Academic literature on the topic 'Crop Phenotyping'
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Journal articles on the topic "Crop Phenotyping"
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Wang, Ya-Hong, and Wen-Hao Su. "Convolutional Neural Networks in Computer Vision for Grain Crop Phenotyping: A Review." Agronomy 12, no. 11 (October 27, 2022): 2659. http://dx.doi.org/10.3390/agronomy12112659.
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Computer vision (CV) combined with a deep convolutional neural network (CNN) has emerged as a reliable analytical method to effectively characterize and quantify high-throughput phenotyping of different grain crops, including rice, wheat, corn, and soybean. In addition to the ability to rapidly obtain information on plant organs and abiotic stresses, and the ability to segment crops from weeds, such techniques have been used to detect pests and plant diseases and to identify grain varieties. The development of corresponding imaging systems to assess the phenotypic parameters, yield, and quality of crop plants will increase the confidence of stakeholders in grain crop cultivation, thereby bringing technical and economic benefits to advanced agriculture. Therefore, this paper provides a comprehensive review of CNNs in computer vision for grain crop phenotyping. It is meaningful to provide a review as a roadmap for future research in such a thriving research area. The CNN models (e.g., VGG, YOLO, and Faster R-CNN) used CV tasks including image classification, object detection, semantic segmentation, and instance segmentation, and the main results of recent studies on crop phenotype detection are discussed and summarized. Additionally, the challenges and future trends of the phenotyping techniques in grain crops are presented.
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Nguyen, Giao N., and Sally L. Norton. "Genebank Phenomics: A Strategic Approach to Enhance Value and Utilization of Crop Germplasm." Plants 9, no. 7 (June 29, 2020): 817. http://dx.doi.org/10.3390/plants9070817.
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Genetically diverse plant germplasm stored in ex-situ genebanks are excellent resources for breeding new high yielding and sustainable crop varieties to ensure future food security. Novel alleles have been discovered through routine genebank activities such as seed regeneration and characterization, with subsequent utilization providing significant genetic gains and improvements for the selection of favorable traits, including yield, biotic, and abiotic resistance. Although some genebanks have implemented cost-effective genotyping technologies through advances in DNA technology, the adoption of modern phenotyping is lagging. The introduction of advanced phenotyping technologies in recent decades has provided genebank scientists with time and cost-effective screening tools to obtain valuable phenotypic data for more traits on large germplasm collections during routine activities. The utilization of these phenotyping tools, coupled with high-throughput genotyping, will accelerate the use of genetic resources and fast-track the development of more resilient food crops for the future. In this review, we highlight current digital phenotyping methods that can capture traits during annual seed regeneration to enrich genebank phenotypic datasets. Next, we describe strategies for the collection and use of phenotypic data of specific traits for downstream research using high-throughput phenotyping technology. Finally, we examine the challenges and future perspectives of genebank phenomics.
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Yuan, Huali, Yiming Liu, Minghan Song, Yan Zhu, Weixing Cao, Xiaoping Jiang, and Jun Ni. "Design of the Mechanical Structure of a Field-Based Crop Phenotyping Platform and Tests of the Platform." Agronomy 12, no. 9 (September 11, 2022): 2162. http://dx.doi.org/10.3390/agronomy12092162.
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The field mobile platform is an important tool for high-throughput phenotype monitoring. To overcome problems in existing field-based crop phenotyping platforms, including limited application scope and low stability, a rolling adjustment method for the wheel tread was proposed. A self-propelled three-wheeled field-based crop phenotyping platform with variable wheel tread and height above ground was developed, which enabled phenotypic information of different dry crops in different development stages. A three-dimensional model of the platform was established using Pro/E; ANSYS and ADAMS were used for static and dynamic performance. Results show that when running on flat ground, the platform has a vibration acceleration lower than 0.5 m/s2. When climbing over an obstacle with a height of 100 mm, the vibration amplitude of the platform is 88.7 mm. The climbing angle is not less than 15°. Field tests imply that the normalized difference vegetation index (NDVI) and the ratio vegetation index (RVI) of a canopy measured using crop growth sensors mounted on the above platform show favorable linear correlations with those measured using a handheld analytical spectral device (ASD). Their R2 values are 0.6052 and 0.6093 and root-mean-square errors (RMSEs) are 0.0487 and 0.1521, respectively. The field-based crop phenotyping platform provides a carrier for high-throughput acquisition of crop phenotypic information.
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Anchekov, M. I. "High throughput crop phenotyping systems." News of the Kabardin-Balkar Scientific Center of RAS 5, no. 109 (2022): 19–24. http://dx.doi.org/10.35330/1991-6639-2022-5-109-19-24.
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Jin, Xiuliang, Wanneng Yang, John H. Doonan, and Clement Atzberger. "Crop phenotyping studies with application to crop monitoring." Crop Journal 10, no. 5 (October 2022): 1221–23. http://dx.doi.org/10.1016/j.cj.2022.09.001.
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Stanschewski, Clara S., Elodie Rey, Gabriele Fiene, Evan B. Craine, Gordon Wellman, Vanessa J. Melino, Dilan S. R. Patiranage, et al. "Quinoa Phenotyping Methodologies: An International Consensus." Plants 10, no. 9 (August 24, 2021): 1759. http://dx.doi.org/10.3390/plants10091759.
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Quinoa is a crop originating in the Andes but grown more widely and with the genetic potential for significant further expansion. Due to the phenotypic plasticity of quinoa, varieties need to be assessed across years and multiple locations. To improve comparability among field trials across the globe and to facilitate collaborations, components of the trials need to be kept consistent, including the type and methods of data collected. Here, an internationally open-access framework for phenotyping a wide range of quinoa features is proposed to facilitate the systematic agronomic, physiological and genetic characterization of quinoa for crop adaptation and improvement. Mature plant phenotyping is a central aspect of this paper, including detailed descriptions and the provision of phenotyping cards to facilitate consistency in data collection. High-throughput methods for multi-temporal phenotyping based on remote sensing technologies are described. Tools for higher-throughput post-harvest phenotyping of seeds are presented. A guideline for approaching quinoa field trials including the collection of environmental data and designing layouts with statistical robustness is suggested. To move towards developing resources for quinoa in line with major cereal crops, a database was created. The Quinoa Germinate Platform will serve as a central repository of data for quinoa researchers globally.
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Nobuhara, Hajime. "Aerial Imaging for Field Crop Phenotyping." Journal of the Robotics Society of Japan 34, no. 2 (2016): 123–26. http://dx.doi.org/10.7210/jrsj.34.123.
