Tag: agriculture

A semiclassical model- in which electrons within the system redistribute themselves in the out-of-plane direction to screen this electric field- does not apply; instead, the wave functions hosted by the two dimensional crystal are themselves deformed in response to the applied electric field . This changes the electronic band structure of the crystal directly, without affecting the electron density. So to summarize, when a two dimensional crystal is encapsulated with gates to produce a three-layer capacitor, researchers can tune both the electron density and the band structure of the crystal at their pleasure. In the first case, this represents a degree of control that would require the creation of many separate samples to replicate in a three dimensional system. There is a temptation to focus on the exotic phenomena that these techniques for manipulating the electronic structure of two dimensional crystals have allowed us to discover, and there will be plenty of time for that. I’d first like to take a moment to impress upon the reader the remarkable degree of control and extent of theoretical understanding these technologies have allowed us to achieve over those condensed matter systems that are known not to host any new physics. I’ve included several figures from a publication produced by Andrea’s lab with which I was completely uninvolved. It contains precise calculations of the compressibility of a particular allotrope of trilayer graphene as a function of electron density and out-of-plane electric field based on the band structure of the system .

It also contains a measurement of compressibility as a function of electron density and out-of-plane electric field, plastic growers pots performed using the techniques discussed above . The details of the physics discussed in that publication aren’t important for my point here; the observation I’d like to focus on is the fact that, for this particular condensed matter system, quantitatively accurate agreement between the predictions of our models and the real behavior of the system has been achieved. I remember sitting in a group meeting early in my time working with Andrea’s lab, long before I understood much about Chern magnets or any of the other ideas that would come to define my graduate research work, and marvelling at that fact. Experimental condensed matter physics necessarily involves the study of systems with an enormous number of degrees of freedom and countless opportunities for disorder and complexity to contaminate results. Too often work in this field feels uncomfortably close to gluing wires to rocks and then arguing about how to interpret the results, with no real hope of achieving full understanding, or closure, or even agreement about the conclusions we can extract from our experiments. Within the field of exfoliated heterostructures, it is now clear that we really can hope to pursue true quantitative accuracy in calculations of the properties of condensed matter systems. Rich datasets like these, with a variety of impactful independent variables, produce extremely strong limits on theories. They allow us to be precise in our comparisons of theory to experiment, and as a result they have allowed us to bring models based on band structure theory to new heights of predictive power. But most importantly, under these conditions we can easily identify deviations from our expectations with interesting new phenomena- in particular, situations in which electronic interactions produce even subtle deviations from the predictions of single particle band.

This is more or less how I would explain the explosion of interest in the physics of two dimensional crystalline systems within experimental condensed matter physics over the past decade. If you ask a theorist if two dimensional physical systems have any special properties, they will tell you that they do. They might say that the magnetic phase transitions in a Heisenberg model on a two dimensional lattice differ dramatically from those on a three dimensional one. They might say that high Tc superconductivity is apparently a two dimensional phenomenon. They might note that two dimensional electronic systems can support quantum Hall effects and even be Chern magnets , while three dimensional systems cannot. But it is easy to miss the forest for the trees here, and I would argue that interest in these particular physical phenomena is not behind the recent explosion in the popularity of the study of exfoliated two dimensional crystals in condensed matter physics. Instead, much more basic technical considerations are largely responsible- it is simply much easier for us to use charge density and band structure as independent variables in two dimensional crystals than in three dimensional crystals, and that capability has facilitated rapid progress in our understanding of these systems. The techniques described above still have some limitations, and chief among them is a limited range of electronic densities that they can reach. Of course, the gold standard of electron density modulation is the ability to completely fill or deplete an electronic band, which requires about one electron per unit cell in the lattice. Chemical doping can achieve enormous offsets in charge density, sometimes as high as one electron per unit cell.

Electrostatic gating of graphene can produce crystals with an extra electron per hundred unit cells at most. This limitation isn’t fundamental and there are some ideas in the community for ways to improve it, but for now it remains true that electrostatic gates can modify electron densities only slightly relative to the total electron densities of real two dimensional crystals. As it stands, electrostatic gating can only substantially modify the properties of a crystal if the crystal happens to have large variations in the number and nature of available quantum states near charge neutrality. For many crystals this is not the case; thankfully it is for graphene, and for a wide variety of synthetic crystals we will discuss shortly. Electrostatic gating of two dimensional crystals was rapidly becoming a mature technology by the time I started my PhD. So where does nanoSQUID magnetometry fit into all of this? A variety of other techniques exist for microscopic imaging of magnetic fields; the most capable of these other technologies recently developed the sensitivity and spatial resolution necessary to image stray magnetic fields from a fully polarized two dimensional magnet, with a magnetization of about one electron spin per crystalline unit cell, and this was widely viewed within the community as a remarkable achievement. We will shortly be discussing several ferromagnets composed entirely of electrons we have added to a two dimensional crystal using electrostatic gates. Because of the afore-mentioned limitations of electrostatic gating as a technology, this necessarily means that these will be extremely low density magnets with vanishingly small magnetizations, at least 100 times smaller than those produced by a fully polarized two dimensional magnet like the one in the reference above. It is difficult to summarize performance metrics for magnetometers, especially those used for microscopy. Many magnetometers are sensitive to magnetic flux, not field, so very high magnetic field sensitivities are achievable by simply sampling a large region, but of course that is not a useful option when imaging microscopic magnetic systems. Suffice to say that nanoSQUID sensors, blueberry in pot which had been invented in 2010 and integrated into a scanning probe microscope by their inventors by 2012, combine high spatial resolution with very high magnetic field sensitivity. This combination of performance metrics was and remains unique in its ability to probe the minute magnetic fields associated with gate-tunable electronic phenomena at the length scales demanded by the size of the devices. Gate-tunable phenomena in exfoliated heterostructures and nanoSQUID microscopy were uniquely well-matched to each other, and although at the time I started my graduate research only a small handful of gate-tunable magnetic phenomena had so far been discovered in exfoliated two dimensional crystals, nanoSQUID microscopy seemed like the perfect tool for investigating them.So what exactly is nanoSQUID microscopy? We can start by discussing Superconducting Quantum Interference Devices, or SQUIDs. In summary, SQUIDs are electronic devices with properties that strongly depend on the magnetic field to which they are exposed, which makes them useful as magnetometers. I won’t delve into the details of how and why SQUIDs work here, but I will explain briefly how SQUIDs are made, since that will be necessary for understanding how nanoSQUID imaging differs from other SQUID-based imaging technologies. A SQUID is a pair of superconducting wires in parallel, each with a thin barrier in series . The electronic transport properties of this device depend strongly on the magnetic flux through the region between the wires, i.e. inside the hole in the center of the device in Fig. 1.3.

To be a little bit more precise, superconductors transport current without dissipation, so long as the current density stays below a sharp threshold. When this threshold is exceeded, the superconductor revertsto dissipative transport, like a normal metal. Above this critical current, in the so-called ‘voltage state,’ electronic transport is dissipative and highly sensitive to B. Any non-superconductor can function as a barrier, including insulators, metals, and superconducting regions thinner than the coherence length.This is sufficient for many applications, but it presents some issues for producing sensors for scanning probe microscopy. Scanning probe microscopy is a technique through which any sensor can be used to generate images; we simply move the sensor to every point in a grid, perform a measurement, and use those measurements to populate the pixels of a two dimensional array . This can of course be done with a SQUID, and many researchers have used SQUIDs fabricated this way to great effect. But the spatial resolution of a scanning SQUID magnetometry microscope is set by the size of the SQUID, and there are limits to how small SQUIDs can be fabricated using photo lithography. It is also challenging to fashion these SQUIDs into probes that can be safely brought close to a surface for scanning; photo lithography produces SQUIDs on large, flat silicon substrates, and these must subsequently be cut out and ground down into a sharp cantilever with the SQUID on the apex in order to get the SQUID close enough to a surface for microscopy. In summary, the ideal SQUID sensor for microscopy would be one that was smaller than could be achieved using traditional photo lithography and located precisely on the apex of a sharp needle to facilitate scanning. As is so often the case when developing new technologies, we have to make the best of the tools other clever people have already developed. In the case of nanoSQUID microscopy, the inventors of the technique took advantage of a lot of legwork done by biologists. Long ago, glass blowers found that hollow glass tubes could be heated close to their melting point and drawn out into long cones without crushing their hollow interiors. Chemists used this fact to make pipettes for manipulating small volumes of liquid, and biologists later used the techniques they developed to fashion microscopic hypodermic needles that could be used to inject chemicals into and monitor the chemical environment inside individual cells in a process called patch-clamping. A rich array of tools exist for producing these structures, called micropipettes, for chemists and biologists. Eli Zeldov noticed that these structures already had the perfect geometry to serve as substrates for tiny SQUIDs. By depositing superconducting materials onto these substrates from a few different directions, one can produce superconducting contacts and a tiny torus of superconductor on the apex of the micropipette. The same group of researchers successfully integrated these sensors into a scanning probe microscope at cryogenic temperatures. The sizes of these SQUIDs are limited only by how small a micropipette can be made, and since the invention of the technique SQUIDs as small as 30 nm have been realized. We call these sensors nanoSQUIDs, or nanoSQUID-on-tip sensors. A few representative examples of nanoSQUID sensors are shown in Fig. 1.4. A characterization of the electronic transport properties of such a sensor, and in particular the sensor’s response to an applied magnetic field, is shown in Fig. 1.5. NanoSQUID microscopes share many of the core competencies of more traditional, planar scan-ning SQUID microscopes. They dissipate little power, and the measurements they generate are quantitative and can be easily calibrated by measuring the period of the SQUID’s electronic response to an applied magnetic field.

The imaging unit consists of 24 independent objectives attached to a vertical sliding stage using 4 maker beam vertical columns and 2 Nema-11 stepper motors , an example of a row can be seen in Fig. 4a. The fine threads are necessary for focusing on specific biological features and collecting z-stack imaging . With this fixed lens system, the system has a field of view of approximately 5 mm. The Picroscope is able to resolve Group 7, Element 1 targets , corresponding to a resolution of 7 μm . If higher resolution is needed the lens can be swapped out for more magnification . The lens currently on the system was chosen due to our interest in imaging whole organisms. The objectives are distributed on 4-rows and 6-columns to match a standard 24-well culture plate. Each objective consists of a 3D printed camera body that hosts a 5 MegaPixel camera and an off-the-shelf Arducam 1/2” M12 Mount 16 mm Focal Length. Each objective is controlled by a single-board computer , which is connected to an individual slot on one of the three custom-made power distribution boards . All 24 single-board computers computers communicate to a hub board computer that manages the images and autonomously uploads them to a remote server. The hub single-board computer has the MIPI CSI-2 camera port and is connected to an Arduino Uno, which has a motor shield attachment, to control the motors and lift the elevator piece . As a safety feature, the system also includes a custom-made Relay Board that is attached to the Arduino and motor driver stack. The relay board provides control of the LED boards and in the event of an overheat allows us to shut down the system, protecting the system and the biological sample. After each set of pictures, the imaging unit returns to the lowest position, plastic planters bulk which is determined by a limiting switch attached to the elevator unit.

The entire system sits on a 3D printed base, that includes a fan for heat dissipation. Supplementary Fig. 3 shows thermal images of the Picroscope to demonstrate that heat from the system does not impact the experiment. A guide on how to assemble the Picroscope and components needed can be found in Table 2 and Supplementary Note 1. During the course of an experiment, the pictures are autonomously uploaded on a remote computer/server using the ethernet connection of the hub computer board, where they can be viewed or processed in near real time .As proof of principle of the longitudinal live imaging capabilities of the Picroscope, we imaged the development of Xenopus tropicalis embryos from the onset of gastrulation through organogenesis . The fertilization and development of Xenopus occur entirely externally, which allows scientists to easily observe and manipulate the process. For decades, Xenopus have been heavily used in biology studies to model a variety of developmental processes and early onset of diseases, particularly those of the nervous system. While several species of Xenopus are used in different laboratories around the world, Xenopus tropicalis is one of the preferred species due to its diploid genomic composition and fast sexual maturation. Normal development and optimal husbandry of Xenopus tropicalis occur at 25∘ –27 ∘ C, closely approximating standard room temperature, which eliminates the need of special environmental control for most experiments. Given these convenient experimental advantages and their large size, Xenopus embryos have been used extensively to understand the development of the vertebrate body plan, with particular success in elaborating the complex cellular rearrangements that occur during gastrulation and neural tube closure.

