting problem. Since Neutral and Augmented type damages may change in different directions following an alteration in agricultural policy, then estimates of invasion related damage that are based on one type of damage serve as poor—even misleading—indicators of total damage. As noted in the introduction, most real-world estimates of invasion related damage derive predominately from estimates of damage to crops and livestock. However, as proposition 2 indicates, crop damage may be increasing while Neutral and Diminished damages, and hence total damages, are decreasing. This insight confirms our earlier conjecture: economic measures of crop damage are a misleading indicator of total damages arising from biological invasions. For the policy change considered here, an increase in the agricultural output subsidy S changes in crop damage overestimate changes in total damage, and may indicate an increase in total damage even when total damage is in fact declining. As outlined in proposition 3, the effects on an increase in S on damages in an agricultural exporter differ from the effects felt by an importer. Again higher S spurs local agricultural production, however for an agricultural exporter this finances greater imports.

Empirical results include the impact of UCCE’s expenditure stock on individual counties

Therefore, our results agree with the existing literature, which suggests that old expenditures impact current productivity positively, and their exclusion tells us only a partial story. The coefficients we have obtained in this study indicate that there is room for improvement in extension research and outreach, and that introduction of new research-based knowledge and technology improves productivity. Results also suggest that primary-occupation farmers may be less efficient than those who are able to maintain more than one profession. Efforts could be focused towards improving any existing gaps in efficiency among farmers in different counties.The results of our analysis can guide policymakers during a period of political pressure to reduce public spending for agricultural extension in the state. The county fixed effects results allow a more targeted policy intervention on higher and lower performing regions .By controlling for individual county and fixed-year effects that may be driving productivity in that county, we find that some of the major agricultural counties in California record high positive impacts of UCCE expenditures stock. Out of the 50 county offices in our study, we observe that UCCE expenditures stock has a significant impact on 21 counties for all values of knowledge depreciation. We observe a statistically significant negative impact on a few counties, such as Amador, Calaveras, Humboldt-Del Norte, Modoc, and Siskiyou. For two counties, the impact is not statistically different from 0. In terms of policy, these coefficients can be used as reference points for allocating budgets to different counties. Extension efforts could be targeted to the counties with inconclusive or negative impacts. Monetary impact of cutbacks on county productivity could also be calculated, using the estimates of extension expenditures in this paper. The analysis driven by county performance helps design policies with heterogenous focus, which has been more relevant when public funds have to be allocated among heterogeneous performing recipients of these funds. And finally, as shown in Section 5.3 extension introduces substitutability of traditional inputs with extension knowledge so that higher expenditure on extension in some of the lower-performing counties can substitute for other traditional inputs, dutch buckets for sale which may be scarce in supply.

In particular, our analysis highlighted and measured substitution of extension knowledge for labor and chemicals.Both biodiversity and the human activities that threaten it are unevenly distributed around the globe. Thus, evaluating whether they are spatially congruent and choosing the best areas for conservation actions given the distribution of these conflicts are central problems in conservation bio-geography . The magnitude of the current biodiversity crisis, coupled with the limited resources available for protecting biodiversity, implies that prioritization is unavoidable. Spatial prioritization seeks to identify the areas that are likely to yield the best benefits for biodiversity given a particular conservation investment. It may be applied at a variety of scales, including global , regional , national and sub-national levels. Spatial conservation prioritization analyses can be based solely on the distribution of the biological features to be protected . Alternatively, prioritization analyses can include socioeconomic variables that represent threats to biodiversity or opportunities for conservation, such as human population density, land cost and land use . Agriculture is the human activity that represents the main threat to the environment . It constitutes the largest land use on the planet, using 38% of Earth’s ice-free land surface and 70% of global human freshwater uptake. Food production accounts for 19% of Earth’s net primary productivity and 30-35% of global greenhouse gases, with direct impacts on biodiversity . The burden on the environment may be higher in the future as the human population is expected to increase to more than 10 billion by 2050 . Moreover, a billion people are currently chronically malnourished as a result of lack of access to food . Given the value of biodiversity for human well-being , understanding the potential impacts of future agricultural expansion on biodiversity is a key issue for humanity. The general aim of my PhD thesis was to evaluate the potential impact of agricultural expansion on biodiversity conservation during the 21st century. Specifically, I evaluated four interrelated issues: conservation conflict between agricultural expansion and the global biodiversity conservation priorities and the Brazilian system of protected areas ; the effect of incorporating agricultural expansion data into spatial prioritization models for the conservation of world carnivores ; and the benefits of a globalized conservation strategy for food production and for biodiversity conservation . The impact of future socioeconomic development pathways, including land-use trends, on biodiversity can be accessed by means of quantitative scenarios . For all analyses presented here, I obtained future scenarios of agricultural expansion from land cover maps produced by the Integrated Model to Assess the Global Environment .