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Xu, Rui, and Changying Li. "A Review of High-Throughput Field Phenotyping Systems: Focusing on Ground Robots." Plant Phenomics 2022 (June 17, 2022): 1–20. http://dx.doi.org/10.34133/2022/9760269.
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Manual assessments of plant phenotypes in the field can be labor-intensive and inefficient. The high-throughput field phenotyping systems and in particular robotic systems play an important role to automate data collection and to measure novel and fine-scale phenotypic traits that were previously unattainable by humans. The main goal of this paper is to review the state-of-the-art of high-throughput field phenotyping systems with a focus on autonomous ground robotic systems. This paper first provides a brief review of nonautonomous ground phenotyping systems including tractors, manually pushed or motorized carts, gantries, and cable-driven systems. Then, a detailed review of autonomous ground phenotyping robots is provided with regard to the robot’s main components, including mobile platforms, sensors, manipulators, computing units, and software. It also reviews the navigation algorithms and simulation tools developed for phenotyping robots and the applications of phenotyping robots in measuring plant phenotypic traits and collecting phenotyping datasets. At the end of the review, this paper discusses current major challenges and future research directions.
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Watt, Michelle, Fabio Fiorani, Björn Usadel, Uwe Rascher, Onno Muller, and Ulrich Schurr. "Phenotyping: New Windows into the Plant for Breeders." Annual Review of Plant Biology 71, no. 1 (April 29, 2020): 689–712. http://dx.doi.org/10.1146/annurev-arplant-042916-041124.
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Plant phenotyping enables noninvasive quantification of plant structure and function and interactions with environments. High-capacity phenotyping reaches hitherto inaccessible phenotypic characteristics. Diverse, challenging, and valuable applications of phenotyping have originated among scientists, prebreeders, and breeders as they study the phenotypic diversity of genetic resources and apply increasingly complex traits to crop improvement. Noninvasive technologies are used to analyze experimental and breeding populations. We cover the most recent research in controlled-environment and field phenotyping for seed, shoot, and root traits. Select field phenotyping technologies have become state of the art and show promise for speeding up the breeding process in early generations. We highlight the technologies behind the rapid advances in proximal and remote sensing of plants in fields. We conclude by discussing the new disciplines working with the phenotyping community: data science, to address the challenge of generating FAIR (findable, accessible, interoperable, and reusable) data, and robotics, to apply phenotyping directly on farms.
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Ilakiya, T., E. Parameswari, V. Davamani, Dumpala Swetha, and E. Prakash. "High-throughput crop phenotyping in vegetable crops." Pharma Innovation 9, no. 8 (August 1, 2020): 184–91. http://dx.doi.org/10.22271/tpi.2020.v9.i8c.5035.
Full textDissertations / Theses on the topic "Crop Phenotyping"
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Wang, Huan. "Crop assessment and monitoring using optical sensors." Diss., Kansas State University, 2017. http://hdl.handle.net/2097/38224.
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Doctor of PhilosophyDepartment of Agronomy
V. P. Vara Prasad
Crop assessment and monitoring is important to crop management both at crop production level and research plot level, such as high-throughput phenotyping in breeding programs. Optical sensors based agricultural applications have been around for decades and have soared over the past ten years because of the potential of some new technologies to be low-cost, accessible, and high resolution for crop remote sensing which can help to improve crop management to maintain producers’ income and diminish environmental degradation. The overall objective of this study was to develop methods and compare the different optical sensors in crop assessment and monitoring at different scales and perspectives. At crop production level, we reviewed the current status of different optical sensors used in precision crop production including satellite-based, manned aerial vehicle (MAV)-based, unmanned aircraft system (UAS)-based, and vehicle-based active or passive optical sensors. These types of sensors were compared thoroughly on their specification, data collection efficiency, data availability, applications and limitation, economics, and adoption. At research plot level, four winter wheat experiments were conducted to compare three optical sensors (a Canon T4i® modified color infrared (CIR) camera, a MicaSense RedEdge® multispectral imager and a Holland Scientific® RapidScan CS-45® hand-held active optical sensor (AOS)) based high-throughput phenotyping for in-season biomass estimation, canopy estimation, and grain yield prediction in winter wheat across eleven Feekes stages from 3 through 11.3. The results showed that the vegetation indices (VIs) derived from the Canon T4i CIR camera and the RedEdge multispectral camera were highly correlated and can equally estimate winter wheat in-season biomass between Feekes 3 and 11.1 with the optimum point at booting stage and can predict grain yield as early as Feekes 7. Compared to passive sensors, the RapidScan AOS was less powerful and less temporally stable for biomass estimation and yield prediction. Precise canopy height maps were generated from a CMOS sensor camera and a multispectral imager although the accuracy could still be improved. Besides, an image processing workflow and a radiometric calibration method were developed for UAS based imagery data as bi-products in this project. At temporal dimension, a wheat phenology model based on weather data and field contextual information was developed to predict the starting date of three key growth stages (Feekes 4, 7, and 9), which are critical for N management. The model could be applied to new data within the state of Kansas to optimize the date for optical sensor (such as UAS) data collection and save random or unnecessary field trips. Sensor data collected at these stages could then be plugged into pre-built biomass estimation models (mentioned in the last paragraph) to estimate the productivity variability within 20% relative error.
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Crain, Jared Levi. "Leveraging the genomics revolution with high-throughput phenotyping for crop improvement of abiotic stresses." Diss., Kansas State University, 2016. http://hdl.handle.net/2097/32566.
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Doctor of PhilosophyGenetics Interdepartmental Program - Plant Pathology
Jesse A. Poland
A major challenge for 21st century plant geneticists is to predict plant performance based on genetic information. This is a daunting challenge, especially when there are thousands of genes that control complex traits as well as the extreme variation that results from the environment where plants are grown. Rapid advances in technology are assisting in overcoming the obstacle of connecting the genotype to phenotype. Next generation sequencing has provided a wealth of genomic information resulting in numerous completely sequenced genomes and the ability to quickly genotype thousands of individuals. The ability to pair the dense genotypic data with phenotypic data, the observed plant performance, will culminate in successfully predicting cultivar performance. While genomics has advanced rapidly, phenomics, the science and ability to measure plant phenotypes, has slowly progressed, resulting in an imbalance of genotypic to phenotypic data. The disproportion of high-throughput phenotyping (HTP) data is a bottleneck to many genetic and association mapping studies as well as genomic selection (GS). To alleviate the phenomics bottleneck, an affordable and portable phenotyping platform, Phenocart, was developed and evaluated. The Phenocart was capable of taking multiple types of georeferenced measurements including normalized difference vegetation index and canopy temperature, throughout the growing season. The Phenocart performed as well as existing manual measurements while increasing the amount of data exponentially. The deluge of phenotypic data offered opportunities to evaluate lines at specific time points, as well as combining data throughout the season to assess for genotypic differences. Finally in an effort to predict crop performance, the phenotypic data was used in GS models. The models combined molecular marker data from genotyping-by-sequencing with high-throughput phenotyping for plant phenotypic characterization. Utilizing HTP data, rather than just the often measured yield, increased the accuracy of GS models. Achieving the goal of connecting genotype to phenotype has direct impact on plant breeding by allowing selection of higher yielding crops as well as selecting crops that are adapted to local environments. This will allow for a faster rate of improvement in crops, which is imperative to meet the growing global population demand for plant products.