These experiments rely on longitudinal imaging of developing embryos, often at single-embryoscale with dyes, fluorescent molecules, and computational tracking of single cells. These studies have elucidated key cellular mechanical properties and interactions critical to vertebrate development, often replayed and co-opted during tumorigenesis. There exists an opportunity to scale these experiments to be more high-throughput with the Picroscope, as one could image hundreds of developing embryos simultaneously, rather than having to move the objective from embryo to embryo during development, or repeating the experiment many times. We imaged Xenopus tropicalis embryos over a 28 h time period. Four embryos were placed in each of the 23 wells used in a 24-well plate, and we used an extra well as calibration . The embryos were grown in simple saline solution and the experiment took place at room temperature. Imaging was performed hourly starting at gastrulation . Then, we visually inspected each image and mapped the embryos to the standard stages of frog development, categorizing their development in gastrulation, neurulation, and organogenesis . Finally, we took a subset of 27 embryos and measured the diameter of the blastopore as the embryos underwent gastrulation . Only 27 embryos were used because those were the only embryos with their blastopores clearly visible throughout the image set. We observed a progressive reduction of blastopore diameter over a 6 h time period, consistent with progression through gastrulation and the start of neurulation. This simple experiment demonstrated that the Picroscope can be used for longitudinal sequential imaging and tracking of biological systems.

While many biological systems including zebra- fish, planaria, and frogs develop at room temperature and atmospheric gas concentrations, mammalian models require special conditions requiring an incubator enclosure. Mammalian models include 2D monolayer cell cultures, as well as 3D organoid models of development and organogenesis. They have been used to assess molecular features and effects of drugs for a variety of phenotypes including cell proliferation, morphology, and activity, among others. Deploying electronics and 3D printed materials inside tissue culture incubators presents some unique challenges. The temperature and humidity conditions can cause electronics to fail and cause certain plastics to off gas toxins. Plastics can also be prone to deformation in these conditions. A common solution for protecting electronics and preventing off gassing is to use inert protective coatings e.g., Parylene C. This requires expensive clean room equipment. Instead, we print all of the components with PLA, a nontoxic and biodegradable material, to prevent deformation we print using 100% infill and reinforce vulnerable elements with aluminum MakerBeam profiles. We coat all electronic components with Corona Super Dope Coating to protect the electronics from the conditions of an incubator. We tested the functionality of the Picroscope inside a standard tissue culture incubator by imaging 2D-monolayers of human embryonic stem cells . To demonstrate the capacity of our system to perform longitudinal imaging across the z-axis, we imaged human cortical organoids embedded in Matrigel . Using this system, we could monitor and measure the growth of the organoids over 86 h . Tracking of individual cells within organoid outgrowths allowed us observe their migration patterns and behavior . Altogether, we show the feasibility of using our system for longitudinal imaging of mammalian cell and organoid models.The combination of 3D printed technology and open-source software has significantly increased the accessibility of academic and teaching laboratories to biomedical equipment. Thermocyclers, for example, were once an expensive commodity unattainable for many laboratories around the world. Now, lowcost thermocyclers have been shown to perform as well as high end commercially available equipment. Inexpensive thermocyclers can be used in a variety of previously unimaginable contexts, including conservation studies in the Amazon, collection pot diagnostics of Ebola, Zika and SARS-CoV-2, teaching high-school students in the developing world and epigenetic studies onboard the International Space Station. Simultaneous imaging of biological systems is crucial for drug discovery, genetic screening, and high-throughput phenotyping of biological processes and disease. This technique typically requires expensive multi-camera and robotic equipment, making it inaccessible to most. While the need for a low-cost solution has long been appreciated, few solutions have been proposed. Currently, the low-cost solutions can be grouped in two categories: those that use gantry systems that move an individual camera through multiple wells, performing “semi-simultaneous” imaging or those that use acquisition of large fields of view encompassing multiple wells , where they can be viewed and/or processed , with minimal intervention. Commercial electronic systems for simultaneous imaging of biological samples are typically designed to image cells plated in monolayers. Yet, significant attention has been given to longitudinal imaging-based screens using whole organisms. These have included zebrafish, worms, and plants. Many times, the results of the screens are based on single-plane images or in maximal projections obtained from external microscopes.

This is accomplished with fine adjustment by two stepper motors that lift the elevator unit that holds all 24 camera objectives .To date, few 3D printed microscopes are designed to function inside incubators. We have run the Picroscope in the incubator for three weeks. This makes the Picroscope compatible with screens in 3D mammalian models including organoids. We have shown a proof of principle of this function by performing longitudinal imaging of human cortical organoids and analyzing the behavior and movement of individual cells . We anticipate many useful applications of the Picroscope and derivatives of it. Here, we demonstrated the versatility of the Picroscope across animal and cell models in different environmental conditions. The modular nature of the system, allows for new features to be easily built and added. For example, defined spectrum LED light sources and filters for fluorescent imaging would enable longitudinal studies of the appearance and fate of defined sub populations of cells in a complex culture by taking advantage of genetically encoded fluorescent reporter proteins. Similarly, the use of fluorescent reporters or dyes that respond to dynamic cell states such as calcium sensors allow long-term imaging of cell activity.Most studies that monitor plants and their environment, whether it be in the field or in the laboratory, require sensors that convert physical or chemical energy into an electrical signal. Some examples of sensors commonly used in plant research are thermocouples, which convert temperature gradients into an electrical potential; photodiodes, which convert light into an electrical current; and strain gauges, which have an electrical resistance that changes when deformed. Many existing methods, such as sap flow measurement , measuring chloroplast movement , and lysimeters , utilize these types of sensors, and nearly all methods that use sensors require a data acquisition system to record measurements. Such systems usually have two basic components: an analog‐ to‐digital converter that converts the electrical signal from the sensor into digital information and a microcontroller or computer that records and processes the digital information from the ADC . There are many commercially available DAQ systems, but these products are often expensive and lack flexibility; a project may need a custom DAQ system to overcome these limitations. One ideal choice for a custom system is a Raspberry Pi computer paired with a high‐resolution ADC. The low cost, flexibility, and high resolution of such a system is ideal for improving existing plant research methods or for developing new ones. The Raspberry Pi is an inexpensive, single‐board computer that has many easily accessible and configurable input/output interfaces, including multiple serial peripheral interfaces and general‐purpose input/output pins , which allow it to be used with a wide variety of ADCs and other peripheral devices. It can run many different operating systems, but the most common is the Linux‐based Raspberry Pi OS, which supports most programming languages. The Raspberry Pi and other similar single‐board computers have many possible applications in life science research. Its small size and low cost make it suitable for data logging in a variety of environments. The easily accessed I/O interfaces can be connected to many different types of sensors for data acquisition, including cameras for high‐throughput plant imaging , microphones for bioacoustic data collection , or gas sensors for air quality monitoring . These same interfaces can also be used to control external components such as mechanical actuators, lighting, or temperature control. To use sensors for data logging with a Raspberry Pi, an ADC is needed to convert the analog output of a sensor into digital information that the computer can use. Many different ADCs are available for this purpose, and it is important to choose one that is appropriate for the application. A few important specifications to consider when choosing an ADC are bit resolution, sampling rate, and number of channels. There is a necessary tradeoff between an ADC’s sampling rate and effective resolution, in that ADCs with very high resolutions are limited to sampling rates in the kilohertz range or less and that as the sampling rate of a given ADC is increased the effective resolution declines . For applications where ultra‐high‐resolution is not critical, there are many ADCs on the market that have readily available open‐ source software libraries and schematics for interfacing with a Raspberry Pi.

Hyperspectral imaging was deployed to identify contaminated mangos. The algorithm’s overall error proportion of high infested samples ranges between 2% and 6%, whereas the algorithm’s overall error rate for low infested samples is 12.3 percent. To detect contaminated cherries, Xing et al. used reflectance and transmittance spectra. According to the extent of damage, the cherries were separated into two categories: “acceptable” and “nonacceptable.” On transmittance spectra, Canonical Discriminant Analysis achieved 85 percent classification accuracy. Potamitis et al. used optoacoustic spectrum analysis to construct an olive fruit fly detection system. The optoacoustic spectrum analysis detects the species of insects based on wing beat analysis. The authors examined the recorded signal’s temporal and frequency domains. The random forest classifier is fed the retrieved features from the time and frequency domains. The random forest classifier had a precision of 0.93, a recall of 0.93, and an F1-Score of 0.93. The optoacoustic approach, on the other hand, cannot distinguish between different types of fruit flies, including peaches and figs. Furthermore, solar radiation affects sensor readings, and the trap is susceptible to sudden strikes or shocks that cause false alarms on windy days. Böckmann et al. utilizes Bag of Visual Words to encode clusters of key points extracted by scale-invariant feature transform into some meaningful local features in a so-called visual codebook. This kind of dictionary is then used to incorporate how frequent each feature appears in each patch of newly extracted key points as the input to train an SVM classifier for different classes of flies as well as one background class for a patch of nothing of interest.

In contrast, blueberry containers the precision values decreased after 7 days of the insects remaining on the Yellow Sticky Paper by approximately 20% compared to the test results of the initialization measurement on day 0. Regarding class mean accuracy, the dictionary size had no obvious influence but on the recall in individual categories. Within the individual categories, the recall of the background class was the highest, as expected. A maximum value of 99.13% was achieved without differences in color space conversion or dictionary size. The best classification results were achieved with greyscale images and dictionary sizes of 200 and 500 words. Regarding deep learning techniques, Zhong et al. created a deep-learning-based multi-class classifier that can classify and count six different types of flying insects. The You Only Look Once algorithm is used for detection and coarse counting. To increase the number of training images required by the YOLO deep learning model, the scientists considered the six species of flying insects as a single class. The authors augment the images with translation, rotation, flipping, scaling, noise addition, and contrast adjustment to extend the data set size. They also employed a pre-trained YOLO to fine-tune its parameters on an insect dataset. Support Vector Machine is used for classification and fine counting, with global features. The technique was run on Raspberry PI, with detection and counting performed locally in each trap. The system attained a 92.5 percent average counting accuracy and a 90.18 percent average categorization accuracy. The Dacus Image Recognition Toolkit was created by Kalamatianos et al.. The toolkit includes MATLAB code samples for fast experimentation, as well as a collection of annotated olive fruit fly photos acquired by McPhail traps.

On the DIRT dataset, the authors tested various forms of the pre-trained Faster Region Convolutional Neural Networks deep learning detection technique. Prior to classification, RCNNs are convolutional neural networks containing region proposals that suggest the regions of objects. Faster-RCNN had a mAP of 91.52 percent, where mAP is the average maximum precision for various recall levels. The authors demonstrated that image size has a substantial impact on the detection, but RGB and grayscale images have almost the same detection accuracy. Because Faster RCNN is computationally costly, each e-trap regularly uploads its collected image to a server for processing. Ding et al. created a technique for detecting moth flies. Translation, rotation, and flipping are used to enhance the visuals. To balance the average intensities of the red, green, and blue channels, the photos are pre-processed with a color-correcting algorithm. The moths in the photos are then detected using a sliding window Convolutional Neural Network . CNNs are supervised learning algorithms that use learned weights to apply filters on picture pixels. Back propagation is used to learn the weights. Finally, Non-Max Suppression is used to remove the overlapping bounding boxes . Using an end-to-end deep learning neural network, Xia et al. detect 24 kinds of insects in agriculture fields. A pre-trained VGG-19 network is utilized to retrieve the features. The insect’s position is then determined through the Region Proposal Network . The proposed model had a mAP of 89.22 percent. Recently, YOLO is proving its notable performance in the work in pest detection. Especially, the reported results of YOLO v5 by the authors illustrate the mAP of 94.7 percent, where it has the highest recall score of 0.92 among all the other state-of-the-art methods, such as Fast RCNN, Faster RCNN and RetinaNet.

The models have been pretrained on COCO dataset and later fine-tuned on a training dataset of 4480 sub-images made from 280 images of yellow sticky pheromone traps. However, YOLO v5 is considered slower than YOLOv4. For the AI implementation on edge devices, works in demonstrate the AI applications on edge devices pest monitoring as well. In [30], Lynfield-inspired trap was used with naled-and fipronilintoxicated methyl eugenol in replacement of the yellow sticky paper trap combined with object detection system to detect only targeted oriental yellow flies. Unlike the yellow sticky paper, the substance is proved to only attract harmful fruit flies and the detection problem is thus reduced to one class detection for detecting the existence of the fruit flies and verifying whether the detection is correct. The work showed primary work and provided foundation to further develop real-time system for yellow fly detection in on-field scenario. Compared to [27], the application Single Shot Multibox Detector with variant backbones and YOLOv4- tiny show significant speed performance to YOLO v5, while taking the raw images as input instead of segmented sub-images. Nevertheless, the work also showed limitation of applying detection models on edge device due to the slow processing speed, which will be further addressed in this article.Most of the time, insects are not stationary, so it is difficult to get a clear image of flying insects. In studies [32 – 35], the authors chose insect specimens that were well-preserved in an ideal laboratory environment to capture images of the insects at high resolution. However, since fewer environmental factors are considered in this method, it is limited in specific applications. In this study, we designed a unique automatic autonomous environment data reading and pest identification system to try to eliminate the above problems. Being largely motivated by preventing the oriental fruit flies from destroying citrus fruits such as oranges and grapefruits, we come up with a trap which targets only that one type of the species, best indoor plant pots which is specifically named B. Dorsalis. This can be achieved by replacing the yellow sticky paper with the naled-and fipronil-intoxicated methyl eugenol attractant to assure only B. Dorsalis flies are lured into the trap. It eases the classification and counting process as no other insects will get attracted by the methyl eugenol attractant . The system involves a two-fold setting: a) an electronic system reads environment data with a sticky trap installed and a digital camera is set up to collect images of the flies, b) the object detection software to recognize fruit flies on the image before sending all information via email or SMS to alert farmers independently. The whole system is autonomous and powered by a solar system. This system is implemented on an Arduino Uno and Raspberry Pi system. The results provide precise prevention and treatment methods based on the combination of pest information and other environmental information. Based on this edge computing design, the computation pressure on the server is alleviated and the network burden is largely reduced.