IMAGE forecasts, at a resolution of 0.5° × 0.5°, the number of years that each area will be cultivated during the 21st century for six socioeconomic scenarios . For chapter IV, I also included an estimation of potential agricultural productivity in each grid cell, based on climate, relief, soil constraints and irrigation impact . For the first chapter, I overlaid the spatial polygons of the Global Biodiversity Conservation Priorities onto a grid with a spatial resolution of 0.5° × 0.5°. I tested whether areas defined by their higher vulnerability were more affected by agriculture in the year 2000. The opposite was expected for areas with low vulnerability . I also tested whether these priority areas would be more affected by agricultural expansion during the 21st century than expected by chance . To address the aims of chapter II, I overlaid the IMAGE’s land-use model with Brazilian protected areas to calculate the conflict between these two land uses. I obtained Brazilian protected areas’ polygons from the World Database of Protected Area . I also included 10 km buffers around each protected-area polygon to represent the legal buffer zone usually used in Brazil, which is an area where human activity is restricted. I then tested whether these areas were more affected in the present and in the future than expected by chance. Additionally, I tested whether there was difference between the integral protection protected areas and sustainable use protected areas . In both chapters I and II, I evaluated the probability of such conflicts to be found by chance using spatial randomization tests developed in R , considering 1000 iterations . To meet the objectives of chapters III and IV, I performed global spatial conservation prioritization using Zonation . Zonation’s algorithm provides a nested hierarchical ranking of the sites, maximizing the representation of species’ distributions. To define the ranking of importance of sites for conservation, Zonation analyses can also incorporate costs such as potential agricultural production. For all prioritization analyses, I defined the target proportion of areas to be protected as 17%, following the Convention on Biological Diversity , which proposed this percentage as the goal to be met by 2020. I obtained information about mammal species’ distributions from the International Union for Conservation of Nature’s Red List of Endangered Species. I overlaid the spatial polygons onto a grid with a spatial resolution of 0.5° × 0.5°. For chapter III, I focused on 245 terrestrial carnivore species. In chapter IV, I used 5216 terrestrial mammals. These taxonomic groups have been the focus of many conservation programs and they are often considered to represent a potential surrogate for other taxonomic groups . To test whether there is a spatial conflict between the global carnivore conservation solutions obtained in chapter III and the agricultural expansion, I performed spatial correlation analyses using the Spatial Analysis in Macroecology software .

The objectives of chapter IV were achieved by defining global conservation priorities considering three levels of political integration: individual countries, regions , and globalized . I also evaluated the effect of considering, or not, agricultural costs for spatial conservation prioritization. The different conservation solutions were evaluated in terms of the relative amount of food production lost by setting aside sites for conservation and the representation of the geographic distribution of species within those sites. I also evaluated whether the most underdeveloped countries would be subject to higher losses in food production under the global strategy. For this, I correlated the percentage of food production and area lost to sparing land for biodiversity conservation with three development indicators: the Human Development Index , the per-capita gross domestic product , and the percentage of GDP added by agriculture . I found that reactive global biodiversity priorities had about 49% of their area impacted by agriculture in the year 2000 . Conversely, proactive schemes had a low intersection with the agricultural distribution . By the end of the 21st century, there will be an overall increase in world agricultural area from 26.5% of the analyzed area in 2000 to 34.6% in 2100, according to IMAGE, and the difference between the proactive and reactive schemes is predicted to hold true. However, High Biodiversity Wilderness Areas, a proactive scheme,hydroponic net pots is predicted to suffer agricultural impact similar to the reactive schemes, with 73.5% of its area affected, if the worst-case scenarios are realized . In Brazil, a megadiverse country in which agribusiness is the pillar of economy, agricultural expansion is a major conservation concern . According to IMAGE, agricultural land use represented 22% of Brazilian land coverage in 2000 and is predicted to increase up to 40% by 2100, according to a business-as-usual scenario. Moreover, the percentage of protected areas affected is predicted to increase from 11% to 30%, with no difference between IPPAs and SUPAs . I found spatial conflicts between the best areas for terrestrial carnivore conservation and agricultural expansion in the 21st century . These conflicts were alleviated when I incorporated agricultural expansion information into the spatial prioritization process . Nevertheless, accounting for agricultural expansion resulted in a lower representation of species’ geographical ranges: the average proportion of represented ranges was reduced from 58% to 32%. This reduction affected mainly those species with small geographic distributions. In addition, the best solution for global carnivore conservation changed from a spatial distribution closer to that of the reactive global conservation priority schemes to one more like proactive ones. Looking at the impact of globalization for conservation and food production, I found that combining the use of agricultural expansion data and integrating countries in a globalized conservation blueprint to meet the 17% target for terrestrial protected areas, resulted in a 78% reduction in the costs of food production . Furthermore, this globalized conservation approach represented an increase of 30% in the representation of the species in the protected areas network.