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Thomas, C. L. "High throughput phenotyping of root and shoot traits in Brassica to identify novel genetic loci for improved crop nutrition." Thesis, University of Nottingham, 2017. http://eprints.nottingham.ac.uk/43440/.
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Despite the success of breeding for high-yielding varieties during and since the ‘Green Revolution’, there are still an ever increasing number of people who suffer from malnutrition, due to both inadequate calorie intake and ‘hidden hunger’ from insufficient essential nutrients. There are also adverse impacts of such high-input, intensive agriculture on the wider environment. It is necessary therefore to focus breeding efforts on improving nutrient uptake and composition of crops, as well as improved yield. Roots have been an under-utilised focus of crop breeding, because of difficulty in observation and accurate measurement. Furthermore, genetic diversity in crop roots may have been lost in commercial varieties because of the focus on above-ground traits and the use of fertilisers. Techniques which can accurately measure phenotypic variation in roots, of a diverse range of germplasm at a high throughput, would increase the potential for identifying novel genetic loci related to improved nutrient uptake and composition. The aim of this PhD was to screen at high throughput in a controlled-environment, the roots of an array of Brassica napus germplasm. The validity of the system to predict field performance, in traits including early vigour, nutrient composition and yield was assessed. Genetic loci underlying variation for the root traits were also investigated. A high throughput screen of the mineral composition of a mutagenised B. rapa population was also conducted, with the aim of identifying mutants with enhanced mineral composition of human essential elements, particularly magnesium. It has been demonstrated that root traits in the high throughput system can predict field performance, particularly primary root length which has the greatest ‘broad-sense heritability’ and relates to early vigour and yield. Lateral root density on the otherhand was found across the studies to relate to mineral composition, particularly of micro-nutrients. Genetic loci underlying root traits, and enhanced magnesium accumulation have been identified, and have potential for use in breeding Brassica with improved mineral nutrition.
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McNulty, Sarah Kristine. "Accelerated Crop Domestication through Identification of Phenotypic Characteristics of Taraxacum kok-saghyz Relevant to Rubber Yield." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1574766469110561.
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Campbell, Lesley G. "Rapid evolution in a crop-weed complex (Raphanus spp.)." The Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=osu1166549627.
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Agostinelli, Andres Mateo. "PHENOTYPIC AND GENOTYPIC SELECTION FOR HEAD SCAB RESISTANCE IN WHEAT." UKnowledge, 2009. http://uknowledge.uky.edu/gradschool_theses/582.
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Fusarium Head Blight (FHB) is a destructive disease caused by Fusarium graminearum that affects wheat (Triticum aestivum L.) worldwide. Breeding for resistance to FHB is arguably the best way to combat this disease. However, FHB resistance is highly complex and phenotypic screening is difficult. Molecular markers are a promising tool but breeding programs face the challenge of allocating resources in such a way that the optimum balance between phenotypic and genotypic selection is reached.
An F2:3 population derived from a resistant x susceptible cross was subjected to phenotypic and genotypic selection. For phenotyping, a novel air separation method was used to measure percentage of damaged kernels (FDK). Heritability estimates were remarkably high, which was attributed to the type of cross and the quality of phenotyping. Genotypic selection was done by selecting resistance alleles at quantitative trait loci (QTL) on the 3BS (Fhb1) and the 2DL chromosomes. Fhb1 conferred a moderate but stable FHB resistance while the 2DL QTL conferred a surprisingly high level of resistance but with significant interaction with the environment. Phenotypic selection conferred higher or lower genetic gains than genotypic selection, depending on the selection intensity. Based on these results, different selection strategies are discussed.
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Vergara, Díaz Omar. "High-throughput field phenotyping in cereals and implications in plant ecophysiology." Doctoral thesis, Universitat de Barcelona, 2019. http://hdl.handle.net/10803/668314.
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Global climate change effects on agroecosystems together with increasing world population is already threatening food security and endangering ecosystem stability. Meet global food demand with crops production under climate change scenario is the core challenge in plant research nowadays. Thus, there is an urgent need to better understand the underpinning mechanisms of plant acclimation to stress conditions contributing to obtain resilient crops. Also, it is essential to develop new methods in plant research that permit to better characterize non-destructively plant traits of interest. In this sense, the advance in plant phenotyping research by high throughput systems is key to overcome these challenges, while its verification in the field may clear doubts on its feasibility. To this aim, this thesis focused on wheat and secondarily on maize as study species as they make up the major staple crops worldwide. A large panoply of phenotyping methods was employed in these works, ranging from RGB and hyperspectral sensing to metabolomic characterization, besides of other more conventional traits. All research was performed with trials grown in the field and diverse stressor conditions representative of major constrains for plant growth and production were studied: water stress, nitrogen deficiency and disease stress. Our results demonstrated the great potential of leave-to-canopy color traits captured by RGB sensors for in-field phenotyping, as they were accurate and robust indicators of grain yield in wheat and maize under disease and nitrogen deficiency conditions and of leaf nitrogen concentration in maize. On the other hand, the characterization of the metabolome of wheat tissues contributed to elucidate the metabolic mechanisms triggered by water stress and their relationship with high yielding performance, providing some potential biomarkers for higher yields and stress adaptation. Spectroscopic studies in wheat highlighted that leaf dorsoventrality may affect more than water stress on the reflected spectrum and consequently the performance of the multispectral/hyperspectral approaches to assess yield or any other relevant phenotypic trait. Anatomy, pigments and water changes were responsible of reflectance differences and the existence of leaf-side-specific responses were discussed. Finally, the use of spectroscopy for the estimation of the metabolite profiles of wheat organs showed promising for many metabolites which could pave the way for a new generation phenotyping. We concluded that future phenotyping may benefit from these findings in both the low-cost and straightforward methods and the more complex and frontier technologies.Els efectes del canvi climàtic sobre els agro-ecosistemes i l’increment de la població mundial posa en risc la seguretat alimentària i l’estabilitat dels ecosistemes. Actualment, satisfer les demandes de producció d’aliments sota l’escenari del canvi climàtic és el repte central a la Biologia Vegetal. Per això, és indispensable entendre els mecanismes subjacents de l’aclimatació a l’estrès que permeten obtenir cultius resilients. També és precís desenvolupar nou mètodes de recerca que permetin caracteritzar de manera no destructiva els trets d’interès. L’avenç del fenotipat vegetal amb sistemes d’alt rendiment és clau per abordar aquests reptes. La present tesi s’enfoca en el blat i secundàriament en el panís com a espècies d’estudi ja que