The edge-computing traps are designed to work separately and individually re-port the count of fruit flies to the farmers. They are spread, based on the effectiveness of the attractant, such that each 2-3 devices can cover an area of 1000 square meters.Overall, the hardware part of the system consists of five interconnected subsystems with distinctive functions and behaviors, which are described in Figure 1, namely the solar panel system, the control system, the sensor system, the trap, and the object detection and communication system. The power system of the trap contains a solar panel, a battery, and a solar charge controller . The solar panel converts the solar energy to DC current with 830 mA to power the trap system. The converted energy is stored in an electro-chemical energy storage with a capacity of 5 Ah and a voltage of 12 V. The Arduino in the operating system will check voltage of the battery with a voltage sensor to make sure the battery voltage is above a certain level required for the system’s operation. If the condition is not met, the object detection module will not be operated. The Pulse Width Modulation solar charge controller is used to control the device voltage, open the circuit, and halt the charging process if the battery voltage is above a certain level. The operation system is controlled by an Arduino micro-controller board. As aforementioned, the Arduino module reads the battery voltage with a voltage sensor from the sensor system to decide whether to turn on or off the object detection system, which is controlled by the Raspberry module. The SSR10D is used to control activate and deactivate the object detection system. The SSR10D is a solid-state relay and uses lower power electrical signal to generate an optical semiconductor signal as an activate signal for the opto-transistor to allow high voltage going into and powering the device’s output device, which is the Raspberry device in this case. In addition, the lower electrical signal is the output from the 2N2222 bipolar junction transistor receiving control signal from the Arduino module. Hence, the Arduino can stop the Raspberry Pi 3b+ computer drawing current from the solar system after it is shut down. The sensor system takes responsibility for measuring the three important factors, temperature, humidity, and light. Also, it records the current created by the solar system and the voltage battery. The humidity and temperature, which also affect the living environment of the yellow flies, are measured with the AM2315 I2C sensor. RGB and clear light is measured with the TCS34725 light sensor with IR filter and white LED. In addition to sensor system, INA219 is used to read the solar current and battery voltage information. Moreover, a DS1307, which is a battery-backed real time clock , is used to help the microcontroller keep track of time. The information from the sensors along with their corresponding time are stored in an SD card attached on the device. These two factors, the operation system and sensor system, help the microcontroller decide whether to turn on the object detection or not. The object detection system, shown in Figure 1e, is operated by the Raspberry Pi 3b+ and collect images for its fruit fly detection algorithm with a Waveshare Pi camera with 5 MP. The camera is placed at the top of a double-size Lynfield shape trap with several holes at the bottom, shown in Figure 1d. To attract and capture only the yellow flies, methyl eugenol is used as the attractant to the insects, which later helps to simplify the detection and classification problem. The Raspberry Pi module will receive data from the sensor system and send all data to the notification system to notify or alert farmers about the environmental data and the number of detected fruit flies through email or SMS. The behavior of the whole system is described in the flow chart shown in Figure 2.The architectures used to train the yellow fly detection models are SSD with MobilenetV1 and MobilenetV2 backbones, and YOLOv4-tiny. The selected models are all single-stage detection models since, compared to their counterpart, the two-stage detection models, the single-stage detection models have been shown to have a faster processing speed with a competitive performance. Moreover, the three models were selected because of their comparable parameter size and their feasibility for real-time implementation on edge devices.

We show that six of eight ant species limit CBB colonization of berries and that the effect of ants is independent of ant activity on branches. This study is the first field experiment to provide evidence that a diverse group of ant species limits the CBB from colonizing coffee berries.To test the effects of each ant on CBB colonization of berries, we performed an ant exclusion experiment. We surveyed bushes occupied by one of the eight target ant species. We excluded coffee bushes with few branches to control for the size of the foraging area of each ant species. On each bush, we searched for two branches of equal age and position and roughly the same number of coffee berries . On each branch, we removed all berries that had CBB entrance holes. We then removed all ants from one branch and applied tangle foot to the base of the branch near the coffee trunk. On the second branch, we left ants to forage freely . To estimate ant activity, we counted the total number of ants foraging on the stem, leaves, and berries of each branch for 1-min including those that travelled onto the branch during the 1-min survey. We also counted ants on exclusion branches after the experiment and if a branch had more than one ant individual present, we excluded the bush from analysis . To release CBB onto control and treatment branches, we created a leaf platform to aid their chances of encountering berries. The leaf was wedged between the branch stem and a cluster of berries to create a platform surrounding the cluster . A coffee leaf was used as a platform because artificial structures attract attention from many ant species. After waiting several minutes to ensure normal ant activity, blueberries in pots we released 20 CBBs on the leaf platforms of the control and exclusion branches.

After 24 h, we counted the number of berries per branch that had CBBs inside entrance holes. We did not count partially bored holes in berries, nor CBBs that had bored into twigs and leaves. Multiple bored entrance holes per berry were only counted as one bored berry. We modified the experiment slightly for P. simplex and P. ejectus because of the difficulty in locating these species within a bush using visual cues . For these two species, we used the living branch to which the nest was attached to as the control branch . This was done because we wanted to make sure that ants were actively foraging on control branches after the disturbance of removing nests. To statistically analyze experimental data, we opted to use linear mixed models instead of paired t tests because mixed models allow inclusions of experimental non-independencies through the incorporation of covariates. We included bush as a random effect in the model to pair control and exclusion branches within each bush. Ant species and treatment and the species 9 treatment interaction were included as fixed effects in the model. To control for differences between each branch and bush, we included the number of berries per branch, the number of berries in contact with the leaf platform, and the number of worker ants per branch as covariates in the model. We performed type III F tests of significance for main effects with maximum likelihood to estimate the fixed effect parameters and variance of random effects . We removed non-significant factors from models and compared nested and null models with likelihood ratio tests to determine the best-fit model. We also compared ant activity across different species to determine if this factor might correlate with berries bored and vary across ant species.

To determine if ant activity correlated with the number of coffee berries bored, we limited the dataset to only control branches and used a generalized linear model with a Poisson log-link function because data did not meet the assumptions of normality. To determine if ant activity varied by species, we again limited the dataset to only control branches and used ANOVA with Tukey’s HSD analysis. We tested the normality of the data with qq-plots and Kolmogorov–Smirnov tests of model residuals. We conducted all statistical analyses with SPSS .Our study represents one of the first field experiments showing that a broad survey of ants reduce colonization of coffee berries by the CBB. This is in contrast to previous studies that suggest ants may not have any effects on CBB, especially in field experiments . Our results are in accordance with other observational studies that show that specific ant species may limit CBB in coffee plantations, yet these studies have either focused on the most dominant or abundant species observed or investigated the broad community-wide impacts of ants on the CBB . Our experimental approach is limited to our understanding of how ants control CBB colonization of berries and not other life stages of the CBB. Our study suggests that ant occupation of coffee bushes is very important during a seasonal period when new coffee berries develop and the CBB begins to disperse from old infested berries to developing un-infested berries . It is surprising that Crematogaster spp. and S. picea did not limit the colonization of berries, considering that other studies have shown species within these two genera have important effects on herbivores .

Low ant activity on coffee bushes with Crematogaster spp. or S. picea cannot explain these results because thesespecies had greater activity per branch than P. ejectus and P. simplex and equivalent activity to A. instabilis and P. synanthropica, species that did limit CBB damage. One explanation could be that because we grouped five Crematogaster spp. together into a single treatment, effects of individual species may be masked. Solenopsis picea may have an effect on CBB colonization, but only with higher ant activity or when CBB are in closer proximity to nest entrances. This species also has a small body size and moves relatively slowly in comparison to the species that did have an effect, which might have limited it from removing or easily capturing CBBs. Wasmannia auropunctata is of similar size to S. picea and still had strong effects on CBB. However, W. auropunctata had significantly higher ant activity on branches as compared to S. picea. Perhaps the combination of low activity, small body size, and slower movement limited S. picea from affecting the CBB. While we found no effect of S. picea on CBB colonization of berries, it may be that S. picea, and other smaller ants, have important impacts on the CBB at other stages of the CBB life cycle because they can pass into entrance holes of the CBB . Experiments with both P. simplex and P. ejectus employed slightly different methodologies than the other ant species, which may have intensified the effect of these ants. For these two species, hollow twigs that contained ants were attached to a branch with berries and this branch was used as the control branch in the experiment. This likely elevated the number of ants per branch per minute. However, in the lab, P. simplex had similar effects on the CBB . Additionally these two species had the lowest densities on control branches of all other species, averaging 3.6 and 3.7 ants per branch for P. ejectus and P. simplex, respectively. Thus, these species have effects at very low numbers, and the results of this study should only pertain to branches for which the density of these species reaches this mark. Certain aggressive ants that limit CBB colonization of berries might also benefit CBB after colonization. Larger ants cannot enter berries, but if they are aggressive competitors for space, square plant pots they will prevent other ants from occupying the branches they patrol . These ants, likely A. instabilis and P. synanthropica, may provide CBB with enemy free space after the CBBs colonize berries in their territories. In conclusion, we find that six of eight ant species limited CBB colonization of coffee berries suggesting that ants, generally, provide important pest control services within coffee agroecosystems. This is the first field experiment to demonstrate general ant limitation of CBB colonization. This finding is important considering that chemical pesticides are thought to be ineffective at controlling the CBB . Nonetheless, ants do not completely control the CBB, other control agents like birds, parasitoids, and fungal pathogens also aid in the control of the CBB . Further work should look at larger scale impacts of ants on the CBB, such as farm scale impacts. Also, more theoretical work is needed to understand how ants impact the CBB at different stages of its life cycle and to reveal which stage of the life cycle is most important for population regulation. Nonetheless, this study provides strong evidence that ants defend coffee from CBB colonization.

Seminal work by Thouless and coworkers pointed out that band insulators are not identical, but can differ in fundamental respects, that are characterized by a topological property of the bands. The central example discussed was the integer quantum Hall state, whose topological properties are characterized by an integer which is essentially the Hall conductance. Realizing such a state naturally requires breaking of time reversal symmetry, typically by the application of a strong magnetic field on a two-dimensional system. The topological nature of the integer quantum Hall state is also revealed by studying the edge of a two-dimensional sample, where chiral edge states occur at energies within the bulk energy gap. Recently, it has been realized that band insulators with spin orbit interactions can also be characterized by their band topology. In two dimensions, the quantum spin hall phase is closely analogous to the quantum Hall state. However, since it preserves time reversal symmetry, it has a pair of counter-propagating one-dimensional modes at the edge. Such a state can occur with SOIs that preserve spin rotation symmetry about an axis. It was shown in Ref., that even in the absence of such spin rotation invariance, the counter-propagating modes remain protected by time reversal symmetry. The topological property of these insulators are characterized, not by an integer, but by aZ2 number, so that all topologically non-trivial insulators of this kind fall within the same topological class. An experimental realization of this phase has been reported in HgTe heterostructures. Turing to three dimensions, an insulator with nontrivial band topology can be realized just by stacking such two-dimensional QSH states. These are called the weak topological insulators . However, a more surprising possibility, the strong topological insulator , has been predicted theoretically. Once again, the surface physics is exotic, which provides a physical characterization of this phase. STIs have an odd number of Dirac nodes on their surface, which are stable against moderate perturbations that preserve time reversal symmetry. Such a band structure cannot be realized in any two-dimensional system with time reversal invariance. There have been experimental realizations of these predictions in bismuth antimony and in bismuth selenium, which have been verified by angle resolved photoemission spectroscopy. Note, in contrast to the QSH state, in order to realize the STI the SRS must be completely broken. The topological insulator and QSH phases normally exist in systems with strong SOI that explicitly breaks SRS. However, as pointed out in Ref.an extended Hubbard model on a two-dimensional honeycomb lattice can have spontaneous SRS breaking and result in a QSH phase, with the right kind of repulsive interactions. SRS is only preserved about an axis ˆn, which is spontaneously chosen, leading to gapless Goldstone modes. This was termed a topological Mott insulator – the separation of energy scales between the low lying magnetic excitations and the gapped charge excitations being typical of Mott insulators. We will also adopt this nomenclature although it must be noted that local moment physics, often associated with Mott insulators, does not occur here. Subsequently, it was argued in Ref. that skyrmions of ˆn carry charge 2e. Here, we consider the analogous problem of a three-dimensional system without bare spin orbit couplings, and full SRS, being driven into a TI state by strong interactions. The key difference from the two-dimensional case, is that in order to realize the STI, SRS must be completely broken. Hence the order parameter in this case is a rotation matrix ←→R ∈ O, similar to super fluid Helium-3 A and B-phases. Physically, this order parameter describes the orientation of the spin coordinate system, relative to the spatial coordinates. Spatial variations of the order parameter lead to a rich set of topological textures.