The regional-scale conservation solution resulted in similar losses in food production, compared to the globalized solution, and an increase of 17.5% in terms of representation of mammals’ geographical ranges .Conservation actions in the different areas of the world should be planned according to the expected agricultural expansion in the 21st century. Some areas can hold mega-reserves , while other areas should focus on the development of wildlife-friendly agricultural practices. Within Brazil, my findings suggest that the risk of agricultural expansion should be included in the management of protected areas and associated buffer zones. Globally, conservation actions for carnivores should consider agricultural expansion because this may significantly influence the distribution of areas where conservation actions could be more effective in the future . The regional scale may represent an intermediate step towards the global integration. Economic agreements may evolve to common conservation policies, since this has already been done in the European Union by means of the Natura 2000 network . By comparing differences in the distribution of protected areas among countries in the different scenarios, I found that the poorest countries will not be negatively affected by participating in this globalized conservation blueprint. However, the particular cases in which poor countries would be impaired in their development process should be a focus of compensatory policies in order to guarantee the participation of these countries within the global approach. Moreover, such compensatory policies may help to overcome socioeconomic problems such as poverty and inequality, which are known to be detrimental to the success of conservation actions . Feeding an increasing human population, with rising per-capita consumption, while managing the environmental impacts of agriculture, is one of the greatest challenges for global policy. In my thesis, I demonstrated that agricultural expansion will continue to represent an important threat to biodiversity throughout the 21st century. Reducing food waste, increasing agricultural resource efficiency, closing yield gaps, and fostering organic agriculture are tools available for solving this challenge .

Prime-age adult mortality affects their production since their family business is labor-intensive

In the regions affected by Human Immunod efficiency Virus / Acquired Immune Deficiency Syndrome , prime-age adult mortality negatively affects household welfare by decreasing household income and consumption. Previous studies on the effects of prime-age adult mortality on household agricultural production show that the mortality decreases household size and productive assets such as land and livestock. In this study, we further ask whether prime-age adult mortality due to HIV/AIDS decreases the endowment of knowledge for agricultural production in Kagera, Tanzania, reducing total factor productivity. Equivalently, we ask whether prime-age adult mortality due to HIV/AIDS destroys household agricultural production by magnitude beyond the decreases in observed productive assets such as household members, land, and livestock. We also quantify how much decreased TFP growth contributes to the decrease in long-term household agricultural income growth compared to the decreased accumulation of each productive asset. Kagera was estimated to be one of the regions in Tanzania most affected by the HIV/AIDS epidemic , Beegle. Kagera is also the region where AIDS cases were reported first in hospitals in Tanzania. In 1983, the first 3 AIDS cases were reported and the number of cases increased rapidly to 5,116 cases in 1994. On the other hand, the share of reported AIDS cases in Kagera to Tanzania decreased from 100% in 1983 to 10% in 1994. In 2003, the percentage of HIV positive in Kagera among age 15-49 is 3.7% while the figure in Tanzania is 7.0% and thus HIV/AIDS pandemic in Kagera has been alleviated compared to other regions in Tanzania. We use the Kagera Health and Development Survey which collects the detailed information on households in Kagera in 1991-94 and 2003. The survey samples households hit by prime-age adult mortality more than households without the mortality and the data allow us to study the long-term effects of prime-age adult mortality on agricultural production. In the data, 36.7% of prime-age adult mortality is considered to be due to HIV/AIDS by deceased individuals’ families.