constitueixen els cultius bàsics arreu del món. Un ampli ventall de mètodes de fenotipat s’han utilitzat, des sensors RGB a híper-espectrals fins a la caracterització metabolòmica. La recerca s’ha dut a terme en assajos de camp i s’han avaluat diversos tipus d’estrès representatius de les majors limitacions pel creixement i producció vegetal: estrès hídric i biòtic i deficiència de nitrogen. Els resultats demostraren el gran potencial dels trets del color RGB (des de la planta a la capçada) pel fenotipat de camp, ja que foren indicadors precisos del rendiment a blat i panís sota condicions de malaltia i deficiència de nitrogen i de la concentració de nitrogen foliar a panís. La caracterització metabolòmica de teixits de blat contribuí a esbrinar els processos metabòlics endegats per l’estrès hídric i la seva relació amb comportament genotípic, proporcionant bio-marcadors potencials per rendiments més alts i l’adaptació a l’estrès. Estudis espectroscòpics en blat van demostrar que la dorsoventralitat pot afectar més que l’estrès hídric sobre l’espectre de reflectància i consegüentment sobre el comportament de les aproximacions multi/híper-espectrals per avaluar el rendiment i d’altres trets fenotípics com anatòmics i contingut de pigments. Finalment, l’ús de l’espectroscòpia per l’estimació del contingut metabòlic als teixits de blat resulta prometedor per molts metabòlits, la qual cosa obre les portes per a un fenotipat de nova generació. El fenotipat pot beneficiar-se d’aquestes troballes, tant en els mètodes de baix cost com de les tecnologies més sofisticades i d’avantguarda.
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Hasing, Rodriguez Tomas Nestor. "Genomic Reconstruction of the Domestication History of Sinningia speciosa (Lodd.) Hiern, and the Development of a Novel Genotyping Approach." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/95510.
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Most staple food crops were domesticated thousands of years ago through independent processes across different regions of the world. Studies of the history of such crops have been essential to our understanding of plant domestication as a process that started with the collection of wild material and continued with subsequent propagation, cultivation, and selection under human care. Domestication often involves a complex genetic structure with contributions from multiple founder populations, interspecific hybridization, chromosomal introgressions, and polyploidization events that occurred hundreds to thousands of years earlier. Such intricate origins complicate the systematic study of the sources of phenotypic variation.
The analysis of recently domesticated, non-traditional, non-model species, such as Sinningia speciosa (Gesneriaceae), can expand the knowledge that we have on phenotypic variation under domestication, and help us to comprehend modern patterns of plant domestication and to broaden our understanding of the general trends. S. speciosa is commonly known as the 'florist's gloxinia', and it has been cultivated for 200 years as an ornamental houseplant. In our genomic study of S. speciosa, we examined an extensive diversity panel consisting of 115 individuals that included different species in the genus, wild representatives, and cultivated accessions, as well as 150 individuals from an F2 segregating population. Our analyses revealed that all of the domesticated varieties are derived from a single founder population that originated in or near the city of Rio de Janeiro in Brazil. We identified two loci associated with domesticated traits (flower symmetry and color) and did not detect any major hybridization or polyploidization events that could have contributed to the rapid increase in phenotypic diversity. Our findings, in conjunction with other features such as a small, low-complexity genome, ease of cultivation, and rapid generation time, makes this species an attractive model for the study of genomic variation under domestication.
Basic research on non-model organisms with low economic importance is uncommon but necessary to understand the world from a broader perspective. In such cases, reduced representation approaches like Genotyping-by-Sequencing (GBS) are efficient low-cost alternatives to whole genome resequencing. However, most of these technologies are subject to patent protection, licensing processes, and fees that constrain genomic research for small non-profit research organizations. We have designed a protocol to construct reduced representation libraries from genomic DNA. Our approach, called Targeted Amplification of Scattered Sites (TASS), deviates from the traditional digestion-ligation-amplification process that is the subject of intellectual property that protects most current methods. Instead, TASS relies on 1) targeting and duplicating scattered regions in the genome by annealing and expanding long tail primers with short annealing sites, and 2) amplifying these regions using primers that are complementary to the added overhangs. At the moment GBS is more consistent and delivers more variants than TASS. However, we have established a foundation on which further optimization can produce an accessible, easy to implement, high-throughput genotyping approach.Doctor of Philosophy
Most staple food crops were domesticated thousands of years ago through unrelated processes that were initiated across different regions of the world. Studies of the history of such crops have been essential to our understanding of plant domestication, a process that started with the collection of wild material and continued with subsequent propagation and cultivation under human care. Plant domestication has often involved a complex combination of ancestral lineages that encompass multiple populations, crosses with other species, and large DNA reorganizations that occurred hundreds to thousands of years earlier. Such intricate origins make the systematic study of plant domestication very challenging. The analysis of recently domesticated plants such as the 'florist's gloxinia' (Sinningia speciosa), can help us to better understand some of the changes that have occurred during domestication, as well as to comprehend modern patterns of plant domestication and to broaden our understanding of general trends. Florist's gloxinias are ornamental plants that have been cultivated during the last 200 years. In this study we examined 115 specimens, including wild and cultivated types of florist's gloxinias, as well as closely related species in Sinningia. We also constructed and evaluated an artificial population of 150 individuals from the cross of a wild and a cultivated form. Our analyses revealed that all of the domesticated varieties are descendants from a single wild population that originated in or near the city of Rio de Janeiro in Brazil. We also identified two regions of DNA that are responsible for the changes in flower shape and color, and crosses with other species did not introduce such alterations. Our findings, in conjunction with other features such as its small nuclear DNA content, the ease of cultivation indoors, and a rapid generation time, makes the florists' gloxinia an attractive crop to the study the effects of plant domestication. Research on organisms with low economic importance is uncommon but necessary to understand the world from a broader perspective. In such cases, analyzing the entire genetic information that is stored as DNA may be cost-prohibitive. Instead, approaches that sample small portions of DNA from each individual can be utilized. Most of these technologies are currently patented and subject to licensing processes and fees that limit their implementation by small non-profit research organizations. In this study we designed a protocol to sample small portions of DNA, similarly to existing techniques. However, our approach, called Targeted Amplification of Scattered Sites (TASS), employs a sampling process that deviates from the traditional patented procedure that is used in most current methods. At present, TASS is not as consistent and delivers less information than traditional approaches. However, we have established a foundation on which further optimization can produce an accessible and easy to implement technique.