The Axion Maestro Edge is designed as an out-of-the-box benchtop electrophysiology system with maximum comfort and usability. Although it has the highest price per channel, it is also an incubator. The Intan RHD USB interface board and head stages require more effort to calibrate, ground, and shield. Unlike Axion, Intan designs and code are open source. Intan bio-amplifier chips have been used in many open source systems, including Intsy, Willow, Open Ephys, and now Piphys. Both Intan and Axion systems provide valuable perspectives for comparison to Piphys. Axion produces the lowest noise baseline but has a different bio-amplifier circuit. Piphys and Intan have the same bio-amplifier chip; therefore Intan is a good reference for ensuring Piphys has the same noise floor and low EMI. Piphys and Intan RHD interface board differ in the way they sample the bio-amplifier. Specifically, Intan has more stable sampling with FPGA, while Piphys samples the chip with a CPU, which has more clock jitter . Overall the neural waveforms recorded on both systems are statistically comparable in shape for neural spikes for the detected neuron. Other comparable platforms in the literature include Intsy, Willow, and Open Ephys. Intsy was designed for measuring gastrointestinal , cardiac , neural , and neuromuscular signals. Willow was designed for high channel count neural probes and resolved the need for many computers by writing data directly to hard drives. Open Ephys is an alternative system to Intan integrating more features into their GUI for closed-loop experiments and plugin-based workflows *. Noise measurements for Piphys, Intan, and Axion were experimentally recorded, blueberry pot while noise measurements for Intsy, Willow, and Open Ephys were cited. Intan claims 2.4 μV RMS as typical in the datasheet for their chips # which was likely inherited into Open Ephys documentation.

Remote longitudinal recording of neural circuits on an accessible platform will open up many exciting avenues for research into the physiology, organization, development, and adaptation of neural tissue. Integration with cloud software will allow in-depth experimentation and automation of analysis. The proof of principle for Piphys has been shown on 2D cultures. As experiments with other devices have shown, it should be applicable to measurements of 3D brain organoids, which are becoming an increasingly popular model for studying human brain tissue developmentand function. One example application of Piphys would be monitoring how genotypes affect neural activity over the course of organoid development. More generally, IoT devices would allow less invasive and less laborious collection of longitudinal datasets of organoid development, to benchmark what wild-type organoid activity looks like throughout the first few months of growth. It would be interesting to compare whether different protocols and cell lines affect organoid activity over the course of development. IoT devices could be distributed and shared to compare whether organoid datasets are replicable and comparable between different labs, using the same low-cost hardware. Many electrode probes have been designed to interface with tissues to provide measurement points for voltage recordings. Future work on Piphys would involve expanding the number of different electrodes types for long-term culture of the biological sample through collaborations with other research groups. Future work on Piphys also includes increasing sampling rate and precision of timing in between samples. Currently, the Raspberry Pi CPU samples the Intan RHD2132 bio-amplifier chip, and the sampling rates are limited by the CPU’s ability to multitask. Future solutions may involve adding another CPU or FPGA to the hardware shield.

The platform will continue to be improved, and its modularity allows adapting hardware and software components as different needs arise. The current proof of concept design is based on a Raspberry Pi chip and uses one 32 channel chip attached to one of the SPI ports. The system can be easily extended to sample 64 channels . The channel number can be doubled if the design would include an FPGA and alternative Intan chips that have 64 channels/chip . However, the true scalability advantage of the proposed system lies in its open source and open hardware architecture. If the number of channels is insufficient, the shield board could be modified to accept multiple Raspberry Pi’s, therefore, increase the number of channels. Piphys is the only electrophysiology device that supports Internet of Things software integration out of the box. The IoT hardware modules and cloud software allow for horizontal scalability, enabling long-term observations of development, organization, and neural activity at scale, and integration with other IoT sensors. Piphys has a low entry cost, and the cost per channel can also be significantly lowered by increasing the number of channels supported per device. This would be accomplished by engineering an inexpensive FPGA into the controller shield to sample multiple bio-amplifier chips and buffer those readings for the Pi. Piphys can have a large cost reduction if extra specialty connectors and adapters are removed and it is fitted with a USB cable which is less expensive. The signal-to-noise ratio could be improved by enabling and tuning on-chip filtering, and improving Faraday cage shielding. In vitro cultures typically fire with amplitudes between 10 – 40 μV . They demand sensitive recording equipment, as an increase of just afew μV in noise for spikes on the lower end of the spectrum can be considered a non-trivial variable. Overall, the open source Piphys design, programmability, and extreme flexibility of the Raspberry Pi significantly lowers the entry barrier of the electrophysiology system, providing an opportunity for broader applications in education and research.Prior to cell culture, the electrode surfaces of 6-well Axion plates were coated with 10 mg/mL poly-D-lysine at room temperature overnight.

The following day, plates were rinsed 4 times with water and dried at room temperature. Primary cells were obtained from human brain tissue at gestational week 21. Briefly, cortical tissue was cut into small pieces, incubated in 0.25% trypsin for 30 minutes, then triturated in the presence of 10 mg/mL DNAse and passed through a 40 μm cell strainer. Cells were spun down and resuspended in BrainPhys supplemented with B27 , N2 , and penicillin-streptomycin , then diluted to a concentration of 8,000,000 cells/mL. Laminin was added to the final aliquot of cells, and a 10 μL drop of cells was carefully pipetted directly onto the dried, PDL-coated electrodes, forming an intact drop. The plate was transferred to a 37 °C, 5% CO2 incubator for 1 hour to allow the cells to settle, then 200 μL of supplemented BrainPhys media was gently added to the drops. The following day, another 800 μL of media was added, and each well was kept at 1 mL media for the duration of the cultures, with half the volume exchanged with fresh media every other day. Activity was first observed at 14 days in culture, and the second recordings were performed on day 42 of culture.The power supplied to the Raspberry Pi is through a mains adapter plugged into the wall outlet. To reduce environmental noise and maximize the signal-to-noise ratio , we use a Faraday cage during recording. The Faraday cage is made of 1 mm thick steel and connected to the wall outlet ground. For noise measurement benchmarks on Piphys, nursery pots an empty Axion plate was filled with the same media used in cell culture and placed in the Faraday cage. The noise baseline of this media-only system was an average of 2.36 ± 0.4 μV RMS for all the channels with software filters. Comparison of the baseline noise we measured for Piphys, Intan, and Axion is in Table 1. During the experiment, the systems were compared by measuring the same neural culture on the same plate within a similar time frame. Recordings occurred within 1 to 3 hours of each other. A 300–6000 Hz 3rd order Butterworth bandpass filter was used to attenuate frequency components outside the neural activity range after the recording. Data was analyzed by a spike sorting algorithm and shown side by side in Figure 6 over an identical time length. Instructions and source files for construction of Piphys hardware and software are available open source on GitHub ††. All files are provided ‘as is’ and endusers are encouraged to freely use and adapt the system for their own application-specific protocols.The printed circuit board was designed in Autodesk Eagle. The board has four layers of copper. The top and bottom layers of the board are GND, while the two layers inside are signal and power. Every signal via has a ground via next to it to sink EMI as signals switch layers. The layout of the circuit board is done in modules. Via stitching was done around the perimeter and throughout the board area to separate modules and fill in areas with no components. The amplifier chip and Raspberry Pi computer are separated by a cable such that noise from the computer would not interfere with the sensitive neural signal recording. During data acquisition, all of the electronics and biology were shielded by a 1 mm thick steel faraday cage.We deployed servers and cloud computing platforms to achieve permanent data storage and messaging between the local device and the dashboard. We used Remote Dictionary Server , Amazon Web Services Internet of Things , and Simple Storage Service .

All services are platform agnostic and can be hosted anywhere. For our particular experimental setup, Redis and S3 were hosted on the Pacific Research Platform [30]. The Internet of Things service with MQTT messaging and device management was coordinated through Amazon Web Services . The dashboard was hosted on a server at UC Santa Cruz. The thresholding spike detection shown in the dashboard runs inside a Docker container, which reads from the Piphys data Redis stream and writes to another Redis stream shown in the dashboard. In our case the Docker, the Redis service and the dashboard run on the Pacific Research Platform . However, this could be transferred to any cloud storage provider . The IoT architecture of these cloud services is explicitly described in [53].Redis, near real-time data stream—Neuronal action potential recording with a high sample rate and multiple channels requires a high throughput pipeline to make near real-time streaming possible. Remote Dictionary Server is a good choice for the implementation of this objective. It is a high-speed cloud-based data structure store that can be used as a cache, message broker, and database. Based on bench marking results, Redis can handle hundreds of thousands of requests per second. The highest data rate for every push from Piphys system to Redis is 7.68 Mb for each second .Pi data stream to Redis requires the network bandwidth to be at least 7.68 Mbps so that uploading to the Dashboard through Redis can be uninterrupted. Internet of Things communication—The dashboard is programmed to be an IoT device that sends Message Queuing Telemetry Transport messages to control and check the Piphys system. In response, the Piphys subscribes to a particular MQTT topic to wait for instructions. The AWS IoT supports the communication of hundreds of devices, making the Piphys system’s extension to a large scale possible in the future. Simple Storage Service —The Simple Storage Service is the final data storage location. S3 is accessible from anywhere at any time on the internet. It supports both management from a terminal session and integration to a custom web browser application. After each experiment, a new identifier will be updated on the dashboard. When a user asks for a specific experiment result, the dashboard can pull the corresponding data file directly from S3 for visualization.Managing the benefits people receive from nature, or ecosystem services, requires a detailed understanding of ecosystem processes. In particular, biodiversity-driven services, such as pest control on farms, requires knowledge of cropping systems, the habitats in and around croplands, and the interactions among the many organisms that inhabit them. Interactions are complex and often change over space and time ; therefore, a critical first step is identifying the species and populations that provide benefits to society . Identifying service providers, however, may not be straightforward. For example, predation is rarely witnessed directly, making it difficult to identify the predators of crop pests. Pest control is a critical service; in the United States, insect predators save farmers billions of dollars annually in avoided pest damage . Several different techniques have been utilized to identify predator–prey interactions. An indirect approach is using stable isotopes to determine trophic positions .

Univariate analysis of variance was used for all data in determining significant differences. For descriptive analysis data, multivariate analysis of variance was used prior to ANOVA to determine the main treatment effect. ANOVA was used for judge, treatment, and replicate effects along with a pseudo mixed model. Fisher’s least significant difference was used for pairwise comparisons of means. Statistical significance was set at 5% for all tests.Analysis of Brix, pH, and TA of the musts showed minimal differences among treatments for each variety . There were no significant differences for all three parameters of the BA must and only the reject treatment for GN had a significantly higher TA; however, this difference was not large. It is possible that this difference could be the result of the inclusion of underripe berries in the must, which have a higher TA. Raisins were also rejected from the sorter, which are high in sugar and could have compensated for the difference in sugar from the less ripe berries. The CS must exhibited the most differences among treatments, which was unexpected considering this variety had the lowest percentage of rejected fruit . The Brix was significantly higher in the sorted treatment compared to the control and reject treatments. This may indicate that the sorter was effective at removing less ripe berries for CS. The pH also differed significantly among treatments for CS; pH was highest in the reject must at 3.8, followed by sort and control at 3.71 and 3.67 respectively. Although the difference in pH between the sort and control was statistically significant, they are very similar with only a 0.04 pH unit difference. Overall, growing blueberries in pots the differences seen in the must chemistry were minimal and likely made little to no difference in the progression of the wines.