We will focus on agricultural production among other income generating activities and we will study the effects of prime-age adult mortality on agricultural production in the region. Agriculture is the major income source in Kagera and also in Tanzania. In Kagera, 85% of household heads engage in agriculture in 2000/01 while 70% in Tanzania , Tanzania NBS. In Kagera,grow lights households engage in subsistence and traditional agriculture. Male adult members produce coffee and banana with or without cattle manure. Female adult members produce crops such as maize and yams mainly for own consumption.As shown below, households hit by prime-age adult mortality between 1990 and 2003 have less increase in household members by 1 person from 1991 and 2003 than households without the mortality.They also accumulate less other productive assets; land and livestock. As a consequence, their agricultural income growth is also smaller. However, we do not find such clear differences in per capita asset accumulation and income growth between households with prime-age adult mortality and those without it. In order to explore the effects of the mortality on agricultural production more, we will study the difference in TFP growth. We study the hypothesis that a household hit by the mortality cannot increase TFP as much as a household not hit by it. We also decompose agricultural income growth into the contribution of the accumulation of each productive asset and TFP growth and compare the differences in those factors between households with and without the mortality. The remainder of this paper is organized as follows. Section 2 reviews the previous studies on the effects of prime-age adult mortality on households’ welfare based on household level micro data and the differences between the previous studies and this study. Section 3 outlines our conceptual model, hypothesis, and framework of empirical methods. Section 4 explains the characteristics of the original data, especially with respect to prime-age adult mortality, how we construct our data for the analysis from the original KHDS data, and discuss the relevancy of our specification of the model to study the data. Our empirical methods are explained in more details in Section 5 and the empirical results are shown and discussed in Section 6. Section 7 concludes this paper.Whether and how much HIV/AIDS epidemic affects a household welfare is the important topic. We can categorize the literature of the effects of prime-age mortality due to HIV/AIDS on household welfare into consumption studies and production studies. Beegle, de Weerdt and Dercon studies the effects of prime-age mortality on long-term consumption growth based on KHDS.

Their regression equations have change in logarithm of per capita consumption from 1991 to 2003 as the dependent variable and dummy variables for deaths as explanatory variables. They use household fixed effects methods in order to control unobserved time-invariant characteristics and relax the endogeneity and self-selection problem of HIV/AIDS as other previous studies based on panel data do. They take into account which year each death occurred by using dummy variables for deaths in 1991-1995, 1996-1999, and 2000-2004. Their results show that the coefficients of dummy variables for deaths are negative but only dummy variables for deaths in 2000-2004 are statistically significantly different from zero. This characteristics of the results are robust in various specification of regression equations. Their results imply that there are negative effects of prime-age adult mortality on consumption growth but households may recover from the negative shock of the mortality after 5 years. They find that a prime-age adult death results in a 7% drop in consumption in the first 5 years after the death. Carter, May, Aguero and Ravindranath use KwaZulu-Natal Income Study , South Africa data and study the effects of prime-age mortality due to HIV/AIDS on long-term growth rate of per capita consumption and find the negative coefficients for dummy variables for deaths although they are not statistically significantly different from zero. They also find the large magnitude of the negative effects: a prime-age adult death lowers a household’s 5 year growth rate by 21%. Although the consumption studies above find the negative effects of prime-age adult mortality on household 5-year consumption growth, channels of the causality has not been made clear. Production studies analyze some potential channels of the causality. Beegle uses the first 4 waves of KHDS from 1991 to 1994 and studies the short-term effects of prime age adult mortality in a household on the household members’ labor supplies. She constructs dummy variables for male and female deaths in future and past 0-6 months and 7-12 months and uses them as explanatory variables in regression equations. The dependent variables are the probabilities of being in wage employment, non-farm self-employment, working on coffee production, banana production or maize, cassava, or beans production. She finds coefficients of some dummy variables for deaths are negative and statistically significantly different from zero in regression equation of being in wage employment, working on coffee production and maize, cassava, or beans production.