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Damesa, Tigist Mideksa [Verfasser], and Hans-Peter [Akademischer Betreuer] Piepho. "Weighting methods for variance heterogeneity in phenotypic and genomic data analysis for crop breeding / Tigist Mideksa Damesa ; Betreuer: Hans-Peter Piepho." Hohenheim : Kommunikations-, Informations- und Medienzentrum der Universität Hohenheim, 2019. http://d-nb.info/1199440035/34.
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Fernández, Gallego José Armando. "Image processing techniques for plant phenotyping using RGB and thermal imagery = Técnicas de procesamiento de imágenes RGB y térmicas como herramienta para fenotipado de cultivos." Doctoral thesis, Universitat de Barcelona, 2019. http://hdl.handle.net/10803/669111.
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World cereal stocks need to increase in order to meet growing demands. Currently, maize, rice, wheat, are the main crops worldwide, while other cereals such as barley, sorghum, oat or different millets are also well placed in the top list. Crop productivity is affected directly by climate change factors such as heat, drought, floods or storms. Researchers agree that global climate change is having a major impact on crop productivity. In that way, several studies have been focused on climate change scenarios and more specifically abiotic stresses in cereals. For instance, in the case of heat stress, high temperatures between anthesis to grain filling can decrease grain yield. In order to deal with the climate change and future environmental scenarios, plant breeding is one of the main alternatives breeding is even considered to contribute to the larger component of yield growth compared to management. Plant breeding programs are focused on identifying genotypes with high yields and quality to act as a parentals and further the best individuals among the segregating population thus develop new varieties of plants. Breeders use the phenotypic data, plant and crop performance, and genetic information to improve the yield by selection (GxE, with G and E indicating genetic and environmental factors). More factors must be taken into account to increase the yield, such as, for instance, the education of farmers, economic incentives and the use of new technologies (GxExM, with M indicating management). Plant phenotyping is related with the observable (or measurable) characteristics of the plant while the crop growing as well as the association between the plant genetic background and its response to the environment (GxE). In traditional phenotyping the measurements are collated manually, which is tedious, time consuming and prone to subjective errors. Nowadays the technology is involved in many applications. From the point of view of plan phenotyping, technology has been incorporated as a tool. The use of image processing techniques integrating sensors and algorithm processes, is therefore, an alternative to asses automatically (or semi-automatically) these traits. Images have become a useful tool for plant phenotyping because most frequently data from the sensors are processed and analyzed as an image in two (2D) or three (3D) dimensions. An image is the arrangement of pixels in a regular Cartesian coordinates as a matrix, each pixel has a numerical value into the matrix which represents the number of photons captured by the sensor within the exposition time. Therefore, an image is the optical representation of the object illuminated by a radiating source. The main characteristics of images can be defined by the sensor spectral and spatial properties, with the spatial properties of the resulting image also heavily dependent on the sensor platform (which determines the distance from the target object).Las existencias mundiales de cereales deben aumentar para satisfacer la creciente demanda. Actualmente, el maíz, el arroz y el trigo son los principales cultivos a nivel mundial, otros cereales como la cebada, el sorgo y la avena están también bien ubicados en la lista. La productividad de los cultivos se ve afectada directamente por factores del cambio climático como el calor, la sequía, las inundaciones o las tormentas. Los investigadores coinciden en que el cambio climático global está teniendo un gran impacto en la productividad de los cultivos. Es por esto que muchos estudios se han centrado en escenarios de cambio climático y más específicamente en estrés abiótico. Por ejemplo, en el caso de estrés por calor, las altas temperaturas entre antesis y llenado de grano pueden disminuir el rendimiento del grano. Para hacer frente al cambio climático y escenarios ambientales futuros, el mejoramiento de plantas es una de las principales alternativas; incluso se considera que las técnicas de mejoramiento contribuyen en mayor medida al aumento del rendimiento que el manejo del cultivo. Los programas de mejora se centran en identificar genotipos con altos rendimientos y calidad para actuar como progenitores y promover los mejores individuos para desarrollar nuevas variedades de plantas. Los mejoradores utilizan los datos fenotípicos, el desempeño de las plantas y los cultivos, y la información genética para mejorar el rendimiento mediante selección (GxE, donde G y E indican factores genéticos y ambientales). El fenotipado plantas está relacionado con las características observables (o medibles) de la planta mientras crece el cultivo, así como con la asociación entre el fondo genético de la planta y su respuesta al medio ambiente (GxE). En el fenotipado tradicional, las mediciones se clasifican manualmente, lo cual es tedioso, consume mucho tiempo y es propenso a errores subjetivos. Sin embargo, hoy en día la tecnología está involucrada en muchas aplicaciones. Desde el punto de vista del fenotipado de plantas, la tecnología se ha incorporado como una herramienta. El uso de técnicas de procesamiento de imágenes que integran sensores y algoritmos son por lo tanto una alternativa para evaluar automáticamente (o semiautomáticamente) estas características.
Books on the topic "Crop Phenotyping"
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Zhou, Jianfeng, and Henry T. Nguyen, eds. High-Throughput Crop Phenotyping. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73734-4.
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Zhou, Jianfeng, and Henry T. Nguyen. High-Throughput Crop Phenotyping. Springer International Publishing AG, 2022.
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Zhou, Jianfeng, and Henry T. Nguyen. High-Throughput Crop Phenotyping. Springer International Publishing AG, 2021.
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Panguluri, Siva Kumar, and Are Ashok Kumar. Phenotyping for Plant Breeding: Applications of Phenotyping Methods for Crop Improvement. Springer, 2013.
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Panguluri, Siva Kumar, and Are Ashok Kumar. Phenotyping for Plant Breeding: Applications of Phenotyping Methods for Crop Improvement. Springer, 2013.
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Panguluri, Siva Kumar, and Are Ashok Kumar. Phenotyping for Plant Breeding: Applications of Phenotyping Methods for Crop Improvement. Springer, 2016.
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Panguluri, Siva Kumar, and Are Ashok Kumar. Phenotyping for Plant Breeding: Applications of Phenotyping Methods for Crop Improvement. Springer London, Limited, 2013.
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Sudhakar, P., P. Latha, and P. V. Reddy. Phenotyping Crop Plants for Physiological and Biochemical Traits. Elsevier Science & Technology Books, 2016.