It is possible that the reject must composition was made to be more similar to the control and sort treatments due to the addition of juice that accumulated in the vibrating table trays. If this was not done perhaps there would be more differences in must composition when comparing the reject to the sort and control treatments. Wine chemical compositions are shown in Table 5. All wines progressed consistently through fermentation and fermented dry with less than 1 g/L residual sugar. For the most part, wine chemical compositions are similar among treatments for each variety, especially between the sort and control treatments. However, there are some important exceptions. This mostly corresponds to differences in the starting sugar content, although there is a discrepancy as BA reject wines were not significantly lower in Brix. However, Brix was determined after mixing of the must, and especially if a significant number of raisins were present, soak up in the next 24 h could have resulted in sugar increases. The malolactic fermentations for GN and CS wines progressed to completion; however, the control and sort treatments for BA did not finish and were left with close to 1 g/L malic acid for each of the treatments . This is likely due to the high ethanol content in addition to high TA in the wines which can inhibit malolactic bacteria. This would also explain why the reject treatment for BA progressed further in the malolactic fermentation given that these wines were lower in ethanol content and TA. This difference could have important implications for the sensory analysis of BA wines. The volatile acidity for the CS reject treatment was significantly higher than that for the control and sort treatments . The sensory threshold has been reported to be approximately 0.8 g/L for red table wines, therefore, this discrepancy may not have a large impact on sensory analysis.

It was surprising that GN musts/wines showed few significant differences despite having the largest rate of rejection . It is possible that sorting parameters were too aggressive when processing GN, which may have inadvertently led to the rejection of optimal fruit. As previously mentioned, there was significant variation in color for GN fruit . It may also be possible that observed color difference in GN fruit did not correlate well with sugar content. This would mean that optical sorting based on color for GN fruit from this vineyard is potentially less effective than for the other varieties.Differences among treatments were observed in total phenolics, tannin, and anthocyanin content as measured by the Adams-Harbertson assay . In general, the reject wines were higher than control and sort wines in total phenolics and tannin, and lower in anthocyanin. This may be explained by the inclusion of MOG in the reject fermentations which can lead to greater extraction of phenolics. Lower anthocyanin levels wereobserved in the reject wines for all varieties. This is most likely due to the inclusion of green, underripe berries, which contain less anthocyanin.In general, the results from the RP-HPLC analysis of phenolics agree with the results obtained from the Adams-Harbertson assay . Higher levels of most phenolic compounds were observed in the reject treatments. Concentrations of gallic acid and catechin were higher in the reject treatments for all three varieties and dimer B1 was higher in reject wines for BA and CS. Less ripe berries have been shown to contain more of these compounds, which can explain this trend. Higher levels of identified flavan- 3-ols were also observed in the reject treatments of BA and CS wines, which is also in agreement with results found by Obreque-Slier. An interesting trend was found in relation to the proportions of simple hydroxycinnamic acids and their respective tartaric acid esters. All the reject treatments had very low amounts of caftaric and coutaric acid compared to caffeic and p-coumaric acid. It is possible that hydroxycinnamoyl esterase, the enzyme responsible for hydrolyzing the ester linkage, had a greater activity in the reject wines, possibly due to differences in pH . Another possibility is that there could be higher levels of this enzyme in less-ripe fruit. The reject wines for all three varieties were also significantly lower in anthocyanin, which matches results obtained by the Adam-Harbertson assay.

Although reject wines had higher levels of most phenolic compounds, this did not lead to large differences between sorted and control wines. It is likely that not enough material was removed during processing for there to be a significant effect. This may also explain why there were no significant differences in anthocyanin content between sorted and control wines despite reject wines being significantly lower. Perhaps a greater effect would be observed with more aggressive sorting parameters and/or fruit with more variability. Overall, the levels of most phenolic compounds identified were very similar between the sort and control treatments. It can be concluded that optical sorting had little impact on the composition of phenolic compounds between sorted and control wines in all three varieties tested.For CS wines, 37 volatile compounds were identified, 20 of which differed significantly among treatments ; however, only one compound differed significantly between wines made from sorted and control treatments . A Principle Component Analysis biplot plot of significant compounds is presented in Figure 1. It appears the separation is driven primarily by ethyl esters on the left and higher alcohols on the right. Most ethyl esters have higher concentrations in wines made from control and sort treatments . Esters in wine can be formed by an acid catalyzed esterification reaction between an acid and alcohol.Higher amounts of either acid or alcohol can result in increased formation of esters. Wines made from control and sorted treatments had higher ethanol content than wines made from the reject treatment, which would explain this trend. Another important trend is the association of reject treatment wines with a larger concentration of higher alcohols. The suspended solids concentration was significantly higher in reject treatment musts which may explain the difference in the concentration of higher alcohols among the treatments, as previous research has shown that suspended solids during fermentation can lead to greater production of higher alcohols. PCA loading and score plots of volatile analysis for BA wines are given in Figure 2. Thirty-seven compounds were identified, drainage gutter and nine differed significantly among treatments . Again, separation seems to be driven by the proportionally larger presence of higher alcohols in the reject treatments. Like the CS reject musts, the BA reject musts also had significantly higher levels of soluble solids compared to the sort and control treatments . Although most ethyl esters did not differ significantly among treatments for BA, there was a general trend indicating that ethyl ester content was higher in the control and sort treatments . A PCA biplot using all identified ethyl esters and higher alcohols is provided in Figure S1 and there is a clear trend in the separation of these compounds. This agrees with the previous discussion regarding ethyl ester content in the CS wines. The BA control and sort treatments had significantly higher ethanol content compared to the rejects so it is expected that ethyl ester concentration would be higher as well. One exception to this trend is that ethyl lactate was significantly higher in the reject treatment.

The reject wines completed ML fermentation, but the control and sort wines got stuck with almost 1 g/L malic acid . Therefore, ethyl lactate is significantly higher in reject wines because there was more lactic acid present from the conversion of nearly all the malic acid.For GN wines, 32 compounds were identified, nine of which differed significantly among treatments and four differed significantly between sort and control treatments. The same trend was observed for higher alcohols for GN as for the other varieties driving separation in the PCA plot . The concentrations of cis-3-hexen-1-ol, trans-3- hexen-1-ol, and hexanol were all significantly higher in the reject treatments. Again, this is most likely due to higher suspended solids content in the reject treatment musts . The trend with ethyl esters was not observed for GN wines, most likely because all treatments had similar ethanol content . Overall, the results indicate that optical sorting had a minimal effect on the aroma profile for all three varieties, particularly when comparing sort and control treatments.Given the uniformity of chemical results among biological replications, it is fair to assume that the two replications used for descriptive analysis are representative, and the chemical results can therefore be used to discuss sensory trends. MANOVA was performed and revealed a non-significant treatment effect for all three varieties . From this result, it can be concluded that all three treatments for each variety were similar in sensory properties. Despite this result, ANOVA was carried out on individual attributes and some significant differences were found for each variety . For GN, only one attribute out of twenty differed significantly among treatments. It is possible that sensory analysis was done too soon after the wines were bottled and the levels of molecular sulfur dioxide may have been above sensory threshold of about 2 mg/L. Figure 4 gives a PCA biplot with all attributes from the GN descriptive analysis panel. There are no clear trends from the PCA; therefore, it can be concluded from MANOVA, ANOVA, and PCA results that all treatments lead to wines of similar character for GN wines. When ANOVA was performed on data from the BA descriptive analysis panel, three out of twenty-six attributes were found to be significantly different among treatments. “Alcohol hotness” had a significant judge-by-treatment interaction. Results from the pseudo mixed model indicated the interaction effect was more important than the treatment effect. Thus, “alcohol hotness” will not be included in any further discussion of significant attributes for BA wines. The significant difference in malic acid content in the wines among treatments appears to have had little impact on sensory evaluation given that there was no significant difference in the perception of sourness in the wines. From the PCA generated from BA descriptive analysis results , the control and sort wines appear to be correlated more closely with “alcohol” . Wines made from these treatments were higher in ethanol content, which may explain this trend. However, the small number of significant attributes indicate that BA wines made by different treatments were very similar in sensory properties.For the CS descriptive analysis panel, three out of twenty-two attributes were found to be significantly different when ANOVA was performed. A PCA biplot from the CS panel is provided in Figure 6.

The signature raspberry flavor comes from aromatic volatiles, mostly composed of a mixture of ketones and terpenes . α-Ionone and β-ionone are carotenoid-derived aromatic volatiles that are mostly responsible for floral notes in fruit ; these compounds usually intensify as raspberries ripen. Also, α-terpineol, which has a sweet, flowery aroma was found to have a positive correlation with sweetness in our study. Aromatic volatiles become prominent during fruit ripening and tend to increase towards senescence, ultimately developing the aroma and flavor for the fruit . Guichard reported that in raspberries all the terpenes and sesquiterpenes concentrations significantly increased during ripening with an increase in α -ionone followed by a slight increase in β-ionone. In our research, α-ionone concentration increased over time in air and 5 kPa atmosphere storage, but decreased in raspberries stored in 15 kPa atmosphere, perhaps due to slowing of further ripening. α-Terpineol, limonene, linalool and hexanoic acid also decreased 3-4-fold with increasing CO2 concentration in storage. Linalool, α-terpineol, limonene and hexanoic acid showed increases in concentration with time in air storage. In our study, the aromatic volatiles were mostly associated with raspberries stored in lower CO2 atmospheres . This may be largely due to little or no inhibitory effects on further ripening in these atmospheres. Ripening of fruit is usually accompanied by softening and production of flavor and aroma volatiles Some fruity/floral volatiles are known to enhance the perception of sweetness . Volatiles such α-ionone, linalool, square pot and α-terpineol have a sweet floral aroma . This may explain why we observed a positive correlation of sweetness with these particular volatiles in our study.

While raspberries held in higher CO2 atmospheres had lower concentrations of aromatic volatiles, most, but not all, of the differences can be explained by ripening inhibition. High CO2/low O2 atmospheres also restrict enzyme activity, diminishing generation of certain organic volatiles, and reducing the effects of ethylene on CA-stored produce . Off-flavor’s association with low CO2 atmosphere storage may be related to the concentration of limonene which was higher in low CO2 stored raspberries and positively correlated with off-flavor. Elmaci et al. also reported an association of off-flavor with increasing percentage of limonene during storage of mandarins. It is possible that off-flavor was also linked to development of decay or leakiness because the rate of decay and leakiness was higher in fruit stored in low CO2 atmospheres due to the lack of fungistatic conditions or inhibition of metabolism. However, raspberries stored in 8 kPa atmosphere performed better in sensory evaluations in terms of raspberry flavor, juiciness, and sweetness. Raspberries stored in air or 5 kPa atmosphere lost almost all their sensory quality by 10 days. Selection of modified atmospheres for raspberries should be based on the storage time and desired quality. While 15 kPa atmosphere prolonged shelf life the longest, 8 kPa atmosphere prolonged shelf life to 10 days while maintaining sensory quality. Based on these findings, modified atmosphere conditions can be formulated and applied during transportation to further investigate the impacts on quality under commercial conditions. Also, synthesis of volatile compounds and associated gene expression as effected by high CO2 atmospheres would be an interesting area for further exploration.

Grapevine leaf roll-associated viruses are among the most consequential pathogens affecting grapevine and have considerable economic impact . GLRaVs are diverse and belong to the family Closteroviridae, with six species and numerous strains in three genera . Grapevines are often infected with several of these viruses simultaneously . Given their impact and global distribution, efforts to manage the spread of GLRaVs, characterize their effects, and understand the interaction between the vine and GLRaVs have been undertaken. Generally, plant responses to viruses include numerous changes in gene expression, gene regulation, and metabolism . Pathogens and stresses elicit conserved responses from their hosts . Infections with GLRaVs have been associated with poorer fruit quality, lower yield, and leaves that curl, redden, and become brittle. Gene expression studies that implicate regulatory systems in the leaf roll disease phenotype are few in number and have focused on the impact of GLRaV-3, highlighting changes in the expression of senescence-associated and flavonoid bio-synthetic pathway genes . Additional transcriptomic study could help generate novel hypotheses concerning the controls that are fundamental to GLRaV responses . Though common responses might be expected in infected plants given the relatedness of GLRaVs, there is considerable variability in the severity of GLRaV infections. Some GLRaV infections appear without symptoms or are mild , but others cause significant changes in photosynthesis, metabolism, and gas exchange in leaves . Changes in fruit yield, organic and amino acids, titratable acidity, potassium, sugars, and flavonoids are also observed .