Yamano and Jayne use two-year panel of rural Kenyan households and study the effects of prime-age adult mortality on households’ size and composition, crop production, asset levels and off-farm income. They find the mortality decreases households’ size, area under high-valued crops, gross and net outputs, farm equipment, small animals, and off-farm income. They find that the death of a male household head is associated with a 68% reduction in the net value of the household crop production implying large negative effects of the mortality on households welfare and that channels of the causality are decreases in productive inputs above. Chapoto and Jayne use nationally representative 3-year panel data in Zambia and find the results similar to Yamano and Jayne . These production studies show that the negative effects of prime-age adult mortality on household income and channels of the causality. HIV/AIDS also increases an household’s expenditure for medical care for the sick and funeral for the deceased. Tibaijuka finds that this expenditure is almost equivalent to the cash income for the 10 households in her data from Kagera, Tanzania. We can think that decreased income and increased expenditure for health care and funeral due to HIV/AIDS and prime-age adult mortality contribute to the decreased consumption which is found in the consumption studies above. Households hit by HIV/AIDS have to face tighter budget constraints and invest less in productive assets than the other households. Smaller investment in productive assets brings smaller income in the future. We contribute to the literature with the following three points. First, we provide an answer to the question whether prime-age adult mortality decreases total factor productivity in the long run. Previous studies do not ask this question although it is an important question to study the channels from prime-age adult mortality to decreased income and welfare. This question is closely linked to the question how important an adult’s knowledge stock of agriculture is for his/her household income generation. Since subsistence agriculture in Kagera, Tanzania depends on weather and is erratic,led grow lights the knowledge may be important. On the other hand, its agriculture is traditional and does not depend on new technologies and new market opportunities so much, the knowledge may not be important. If the knowledge is important, prime-age adult mortality destroys not only household members but also the quality of household as an agricultural enterprise. Second, we decompose the agricultural income growth into TFP growth and the contribution of each productive asset. Previous production studies analyze the effects of prime-age adult mortality on each productive asset separately and cannot show how much change in each productive asset due to prime-age adult mortality contributes to change in agricultural income or output.

We quantify this channel from change in each productive asset to change in agricultural income by estimating an agricultural production function and decomposing the long-term change in agricultural income growth into TFP growth and change in contribution of each productive asset for households with and without prime-age adult mortality. Third, we study the effects of prime-age adult mortality on long-term agricultural production and link the previous studies on long-term consumption with the previous studies on short-term change in production mentioned above in this section.We can categorize channels through which the mortality changes the investment decision into two: First, the household changes future asset accumulation path as a response to changes in current asset levels due to the mortality and inheritance. For example, the household may sell land and livestock in order to achieve efficient and smaller productive asset level as a response to decreased household members and productivity due to the mortality. Second, the household’s budget constraint becomes tighter due to the mortality and the household has to change its allocation of income into consumption and investment over time. The household lost labor for income generation since the member who was sick and deceased did not and will not contribute to the household as labor and other members take care of the sick and thus the household income decreases. Furthermore, the household faces expenditure for medical care and funeral. Tibaijuka finds that this expenditure is almost equivalent to the cash income for the 10 households in her study. Although there is no consensus on what adult age range we should use to study the effects of adult mortality on household welfare1, we set the age range for prime-age adults is from 15 and 50. In this subsection, we discuss the relevancy of this age range. Our focus is the effects of prime-age adult mortality on agricultural production. We will focus on prime-age adult’s death rather than other household members’ deaths since prime-age adults contribute to their household as main labor force for agricultural production and they are the age group who are affected by HIV/AIDS directly.We set the lower bound of prime-age adult to be 15 since 15 year old individuals is physically adult and start to face the risk of HIV/AIDS through heterosexual sex. Although under 15 year old children can contribute to their households with their labor, we do not think that decreasing the lower bound would change the results since most of them do not die due to HIV/AIDS shown below. On the other hand, we set the upper bound of the age range at 50. Figures 1 and 2 show the distribution of age by gender in the data. Figures 3 and 4 show the distribution of deceased individuals’ age by gender. Figures 5, 6, 7, and 8 show the distribution of age of deceased individuals due to HIV/AIDS .