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Phenotyping Crop Plants for Physiological and Biochemical Traits. Elsevier Science & Technology Books, 2016.
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Prashar, Ankush, Lindsey Compton, Martina Stromvik, and Helen H. Tai, eds. High-Throughput Phenotyping for Crop Improvement and Breeding. Frontiers Media SA, 2022. http://dx.doi.org/10.3389/978-2-88974-283-7.
Full textBook chapters on the topic "Crop Phenotyping"
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Tariq, Muhammad, Mukhtar Ahmed, Pakeeza Iqbal, Zartash Fatima, and Shakeel Ahmad. "Crop Phenotyping." In Systems Modeling, 45–60. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4728-7_2.
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Araus, José Luis, Shawn Carlisle Kefauver, Mainassara Zaman-Allah, Mike S. Olsen, and Jill E. Cairns. "Phenotyping: New Crop Breeding Frontier." In Crop Science, 493–503. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-8621-7_1036.
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Tariq, Muhammad, Muhammad Habib Ur Rehman, Feng Ling Yang, Muhammad Hayder Bin Khalid, Muhammad Ali Raza, Muhammad Jawad Hassan, Tehseen Ahmad Meraj, et al. "Rice Phenotyping." In Modern Techniques of Rice Crop Production, 151–64. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-4955-4_11.
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Paulus, Stefan, Gustavo Bonaventure, and Marcus Jansen. "Multisensor Phenotyping for Crop Physiology." In Intelligent Image Analysis for Plant Phenotyping, 25–42. First edition. | Boca Raton, FL : CRC Press, 2021.: CRC Press, 2020. http://dx.doi.org/10.1201/9781315177304-3.
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Araus, José Luis, Shawn Carlisle Kefauver, Mainassara Zaman-Allah, Mike S. Olsen, and Jill E. Cairns. "Phenotyping: New Crop Breeding Frontier." In Encyclopedia of Sustainability Science and Technology, 1–11. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-2493-6_1036-1.
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Yol, Engin, Cengiz Toker, and Bulent Uzun. "Traits for Phenotyping." In Phenomics in Crop Plants: Trends, Options and Limitations, 11–26. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2226-2_2.
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Chen, Ying Long, Ivica Djalovic, and Zed Rengel. "Phenotyping for Root Traits." In Phenomics in Crop Plants: Trends, Options and Limitations, 101–28. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2226-2_8.
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Rajendran, Karthika, Somanagouda Patil, and Shiv Kumar. "Phenotyping for Problem Soils." In Phenomics in Crop Plants: Trends, Options and Limitations, 129–46. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2226-2_9.
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Thavarajah, Dil, Casey R. Johnson, Rebecca McGee, and Pushparajah Thavarajah. "Phenotyping Nutritional and Antinutritional Traits." In Phenomics in Crop Plants: Trends, Options and Limitations, 223–33. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2226-2_15.
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Pratap, Aditya, Rakhi Tomar, Jitendra Kumar, Vankat Raman Pandey, Suhel Mehandi, and Pradeep Kumar Katiyar. "High-Throughput Plant Phenotyping Platforms." In Phenomics in Crop Plants: Trends, Options and Limitations, 285–96. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2226-2_19.
Full textConference papers on the topic "Crop Phenotyping"
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Pour, Majid Khak, Reza Fotouhi, and Pierre Hucl. "Development of a Mobile Platform for Wheat Phenotyping." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-24329.
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Abstract Designing and implementing an affordable High-Throughput Phenotyping Platform (HTPP) for monitoring crops’ features in different stages of their growth can provide valuable information for crop-breeders to study possible correlation between genotypes and phenotypes. Conducting automatic field measurements can improve crop productions. In this research, we have focused on development of a mechatronic system, hardware and software, for a mobile field-based HTPP for autonomous crop monitoring for wheat field. The system can measure canopy’s height, temperature, vegetation indices and is able to take high quality photos of crops. The system includes developed software for data and image acquisition. The main contribution of this study is autonomous, reliable, and fast data collection for wheat and similar crops.
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Zhang, QianWei, Reza Fotouhi, Joshua Cote, and Majid Khak Pour. "Lightweight Long-Reach 5-DOF Robot Arm for Farm Application." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-98366.
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Abstract Crop monitoring is frequently used by crop scientists to observe growth of plants and to relate plants phenotypes to their genotypes. Instead of traditional crop monitoring, which is labor intensive, high-throughput plant phenotyping (HTP) platforms using ground-based vehicle have several advantages over manual methods. Existing HTP platforms with robot arms has limited reach and payload, and they are sometimes not appropriate for monitoring large fields. In this research, a 5-DOF robot arm is developed and analyzed for monitoring several crops growth. This robot arm is a hybrid of both prismatic and rotational joints. This new mobile manipulator is light, has a compact structure, suitable for plant phenotyping, and doesn’t exist commercially. To investigate the performance of the robot arm, kinematics and dynamics analyses using Newton-Euler iterative method and MATLAB simulations are performed. Results matched with each other very well.
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Zhang, Qianwei, and Reza Fotouhi. "Vibration Analysis of a Long Boom for a Farm Machine." In ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/detc2018-86188.
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Crop phenotyping is frequently used by breeders and crop scientists to monitor growth of plants and to relate them to plants genotypes. Seemingly, this contributes to better crop growth and results in higher yield. Instead of traditional crop monitoring, which is labor intensive, high-throughput phenotyping (HTP) platforms using ground-based vehicle have several advantages (in speed, efficiency, and cost) over manual methods. A wheeled mobile platform for HTP was developed, and automated data collection were performed for different traits of canola and wheat. These data were compared with manual measured data. In this paper, vibration analysis of a relatively long cantilever boom attached to a vehicle is reported. The paper investigates how different factors influence the boom attached to a regular farming machine, its vibration, and effects on phenotyping sensors attached to the boom.
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Smitt, Claus, Michael Halstead, Tobias Zaenker, Maren Bennewitz, and Chris McCool. "PATHoBot: A Robot for Glasshouse Crop Phenotyping and Intervention." In 2021 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2021. http://dx.doi.org/10.1109/icra48506.2021.9562047.
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"Global Patent Analysis on Computer Vision Powered Crop Phenotyping." In 2022 the 12th International Workshop on Computer Science and Engineering. WCSE, 2022. http://dx.doi.org/10.18178/wcse.2022.06.006.
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Manish, Raja, Ze An, Ayman Habib, Mitchell R. Tuinstra, and David J. Cappelleri. "AgBug: Agricultural Robotic Platform for In-Row and Under Canopy Crop Monitoring and Assessment." In ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/detc2021-68143.