These are influenced by host genotype , which virus or combination of viruses is present , and environmental conditions . Leaf reddening, for example, is only observed in red-fruited grapevines . Evidence relating GLRaV responses to rootstock is mixed . In a study of Cabernet Franc vines grafted to different rootstocks, the effect of GLRaV infection on pruning weight depended on rootstock and the largest effects were observed in Kober 5BB-grafted vines . Similarly, fruit yield was influenced by both infection type and rootstock, with Kober 5BB-grafted vines most severely affected by a mixed infection with GLRaV-2, GLRaV-3, and grapevine fleck virus . In another report, Red Globe scion buds infected with a strain of GLRaV-2 were used to inoculate Cabernet Sauvignon plants grafted to 18 different rootstocks; the infection was lethal in plants grafted to several rootstock genotypes, including Kober 5BB . This study used Cabernet Franc grapevines infected with zero, one, or two GLRaVs and grafted to two different rootstocks to identify leaf roll effects in ripening berries that were conserved across experimental conditions, and determine whether or not GLRaV responses could be distinguished in berries from plants grafted to different rootstocks. Grapevines were grown in a single experimental vineyard and evaluated in four consecutive years. Vine growth and several measures of fruit composition were taken in the first two years. Total soluble solids were measured in all four years. RNA sequencing , hormone, and metabolite data were collected from Cabernet Franc berries at four stages during ripening in the third and fourth years. RNA-Seq reads were mapped to the Cabernet Franc genome, which was sequenced in long PacBio reads, assembled using the FALCON-Unzip pipeline, and scaffolded using Hi-C data. The same samples were used to measure the levels of stress and ripening-associated hormones and metabolites. Among these were abscisic acid , jasmonic acid , and salicylic acid . Though many of the GLRaV effects occurred in individual years, a subset of reproducible conserved responses and rootstock differentiating responses were discovered.Cabernet Franc grapevines infected with individual and pairs of GLRaVs and grafted to different rootstocks were studied during grape berry ripening in a dedicated experimental vineyard at the University of California, Davis. Typical grapevine leafroll disease symptoms were observed by mid-ripening . In addition, square plastic planter there was a visible, stark reduction in canopy density and cluster size in GLRaV-1,2 versus GLRaV in vines grafted to Kober 5BB that was not readily apparent in vines grafted to MGT 101-14 with the same infection status . Vine growth, cluster weight, and other measures were collected in 2015 and 2016 . The effect of GLRaV infection on dormant pruning weight, berry weight, pH, and tartaric acid content in 2015 and on moisture content, total anthocyanin content, and titratable acidity in 2016 differed significantly based on the rootstock present . This interaction was significant for malic acid in 2015 and 2016. Significant differences in dormant pruning weight, total cluster weight, and tartaric acid were observed in plants with different GLRaV infection status and rootstock . In contrast, few or no significant differences between GLRaV given the same rootstock were observed for total anthocyanins, moisture content, malic acid content, pH, titratable acidity, weight per berry, or yeast assimilable nitrogen and overwhelmingly in a single year if at all . Overall, GLRaV infection tended to reduce dormant pruning weight and cluster weight. The dormant pruning weights and cluster weights of GLRaV-1,2 was significantly lower than those of GLRaV and other GLRaV ; this was observed for both rootstock genotypes. Significant differences in fruit tartaric acid levels were observed only in 2015 and were between GLRaV-1,3 grafted to different rootstocks and between plants with different GLRaV infection status . In each year except 2015, there was a significant interaction between rootstock and GLRaV infection status in terms of TSS at harvest . This interaction was significant at each other developmental stage in 2017 and at prevéraison in 2018 . Significant differences in TSS at harvest were found between GLRaV and GLRaV in each year except 2017 . Overall, significant reductions in TSS relative to GLRaV were limited to the dual infections and GLRaV-3 . Significant differences were observed between rootstocks in GLRaV 1,2 at every developmental stage, albeit only in 2017 . These data provide limited evidence that different GLRaV infections may or may not affect various aspects of vine growth and fruit composition, some of these differences are rootstock specific, and although some of these effects are observed across years, year-to-year differences may impact whether or not effects Occur.

We used RNA-Seq to sequence the transcriptome of 384 Cabernet Franc berry samples collected from plants grafted to different rootstocks , with different GLRaV infection status, at four developmental stages , and in two consecutive years . Because of the remarkable structural and gene content variability among grape cultivars , we built a genome reference specificallyfor the analysis of these RNA-Seq data. The Cabernet Franc genome was assembled into 504 primary contigs for a total assembly size of 570 Mb. This is comparable to the size of the Zinfandel , Cabernet Sauvignon , Chardonnay , and Pinot Noir PN40024 genomes. In total, 3,085 additional haplotigs were assembled with an N50 of 184 kb . The primary assembly and haplotigs were annotated with 33,563 and 19,146 protein-coding genes, respectively . Ripening was associated with transcriptomically distinct developmental stages. Samples clustered primarily by developmental stage and secondarily by year, though samples at harvest clustered separately . Genes with comparable, significant responses in both years of the study were selected to identify reproducible responses to GLRaVs during ripening. Gene expression in GLRaV was compared to gene expression in GLRaV grafted to the same rootstock at the same developmental stage . In addition, the effects of each GLRaV infection on gene expression at each developmental stage were compared in plants grafted to different rootstocks . On average, 7.1% of the genes differentially expressed between GLRaV and GLRaV were reproduced in both years . This percentage was slightly above average for plants with dual, relatively more severe, infections and below average for individual infections . A subset of 32 genes significantly changed their expression level in two or more GLRaV infection conditions, in both rootstock conditions, and at least one developmental stage . These genes constitute the “conserved” responses to GLRaVs in Cabernet Franc berries during ripening. The majority of these differentially expressed genes are associated with defence, ABA signalling, and cytoskeleton organization and biogenesis . Six of these were genes encoding nucleotide-binding site and leucine-rich repeat-containing proteins; half of these were upregulated. Two F-box genes encoding SNIPER4 were upregulated , as was a gene encoding a hydroxyproline-rich glycoprotein . HRGP and NBS-LRR proteins are associated with pathogen detection . Genes encoding a respiratory burst oxidase protein D , a wall-associated kinase-like protein , and a β-glucosidase 3 were downregulated. RBOHD participates in the production of reactive oxygen species and hypersensitive responses to pathogens . RBOH family proteins are targeted by Snf1-related kinase 2 phosphorylation, a key component of the ABA signalling pathway. Likewise, a WAKL gene in citrus participates in JA and ROS signalling . Among the functions of β-glucosidases are the activation of ABA and SA by freeing them from the conjugates that render them inactive . Several ABA-related genes were among the conserved GLRaV responses, including an upregulated ABC transporter and two downregulated genes, AMP1 and RDA2. AMP1 negatively regulates ABA sensitivity . RDA2 participates in the inhibition of ABA signalling and the promotion of MAPK signalling . Five genes related to cytoskeleton organization were sensitive to GLRaV infection. Only one of these, a myosin VI motor proteincoding gene, was downregulated.

Host plant resistance is the most sustainable option in managing soilborne disease , but like other crops it is believed there is little resistance to southern blight within commercial processing tomato cultivars. However, some resistance is available in the tomato germplasm. The Texas A&M breeding program released several breeding lines that have shown superior resistance to southern blight under field conditions . The mechanism of resistance is associated with the development of secondary tissue on the basal mainstem called the phellem barrier. The six Texas A&M selections 5635M, 5707M, 5719M, 5737M, 5876M, and 5913M were screened for two years in fields infested with A. rolfsii and showed resistance commensurate to a resistant wild accession PI 126432 . Additionally, the six selections showed field resistance to Fusarium oxysporum f. sp. lycopersici W. C. Snyder & H.N. Hansen race 1 including good average plant yields for 5719M and 5876M . The relative susceptibility of commonly grown commercial processing tomato cultivars to southern blight is unknown but would be beneficial for disease management. Grafting is another option for management of soilborne diseases. Disease control by grafting has already shown to be a beneficial alternative to the soil fumigant methyl bromide in Asia and much of Europe . Grafting is a fusion of two plant segments, 25 liter pot the shoot of the plant with desired fruit quality called the ‘scion’ and the root system with desired root traits as the ‘rootstock,’ that functions as a single plant . Grafting is commonly used for perennial crops and has since the early 20th century become a technique for vegetable production in Cucurbitae and Solanaceae species . Grafting to a resistant rootstock has previously been shown to reduce diseases causes by soilborne pathogens and has potential to be a sustainable alternative to fumigants for the control of many soilborne diseases .

In tomatoes, grafting has been used to augment growth under low potassium environments , improve tomato resistance to root-knot-nematodes , and increase tolerance to drought . The main mechanism of disease control by grafted plants is speculated to be by avoidance by having the resistant rootstock come into contact with the pathogen instead of the susceptible scion tissues . Maxifort is an interspecific hybrid of tomato and a wild Solanum species developed as a rootstock for greenhouse tomato . In a study in the southeastern United States, heirloom tomato grafted to the rootstock specific Maxifort exhibited 0 to 5% southern blight incidence whereas incidence in nongrafted plants was 27 to 79% . To our knowledge grafting processing tomatoes to a southern blight-resistant rootstock has not been explored in processing tomatoes in the San Joaquin Valley. Although rootstocks like Maxifort are highly resistant, some plants often develop southern blight symptoms . In our preliminary work, we observed that the graft union was planted below the soil line, possibly rendering the susceptible scion vulnerable to infection by A. rolfsii in the field. To our knowledge, raising the height of the graft union in other crops has yet to be evaluated in processing tomato. The use of resistant rootstock for an annual crop has been studied in fresh-market and heirloom tomatoes for improvement on yield but has yet to be explored for disease resistance for processing tomato in California. The objectives of this study were to: evaluate susceptibility of commercial processing tomato cultivars to southern blight; and evaluate grafting and increased height of the graft union with the resistant rootstock Maxifort for southern blight management in processing tomato.Athelia rolfsii sclerotia were produced in culture media using the oat seed method . The three Athelia rolfsii isolates used were each obtained from a different processing tomato field in Kern County, California in 2017.

Briefly, for each trial the isolates were grown from infested filter paper maintained at – 80ºC, hyphal tipped from mycelium actively growing on potato dextrose agar, and incubated at 25ºC under continuous light for approximately six days. Two plugs from the edge of the purified colonies were inoculated into Erlenmeyer flasks containing oat seeds and 1% water agar that had been autoclaved twice for 60 min on a 24 hr interval. Flasks were then incubated at room temperature for approximately 33 days. The sclerotia grown on oats were moved into sterile 5.7 L plastic containers placed in a biosafety cabinet to dry for approximately 14 days, and sclerotia were separated from oats by pressing the dried oat-sclerotia mixture with a gloved hand over a 2.0 mm and 850 µm sieves. Sclerotia were stored at room temperature in a plastic Ziploc bag until experiment set up. Viability of the inoculum was evaluated by germinating surface disinfested sclerotia on water agar.The susceptibility of 19 commercial processing tomato cultivars to A. rolfsii was evaluated in a greenhouse study in 2018 . In 2019, 19 commercial cultivars and six processing tomato breeding lines from Texas A&M were evaluated. The commercial cultivars were chosen based on highest total yield in California counties affected by southern blight. Treatments consisted of the 19 of these commercial cultivars grown in inoculated soil and a selection of 6 of the 19 commercial cultivars grown in non-inoculated soil as negative controls. The 2018 trial included two hybrid tomato cultivars grown in inoculated soil as positive controls, but were not included in 2019 due to poor germination. The rate of inoculum was 10 sclerotia per 100 cm3 soil based on recommendations by Punja and Rahe . The plants were started from seed using an organic seed starter soil mix in a tray with 200 22 mL, 2.22 cm x 2.22 cm cells. Two seeds were planted per cell.

The trays were placed on a clear plastic-lined chamber in the greenhouse on a warming mat set at 24ºC and misted three times per day for 15 seconds. Emergence began five days post seeding. Eleven days post seeding the trays were moved to an open misting bench where the plants could receive more sunlight, thinned to one plant per cell using sterile metal scissors, and sprinkled with one tablespoon of granular Osmocote Flower and Vegetable fertilizer 14-14-14 per 90 cells on the trays. The Osmocote rate used for germination was recommended by colleagues with tomato germination experience. Three weeks post seeding the plants were transplanted into trays with 36 166 mL, 5.72 cm x 5.08 cm cells to allow for advanced root development. In these larger trays, the soil substrate used was UC Soil Mix III, composed of 50:50 plaster sand:peat moss that was pasteurized at 100ºC for two hours. Inoculation and transplanting occurred five weeks post seeding. The day before inoculation, sclerotia were surface disinfested using 0.5% sodium hypochlorite solution for 1 minute, subsequently rinsed twice in sterile deionized water, and dried with sterile paper towels. The number of sclerotia needed to total 1 g was determined by manually counting, the amount to be added was weighed and incorporated to the top 10.2 cm of soil in 15.2 cm diameter pots to reach the target sclerotia count per 100 cm3 soil. Plants were then transplanted into 15.2 cm , 2.7 L pots with UC Soil Mix III at one plant per pot. Plants were grown in a greenhouse with the temperature set at 33ºC. Temperature data loggers were installed, but in 2018 they malfunctioned. In 2018, 25 liter plant pot the plants were arranged in a randomized complete block design with seven replications across four benches and with six replications across three benches in 2019 oriented east-west, one or two blocks per bench. Blocking was designed to capture potential confounding factors of light, temperature, and watering differences across the different benches. All benches had their own irrigation sub-line connected to a main line. A drip system was installed 15 days post transplanting with one JAIN Twist Weight emitter per pot and was set to water daily for 2 minutes early in the morning. Each plant was fertilized once per week for 3 weeks with 15 mL of a solution containing Jack’s Classic Professional Water Soluble Plant Food 20-20-20 at the recommended rate of 1 tablespoon per gallon of water. The volume of fertilizer was chosen based on observation of adding a volume of liquid that would not leach through the openings of the pots. Four days after the drip system was installed approximately one tablespoon of granular Osmocote Flower and Vegetable fertilizer 14- 14-14 was added around the drip emitter of each pot. The same growing methods from 2018 were used for 2019 with adjustments in using only granular Osmocote Flower and Vegetable fertilizer 14-14-14. The plants were maintained in the greenhouse for 126 days in 2018 and the plants from 2019 were maintained in the greenhouse for 107 days.In 2018, because little disease development was observed in blocks 5 and 6, additional inoculum was added to the inoculated pots in these blocks 77 days after initial inoculum was added. Inoculum for each individual pot was calculated by multiplying the volume of the top four inches of the pots by the rate of inoculum , then divided by the average number of sclerotia from one gram of sclerotia. The sclerotia from all three isolates were evenly mixed. The mixed sclerotia were then weighed to 0.12 g for each individual pot, inoculum per pot were placed in a ziplock bag, then one bag of inoculum was carefully poured around the previously inoculated tomato stem. Plant material for grafting experiments.

The processing tomato cultivars used as scions or non-grafted controls in grafting experiments were Heinz 5608 and Heinz 8504, which are commonly grown in the San Joaquin Valley of California. The hybrid cultivar Maxifort served as the rootstock in grafted treatments. For all greenhouse and field grafting experiments, transplants and grafting were produced by Growers Transplanting Inc. in Salinas, CA using the tube grafting technique with the modification of using a clip that applies minimal pressure on the graft union. Grafting for the high-union grafted treatment consisted of plants with a union approximately 2.54 cm above the standard graft. These high-union grafted plants were produced by stretching the rootstock 2.54 cm to 5.08 cm before the grafting process, applying extra fertilizer to the rootstock, and cutting the rootstock approximately 6.35 cm to 7.62 cm from the plug .Grafting greenhouse experiments. In 2017 a preliminary study was conducted that evaluated two cultivars , two graft treatments , and four inoculum levels in a full factorial treatment arrangement. On June 5, 2017 a single plant was transplanted into each 2733 mL pot with UC Soil Mix III that was inoculated as described above for the cultivar trial and grown in a greenhouse at 32ºC. One-plant pots were arranged in a randomized complete block design with 8 replications across two benches oriented east-west, four blocks per bench. The pots were watered via a drip system beginning 24 days post planting. The plants were fertilized every 2 to 3 weeks with 100 mL of Jack’s Classic Professional Water Soluble Plant Food 20-20-20. The treatment structure was modified based for 2018 and 2019 to include a grafted treatment with a high-union, referred to as ‘tall’. These studies evaluated two cultivars , three graft treatments , and two inoculum levels in a full factorial arrangement . Plants were transplanted into one-plant pots on July 18 in 2018 and April 29 in 2019. Plants were arranged in a randomized complete block design with 6 and 8 replications in 2018 and 2019, respectively, on benches oriented east-west with two or three blocks per bench. The 2018 experiment was conducted in a greenhouse set to 21ºC for 120 days, which was increased to 26ºC for 34 days due to low disease pressure. The 2019 experiment was conducted in a greenhouse set to 35ºC for 83 days. Hobo MX2301 data loggers monitored temperature in the greenhouse and reported the average temperature maximum 38ºC and minimum 15ºC in 2018. In 2018, four days post planting drip irrigation was used to water daily with fertilized water for 21 days before switching to industrial water. After adjusting the drip system, the plants were fertilized once every week then adjusted to fertilizing twice a week with 100 mL solution of Jack’s Classic Professional Water Soluble Plant food. In 2019, approximately one tablespoon of granular Osmocote Flower and Vegetable fertilizer 14-14-14 was added around the drip emitter of each pot. In 2019 additional inoculum was added to the inoculated pots 64 days after transplant to encourage disease development.

Similar results were observed in wines prepared from “Merlot” grapes treated with a racemic mixture of ABA . This treatment resulted in changes in the proportions of anthocyanins, increased total phenol and flavonol content, and increased antioxidant activity . However, it should be considered that application of racemic mixtures of enantiomers may result in a range of plant responses because R-ABA is not found in plants and is less active and less effective than S-ABA. The two enantiomeric forms may have different effects on gene expression and on physiological responses . Anthocyanin accumulation in grape berries during véraison is probably triggered by increased sugar and ABA concentrations in the berry skin, which activate the expression of genes involved in anthocyanin biosynthesis . The activation threshold for genes involved in anthocyanin production was reported to be between 9 and 10◦Bx . S-ABA application at 7 DAV, when anthocyanin biosynthetic genes are normally induced, followed by a second application at 21 DAV, when endogenous ABA concentrations are close to maximal or are beginning to decrease, can upregulate their expression even further or maintain them at a constant level for a longer period of time. These transcription factors are responsive to ABA and are associated with the regulation of the biosynthetic genes CHI, F3H, DFR, LDOX, and UFGT . The transcription factors VvMYBA1 and VvMYBA2 activate anthocyanin biosynthesis in grapevines and are not functional in white grape cultivars . Transcription factors affect the ratio of tri-/dihydroxylated anthocyanins through trans-regulation of flavonoid 3-hydroxylase and flavonoid 30 5 0 -hydroxylase gene expression .

During anthocyanin biosynthesis, F3H is responsible for the hydroxylation of naringenin at position 30 , black plastic planting pots generating dihydrokaempferol, a dihydroflavonol that can be hydrolyzed at position 30 or 50 of the B-ring by the enzymes F30 H or F30 ,50 H, which are responsible for the hydroxylation of the B-ring of flavonoids. F30 H activity promotes accumulationof the cyanidin and peonidin anthocyanin groups, whereas F30 ,50 H activity results in the production of delphinidin and its derivatives petunidin and malvidin. These two enzymes compete in controlling di- and trihydroxylated anthocyanin synthesis . In our study, treatment of hybrid grapes with two applications of 400 mg/L S-ABA primarily favored the accumulation of delphinidin-3-glucoside and malvidin-3-glucoside ; therefore, such treatment decreased the difference between the concentrations of diand trihydroxylated anthocyanins in the grapes. This is consistent with previous results obtained for “Aki Queen” grapes , in which the application of S-ABA stimulated the gene expression of F30 ,50 H relative to F30 H. In addition, the concentrations of petunidin and malvidin increased in the berries, thereby increasing the proportion of trihydroxylated anthocyanins and decreasing the proportions of cyanidin and peonidin anthocyanins relative to the total anthocyanins . In this study, the expression of the main enzymes leading to anthocyanin biosynthesis were analyzed. Future experiments to study changes in expression of F30 H and F30 ,50 H encoding genes are still required to gain a better insight into the impact of exogenous ABA applications on the differential accumulation of specific anthocyanins. Our results indicate that application of S-ABA increased the expression of the UFGT gene and the transcription factors at 28 DAV, but this was not observed for the treatment with only one S-ABA application. Anthocyanin accumulation begins when all genes involved in the biosynthetic pathway are induced, especially UFGT . Anthocyanidins are unstable and are easily degraded to colorless compounds; therefore, before anthocyanins are transported, they must be stabilized by the addition of a glucose residue at position 3 of the C-ring .

The enzyme UFGT catalyzes the final step of anthocyanin biosynthesis, therefore UFGT has been considered by many authors to be a critical enzyme in anthocyanin biosynthesis . Temporary stimulation of gene transcription is believed to be related to a decrease in S-ABA concentration over time. In ‘Crimson Seedless’ grapes, a constant decrease in S-ABA levels with a half-life time of 14.7 days was observed in treated grape berries . The natural decrease in ABA concentration, along with the decrease in S-ABA levels, may, therefore, lead to decreased activity of some genes, depending on the S-ABA concentration in the plant. Expression of the UFGT gene increased considerably 7 days after S-ABA application in ‘Crimson Seedless’ grapes but decreased 3 weeks after treatment, becoming similar to the control . In “Cabernet Sauvignon” grapes treated with ±cis, trans-ABA, expression analysis of anthocyanin biosynthetic genes revealed that the maximum expression levels were only reached 10–17 days after application and that they then rapidly decreased . ABA cis– and trans-isomers differ in the orientation of the carboxyl group at carbon 2. Only the ABA cis-isomer is biologically active, and it accounts for almost all of the ABA produced in plant tissues. However, unlike the S and R enantiomers, the cis– and trans-isomers can be interconverted in plant tissue . Most of the studies on S-ABA involved V. vinifera cultivars were done in temperate zones and testing a single application . In this study, we evaluated the response of a new V. vinifera × V. labrusca hybrid grape cultivar grown in a subtropical area to multiple S-ABA applications. This hybrid often shows lack of color development; therefore, our results confirm the effectiveness of S-ABA to improve the color of ripening berries, even under warm climate conditions. The application of S-ABA to berries of the seedless grape Selection 21 increased the total anthocyanin concentration, changed the proportion of individual anthocyanins, improved their color attributes, and increased the expression of transcription factors and anthocyanin biosynthetic genes.

Two applications of 400 mg/L S-ABA, at 7 and 21 DAV, resulted in the best results in terms of color increment and total anthocyanin concentration, favored the accumulation of trihydroxylated anthocyanins, and increased the expression of transcription factors and of the genes F3H and UFGT. These results not only show that S-ABA is a valuable tool for improving the color of red grapes in warm areas, where color deficiency is frequently observed, but also suggest that S-ABA may be useful in grape breeding programs by permitting the selection and release of new cultivars with natural poor color, but other desirable characteristics such as high yield and resistance to common diseases.Wild birds provide many ecosystem services that are economically, ecologically, and culturally important to humans . One especially important service is suppression of insect populations in agricultural systems . On a global scale, insectivorous birds consume an estimated 400–500 million tons of insects annually and have the capacity to decrease arthropod populations and increase crop yields of both temperate and tropical farms . While these beneficial effects are not always observed , attention has focused on promoting avian diversity and abundance on farms to leverage these benefits . The fact that birds consume agricultural pests does not ensure that they can control them, in the sense of substantially reducing densities of rapidly-growing pests. Here, we evaluate the capacity of birds to suppress agricultural pests, specifically the coffee berry borer, aninvasive pest found in almost every coffee-producing region worldwide. The coffee berry borer is one of the most economically significant pests of coffee worldwide , causing an estimated annual global loss of US $500 million . These small beetles damage coffee crops when a female bores into a coffee cherry and excavates chambers for larvae to grow, consuming the coffee bean. Control of CBB can be accomplished by spraying fungal bio-insecticide Beauvaria bassinia, increasing harvest frequency or continually removing, by hand, over-ripe and fallen cherries, which serve as reservoirs for infestations . The last, and most laborious, control method appears to be the most economically effective In addition to human-mediated control, natural predators such as ants, parasitoid wasps, and nematodes are being explored as potential bio-control agents . Birds have also been identified as a significant biological control agent of CBB . Field experiments in Central America have shown that CBB infestation dramatically decreases when birds are present . For example, Karp et al. reported that bird predation suppresses CBB infestation by 50% and saves farmers US $75– 310/ha per year; another estimate values bird predation at US $584/ha . Suppression is done by both resident foliage-gleaning insectivores, such as rufous-capped warblers , drainage pot and Neotropical migrants like the yellow warbler . Similar to other agriculture systems, avian abundance is higher on farms with heterogenous landscapes in close proximity to native habitat , suggesting low-intensity shade coffee farms are better not only for supporting biodiversity, but also in providing pest mediating ecosystem services . Several lines of evidence support the notion that birds depredate CBB in coffee plantations, and that their effects are biologically significant. Firstly, we know that a variety of bird species consume CBB from assays of avian fecal and regurgitant samples , though the detection rate is quite low . Low detection rates might be due to low consumption rates; detectability of DNA in feces depends on number of CBB eaten, and time since feeding, as well as fecal mass . Secondly, bird and bat exclosure experiments are associated with greater CBB infestation within enclosures . At the same time, it is not clear how birds can effectively suppress CBB at most sites, and throughout the season. Exclosure experiments that report avian suppression appear to be at sites with relatively low CBB infestations , whereas coffee-producing regions with more recent introduction of CBB have infestations of up to 500,000 CBB in a season .