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Abstract This paper focuses on the development of a small scale agricultural robotic platform with advantages over the current agricultural phenotyping platforms that lack the size-scale and sensor resolution needed to study hard to reach under-canopy row crops. The AgBug utilizes a sensor suite consisting of a LiDAR and RGB camera for crop monitoring on a 12″ × 9″ footprint platform. The main challenge for this platform design is not only its compact size and portability, but its ability to navigate and obtain geo-referenced and time-tagged data in the GNSS-denied environment that exists under the crop canopy. LiDAR and RGB sensors typically rely on inputs from GNSS data. Therefore, a new approach was developed here fusing direct feedback from the RGB camera and a visual-inertial tracking camera supplying robot odometry data. Indoor and outdoor tests were conducted to demonstrate the AgBug’s ability for in-row and under canopy crop monitoring along with the efficacy of sensor fusion approach.
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Niu, Haoyu, Dong Wang, and YangQuan Chen. "Estimating actual crop evapotranspiration using deep stochastic configuration networks model and UAV-based crop coefficients in a pomegranate orchard." In Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V, edited by J. Alex Thomasson and Alfonso F. Torres-Rua. SPIE, 2020. http://dx.doi.org/10.1117/12.2558221.
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Gao, Tianshuang, Hamid Emadi, Homagni Saha, Jiaoping Zhang, Alec Lofquist, Arti Singh, Baskar Ganapathysubramanian, Soumik Sarkar, Asheesh Singh, and Sourabh Bhattacharya. "Navigation Strategies for a Multi-Robot Ground-Based Row Crop Phenotyping Platform." In ASME 2018 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/dscc2018-9096.
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In this work, we address the problem of deploying a multi-robot system for row crop phenotyping. We propose a sampling-based navigation algorithm for the team of robots to estimate the underlying spatial distribution in a field. We use Gaussian Process Models to predict the distribution of a scalar function in a field, and choose Mutual Information as a metric for selecting the future samples. With a row crop structure, we present a collision-free assignment and scheduling algorithm for the robots to reach the goal positions which minimizes the total traveling distance. The effectiveness of the proposed algorithm is demonstrated through simulations.
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Phillips, Ryan, and Jason Ward. "Assessing crop response to simulated damage utilizing UAS imagery." In Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V, edited by J. Alex Thomasson and Alfonso F. Torres-Rua. SPIE, 2020. http://dx.doi.org/10.1117/12.2560702.
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Weyler, Jan, Federico Magistri, Peter Seitz, Jens Behley, and Cyrill Stachniss. "In-Field Phenotyping Based on Crop Leaf and Plant Instance Segmentation." In 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE, 2022. http://dx.doi.org/10.1109/wacv51458.2022.00302.
Full textReports on the topic "Crop Phenotyping"
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Gur, Amit, Edward Buckler, Joseph Burger, Yaakov Tadmor, and Iftach Klapp. Characterization of genetic variation and yield heterosis in Cucumis melo. United States Department of Agriculture, January 2016. http://dx.doi.org/10.32747/2016.7600047.bard.
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Project objectives: 1) Characterization of variation for yield heterosis in melon using Half-Diallele (HDA) design. 2) Development and implementation of image-based yield phenotyping in melon. 3) Characterization of genetic, epigenetic and transcriptional variation across 25 founder lines and selected hybrids. The epigentic part of this objective was modified during the course of the project: instead of characterization of chromatin structure in a single melon line through genome-wide mapping of nucleosomes using MNase-seq approach, we took advantage of rapid advancements in single-molecule sequencing and shifted the focus to Nanoporelong-read sequencing of all 25 founder lines. This analysis provides invaluable information on genome-wide structural variation across our diversity 4) Integrated analyses and development of prediction models Agricultural heterosis relates to hybrids that outperform their inbred parents for yield. First generation (F1) hybrids are produced in many crop species and it is estimated that heterosis increases yield by 15-30% globally. Melon (Cucumismelo) is an economically important species of The Cucurbitaceae family and is among the most important fleshy fruits for fresh consumption Worldwide. The major goal of this project was to explore the patterns and magnitude of yield heterosis in melon and link it to whole genome sequence variation. A core subset of 25 diverse lines was selected from the Newe-Yaar melon diversity panel for whole-genome re-sequencing (WGS) and test-crosses, to produce structured half-diallele design of 300 F1 hybrids (MelHDA25). Yield variation was measured in replicated yield trials at the whole-plant and at the rootstock levels (through a common-scion grafted experiments), across the F1s and parental lines. As part of this project we also developed an algorithmic pipeline for detection and yield estimation of melons from aerial-images, towards future implementation of such high throughput, cost-effective method for remote yield evaluation in open-field melons. We found extensive, highly heritable root-derived yield variation across the diallele population that was characterized by prominent best-parent heterosis (BPH), where hybrids rootstocks outperformed their parents by 38% and 56 % under optimal irrigation and drought- stress, respectively. Through integration of the genotypic data (~4,000,000 SNPs) and yield analyses we show that root-derived hybrids yield is independent of parental genetic distance. However, we mapped novel root-derived yield QTLs through genome-wide association (GWA) analysis and a multi-QTLs model explained more than 45% of the hybrids yield variation, providing a potential route for marker-assisted hybrid rootstock breeding. Four selected hybrid rootstocks are further studied under multiple scion varieties and their validated positive effect on yield performance is now leading to ongoing evaluation of their commercial potential. On the genomic level, this project resulted in 3 layers of data: 1) whole-genome short-read Illumina sequencing (30X) of the 25 founder lines provided us with 25 genome alignments and high-density melon HapMap that is already shown to be an effective resource for QTL annotation and candidate gene analysis in melon. 2) fast advancements in long-read single-molecule sequencing allowed us to shift focus towards this technology and generate ~50X Nanoporesequencing of the 25 founders which in combination with the short-read data now enable de novo assembly of the 25 genomes that will soon lead to construction of the first melon pan-genome. 3) Transcriptomic (3' RNA-Seq) analysis of several selected hybrids and their parents provide preliminary information on differentially expressed genes that can be further used to explain the root-derived yield variation. Taken together, this project expanded our view on yield heterosis in melon with novel specific insights on root-derived yield heterosis. To our knowledge, thus far this is the largest systematic genetic analysis of rootstock effects on yield heterosis in cucurbits or any other crop plant, and our results are now translated into potential breeding applications. The genomic resources that were developed as part of this project are putting melon in the forefront of genomic research and will continue to be useful tool for the cucurbits community in years to come.