We also do not know whether suppression is effective throughout the reproductive cycle of the CBB, or just when abundances are relatively low. Finally, CBB field traps often capture large numbers of CBB, even in the presence of birds . Consequently, while there is clear evidence that birds consume CBB, the degree to which CBB populations can be suppressed is less clear, particularly because of the species’ population growth potential . Here, we use a CBB population growth model to assess the capacity of birds at naturally occurring densities to reduce CBB populations, as a function of a starting infestation size. We created an age-based population growth model for CBB using data from a life-stage transition matrix published by Mariño et al. . We converted their matrix into a female-only, daily time-step, deterministic Leslie matrix; we could not estimate population growth directly from the original matrix because it did not use a common time step . We incorporated a skewed adult sex ratio to mimic real populations , and added a life-stage for dispersing females, the stage at which CBB are vulnerable to predation by birds. Since the entire CBB lifecycle occurs within the coffee cherry, CBB are vulnerable to predation by birds for a short time window when adult females disperse between plants and burrow into a new cherry . Birds do not eat coffee cherries, with the exception of the Jacu , which is found in southeastern South America. Consequently, we assumed that only adult CBB females are vulnerable to bird predation. With our Leslie matrix, we projected population growth for a closed population during a single CBB breeding season. We projected growth at three levels of initial starting populations of CBB , calculated from published estimates of CBB densities from alcohol lure traps in coffee farms from Colombia, Hawaii and Costa Rica. We then determined the degree to which dispersing female survival rate would have to be decreased to result in a 50% depression in the adult population size at the end of the coffee season at all three infestation levels. Finally, we assessed the plausibility of this degree of CBB suppression by birds as a function of avian energy requirements, reported avian densities on coffee farms, prey composition of avian diets, estimated caloric value of CBB, and the starting population size of CBB females.Coffee phenology is directly related to rainfall patterns that differ among coffee producing regions, leading to distinct seasons, and timing of harvest. Our model assumes environmental conditions of Costa Rica, and thus describe the coffee phenology of this region. In regions of Costa Rica with marked seasonality, coffee flowering is triggered during the dry to wet season transition by the onset of acute precipitation . Areas with relatively consistent rain patterns have more continuous flowering events and a longer harvest season In the Central Valley of Costa Rica, flowering typically begins in March, with three flowering events spread over a month . Flowers are short-lived, lasting only a few days before fruit begin to develop.

The levels of amygdalin and prunasin/sambunigrin were almost equal in Ozone but in Ozark, prunasin/sambunigrin levels were much higher than amygdalin . These concentrations are much higher than the levels found in the present study, as raw blue elderberry juice had a total CNG concentration of only 0.737 µg g-1 . Because CNGs are formed from phenylalanine, it is possible that the blue elderberry had limited stock of this key material to create CNGs. An alternative reason may be that blue elderberry may have less expression of the genes needed to form CNGs like sweet almonds compared to bitter almonds. CNGs may have also been degraded during juice preparation due to native β-glucosidases. A future study should investigate the impact of freezethaw cycles on the activity of β-glucosidase in elderberries because elderberries are frequently frozen before processing because they can spoil quickly if only refrigerated.Two cooking temperatures were investigated to understand the impact of temperature on the degradation rates of the phenolic compounds in blue elderberry juice. The pH and soluble solids were evaluated for the five juice replicates to ensure the juices were similar for the cooking process. The average pH value of the juices was 3.76 ± 0.11 and the average Brix reading was 16.2 ± 1.1%. The major phenolic compounds in elderberry juice were measured via HPLC-DAD and include 5-hydroxyprogallol hexoside , which is a novel phenolic compound tentatively identified for the first time by Uhl et al. 202239 chlorogenic acid, rutin, isorhamnetin-3-O-glucoside, cyn 3-sam, and cyn 3-glu. Whereas levels of cyn 3-sam and cyn 3-glu decreased to 82.2 ± 6.9 % and 79.3 ± 6.3 %, respectively , drainage planter pot more than 98% of the original concentration of 5-HPG, rutin, isorhamnetin-3-O-glucoside and chlorogenic acid remained after two hours.

At the higher cooking temperature , the anthocyanins again experienced significant degradation, retaining only 33.2 ± 4.6 % and 36.8 ± 5.5 % of the original concentration after cooking two hours . In a separate study of the thermal stability of elderberry juice, 15% of cyn 3-sam and cyn 3-glu were retained in juice as compared to control juice.1 Szalóki-Dorkó, et al. demonstrated that the more complexly glycosylated anthocyanins cyn 3-sam is more stable during thermal process as compared to cyn 3-glu. The results of our study are similar to Oancea et al. which showed after 90 min at 100 °C, total anthocyanin content degraded 58 %.58 However, that study also observed an increase in total phenolic and total flavonoid content after 60 min, followed by a gradual decrease, which was not observed herein. If sample vials were sealed well to protect from any loss of moisture, this increase in concentrations may be due to the release of phenolic compounds bound to the cell well or other polysaccharides, which can be released with the assistance of pectinase treatments. Because elderberry has predominantly cyanidin-based anthocyanins, protocatechuic acid is typically found as the main degradation product, though phloroglucinaldehyde can also be formed. However, neither protocatechuic acid nor phloroglucinaldehyde were observed in any of the cooked juice samples. Protocatechuic acid dihexoside, which was tentatively identified in an earlier study of blue elderberry did not increase over the cooking period. Caffeic acid, a hydroxycinnamic acid increased up to 108.1% of its initial concentration after 2 hours of cooking at 72 °C, and up to 147.1% after 2 hours of cooking at 95 °C. The levelsof caffeic acid were highly variable, with larger standard deviations that the other phenolic compounds. This is a known metabolite of cyanidin-based anthocyanins,and further work investigating the breakdown of anthocyanins in blue elderberry juice into this phenolic acid can elucidate the pathway to this compound.

The main flavonols in blue elderberry, rutin and isorhamnetin glucoside, were stable during the thermal processing, retaining 100.5% and 99.3%, respectively, of their original concentration even at 95 °C . The high retention rates of rutin and isorhamnetin glucoside match literature reports for the thermal stability of these compounds, which show that rutin has a strong thermal stability at acidic pH. More than 80% of the starting concentration was retained after five hours of cooking at 100 °C at pH 5. Our results do not agree with another study in which rutin had an activation energy 107.3 kJ/mol, and the half-life values at 70 and 90 °C were 19.25 and 1.99 h, respectively; however, the rutin was in an aqueous solution at pH 6.6. Other compounds present in blue elderberry juice, in addition to a lower pH, could cause synergistic effects to improve stability of rutin in the present study. Limited information on the thermal stability of isorhamnetin glucoside was found, though a study of black currant juice stability found that during long-term storage at room temperature and at 4 °C, isorhamnetin glucoside concentrations did not change significantly during the 12-month period. In the same study, rutin did not change significantly during storage. The main phenolic acid in blue elderberry juice, chlorogenic acid, was also thermally stable. This result was unexpected, as another study on the thermal stability of chlorogenic acid in a complex with amylose showed a significant decrease in content after 10-15 minutes, depending on the temperature. Their results also showed that a 10 °C increase in temperature results in a 2.5-fold increase in the rate of degradation of chlorogenic acid. It can be beneficial to maintainlevels of chlorogenic acid in anthocyanin-rich matrices, as shown in black carrot extract where chlorogenic acid increased absorbance of cyanidin-based anthocyanins at pH 3.6 and 4.6 due to intermolecular co-pigmentation. 

Overall, our results show that blue elderberry juice behaves similarly to anthocyanin-rich matrices, in that longer processing at higher temperatures degrades anthocyanins. The two main anthocyanins in blue elderberry, cyn 3-sam and cyn 3-glu, behaves similarly during processing, degrading at about the same rate at 72 °C and 95 °C. Furthermore, the other major phenolic compounds like rutin, isorhamnetin, and chlorogenic acid, were highly stable and can withstand the thermal processing. Our study into the effects of thermal processing on the phenolic composition and cyanogenic glycoside content in blue elderberry juice showed that the main anthocyanins present degrade faster at higher temperatures but other important phenolic compounds like rutin and isorhamnetin 3-glucoside are more thermally stable, retaining over 90% of their original concentrations even after two hours at 95 °C. Furthermore, neoamygdalin and sambunigrin were measured in the blue elderberry juice, which were in lower concentrations compared to European and American elderberry.The Berry phase has played significant roles in many aspects of physics, ranging from atoms to molecules to condensed-matter systems. As pointed out in Ref., the Berry phase has a profound geometrical origin because an adiabatic and cyclic process of a quantum state is mathematically equivalent to parallel transporting it along a loop, which connects to the concept of holonomy in geometry. Hence, the Berry phase bridges physics and geometry, making it extremely important in the understanding of topological phenomena, such as integer quantum Hall effect, topological insulators and superconductors, and others. The description of the Berry phase relies on the properties of a pure state of a quantum systems at zero temperature. Meanwhile, mixed quantum states, including thermal state at finite temperatures, are more common. Therefore, mixed-state generalizations of the Berry phase have been an important task. Uhlmann made a breakthrough by constructing the Uhlmann connection for exploring the topology of finite-temperature systems. As the Berry holonomy arises from paralleltransport of a state-vector along a closed path, the Uhlmann holonomy is generated by parallel-transporting the amplitude of a density matrix. defined by W = √ρU. Here the amplitude W is the mixed-state counterpart of the wave function, and U is a phase factor. A geometrical phase is deduced from the initial and final amplitudes. However, Uhlmann’s definition of parallel transport is rather abstract and may involve nonunitary processes, complicating a direct and clear physical interpretation. Moreover, plant pot with drainage the fiber bundle built upon Uhlmann’s formalism is trivial, which severely restricts its applications in physical systems.Purification of a mixed state leads to purified state, a state-vector equivalent to the amplitude of a density matrix. The lack of a one-to-one correspondence between the density matrix and its purified states gives rise to a phase factor, similar to the phase of a wave function. In a branch of quantum field theory called thermal field theory, there is a similar structure for describing the thermal-equilibrium state of a system by constructing the corresponding thermal vacuum by duplicating the system state as an ancilla and forming a composite state. It plays a crucial role in the formalism of traversable wormholes induced by the holographic correspondence between a quantum field theory and a gravitational theory of one higher dimensions. Importantly, purified states of a two level system has been demonstrated on the IBM quantum computer while the thermal vacuum of a transverse field Ising model in its approximate form has been realized on a trapped-ion quantum computer. Despite the superficial similarity, a major difference between a thermal vacuum and a purified state is a partial transposition of the ancilla to ensure the Hilbert-Schmidt product is well defined.

In quantum information theory, a partial transposition is closely related to entanglement of mixed states. Importantly, partial transpositions of composite systems have been approximately realized in experiments by utilizing structural physical approximations in suitable quantum computing platforms. Although ordinary observables cannot discern the partial transposition between the purified state and thermal vacuum, here we will show that at least two types of generalizations of the Berry phase to mixed states are capable of differentiating the two representations of finite temperature systems. Among many attempts to generalize the Berry phase or related geometric concepts to mixed states, a frequently mentioned approach was proposed in Ref. Instead of decomposing the density matrix to obtain a matrix-valued phase factor, a geometrical phase is di-rectly assigned to a mixed state after parallel transport by an analogue of the optical process of the MachZehnder interferometer. Hence, the geometrical phase generated in this way is often referred to as the interferometric phase. The interferometric phase has been generalized to nonunitary processes, but the transformations are still on the system only. Moreover, it is essentially different from Uhlmann’s theory since the conceptual structure of holonomy is not incorporated. We will first derive a mixed-state generalization of the parallel-transport condition for generalizing the Berry phase without invoking holonomy. This approach unifies the necessary condition for both the interferometric phase and Uhlmann phase . Two ways to implement the parallel-transport condition based on how the system of interest undergoes adiabatic evolution will be introduced, and they lead to different generalizations of the Berry phase. We will name one thermal Berry phase and the other generalized Berry phase. Importantly, the partial transposition of the ancilla between a purified state and thermal vacuum will be shown to produces observable geometrical effects in both thermal Berry phase and generalized Berry phase. Through explicit examples, the two generalized phases are shown to differentiate the two finite-temperature representations, a task beyond the capability of the conventional interferometric phase or Uhlmann phase. The rest of the paper is organized as follows. Sec. II summarizes the Berry phase in a geometrical framework with an introduction of the parallel-transport condition for pure quantum states. In Sec. III, we review the representations of mixed states via purified states and thermal vacua and then explain the difference of the partial transposition of the ancilla. In Sec. IV, we introduce the thermal Berry phase via generalized adiabatic processes. While the thermal Berry phase can differentiate a purified state from a thermal vacuum, it may contain non-geometrical contributions. In Sec. V, we generalize the parallel-transport condition to involve the system and ancilla and derive the general Berry phase according to the generalized condition. While the generalized Berry phase only carries geometrical information, its ability of differentiating a purified state from a thermal vacuum depends on the setup and protocol. We present examples of the thermal and generalized Berry phases. Sec. VI concludes our study. Some details and derivations are given in the Appendix.While purified states of a two-level system incorporating environmental effects have been simulated on the IBM quantum platform, thermal vacua of the transverse Ising model has been experimentally realized on an ion-trap quantum computer by the quantum approximate optimization algorithm. Moreover, partial transposition of a composite system has been approximately realized on quantum computers with various numbers of qubits.