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Hunter, Martha S., and Einat Zchori-Fein. Rickettsia in the whitefly Bemisia tabaci: Phenotypic variants and fitness effects. United States Department of Agriculture, September 2014. http://dx.doi.org/10.32747/2014.7594394.bard.
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The sweet potato whitefly, Bemisia tabaci (Hemiptera: Aleyrodidae) is a major pest of vegetables, field crops, and ornamentals worldwide. This species harbors a diverse assembly of facultative, “secondary” bacterial symbionts, the roles of which are largely unknown. We documented a spectacular sweep of one of these, Rickettsia, in the Southwestern United States in the B biotype (=MEAM1) of B. tabaci, from 1% to 97% over 6 years, as well as a dramatic fitness benefit associated with it in Arizona but not in Israel. Because it is critical to understand the circumstances in which a symbiont invasion can cause such a large change in pest life history, the following objectives were set: 1) Determine the frequency of Rickettsia in B. tabaci in cotton across the United States and Israel. 2) Characterize Rickettsia and B. tabaci genotypes in order to test the hypothesis that genetic variation in either partner is responsible for differences in phenotypes seen in the two countries. 3) Determine the comparative fitness effects of Rickettsia phenotypes in B. tabaci in Israel and the United States. For Obj. 1, a survey of B. tabaci B samples revealed the distribution of Rickettsia across the cotton-growing regions of 13 sites from Israel and 22 sites from the USA. Across the USA, Rickettsia frequencies were heterogeneous among regions, but were generally at frequencies higher than 75% and close to fixation in some areas, whereas in Israel the infection rates were lower and declining. The distinct outcomes of Rickettsia infection in these two countries conform to previouslyreported phenotypic differences. Intermediate frequencies in some areas in both countries may indicate a cost to infection in certain environments or that the frequencies are in flux. This suggests underlying geographic differences in the interactions between bacterial symbionts and the pest. Obj. 2, Sequences of several Rickettsia genes in both locations, including a hypervariableintergenic spacer gene, suggested that the Rickettsia genotype is identical in both countries. Experiments in the US showed that differences in whitefly nuclear genotype had a strong influence on Rickettsia phenotype. Obj. 3. Experiments designed to test for possible horizontal transmission of Rickettsia, showed that these bacteria are transferred from B. tabaci to a plant, moved inside the phloem, and could be acquired by other whiteflies. Plants can serve as a reservoir for horizontal transmission of Rickettsia, a mechanism that may explain the occurrence of phylogenetically-similarsymbionts among unrelated phytophagous insect species. This plant-mediated transmission route may also exist in other insect-symbiont systems, and since symbionts may play a critical role in the ecology and evolution of their hosts, serve as an immediate and powerful tool for accelerated evolution. However, no such horizontal transmission of Rickettsia could be detected in the USA, underlining the difference between the interaction in both countries, or between B. tabaci and the banded wing whitefly on cotton in the USA (Trialeurodes sp. nr. abutiloneus) and the omnivorous bug Nesidiocoristenuis. Additionally, a series of experiments excluded the possibility that Rickettsia is frequently transmitted between B. tabaci and its parasitoid wasps Eretmocerusmundus and Encarsiapergandiella. Lastly, ecological studies on Rickettsia effects on free flight of whiteflies showed no significant influence of symbiont infection on flight. In contrast, a field study of the effects of Rickettsia on whitefly performance on caged cotton in the USA showed strong fitness benefits of infection, and rapid increases in Rickettsia frequency in competition population cages. This result confirmed the benefits to whiteflies of Rickettsia infection in a field setting.
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Paterson, Andrew H., Yehoshua Saranga, and Dan Yakir. Improving Productivity of Cotton (Gossypsum spp.) in Arid Region Agriculture: An Integrated Physiological/Genetic Approach. United States Department of Agriculture, December 1999. http://dx.doi.org/10.32747/1999.7573066.bard.
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Objectives: We seek to establish the basis for improving cotton productivity under arid conditions, by studying the water use efficiency - evaporative cooling interrelationship. Specifically, we will test the hypothesis that cotton productivity under arid conditions can be improved by combining high seasonal WUE with efficient evaporative cooling, evaluate whether high WUE and/or evaporative cooling are based on specific physiological factors such as diurnal flexibility in stomatal conductance, stomatal density, photosynthetic capacity, chlorophyll fluorescence, and plant water status. Genes influencing both WUE and evaporative cooling, as well as other parameters such as economic products (lint yield, quality, harvest index) of cotton will also be mapped, in order to evaluate influences of water relations on these parameters. Approach: Carbon isotope ratio will be used to evaluate WUE, accompanied by additional parameters to elucidate the relationship between WUE, evaporative cooling, and cotton productivity. A detailed RFLP map will be used to determine the number, location, and phenotypic effects of genes underlying genetic variation in WUE between cultivated cottons, as well as test associations of these genes with traits of economic importance such as harvest index, lint yield, and lint quality. Major Conclusions: Productivity and quality of cotton grown under well-watered versus water-limited conditions was shown to be partly accounted for by different quantitative trait loci (QTLs). Among a suite of physiological traits often found to differ between genotypes adapted to arid versus well-watered conditions, genetic mapping implicated only reduced plant osmotic potential in improved cotton productivity under arid conditions. Our findings clearly implicate OP as a major component of cotton adaptation to arid conditions. However, testing of further physiological hypotheses is clearly needed to account for additional QTL alleles conferring higher seed-cotton yield under arid conditions, such as three of the five we found. Near-isogenic lines being made for QTLs discovered herein will offer a powerful new tool useful toward identification of the underlying gene(s) by using fine-scale mapping approaches (Paterson et al 1990). Implications: Adaptation to both arid and favorable conditions can be combined into the same genotype. We have identified diagnostic DNA markers that are being applied to creation of such desirable genotypes. Simultaneous improvement of productivity (and/or quality) for both arid and irrigated conditions will require more extensive field testing and the manipulation of larger numbers of genes, reducing the expected rate of genetic gain These difficulties may be at least partly ameliorated by efficiencies gained through identification and use of diagnostic DNA markers. Genomic tools and approaches may expedite adaptation of crops to arid cultivation, help to test roles of additional physiological factors, and guide the isolation of the underlying genes that protect crop performance under arid conditions.
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Blum, Abraham, and Henry T. Nguyen. Molecular Tagging of Drought Resistance in Wheat: Osmotic Adjustment and Plant Productivity. United States Department of Agriculture, November 2002. http://dx.doi.org/10.32747/2002.7580672.bard.
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Drought stress is a major limitation to bread wheat (Triticumaestivum L.) productivity and its yield stability in arid and semi-arid regions of world including parts of Israel and the U.S. Currently, breeding for sustained yields under drought stress is totally dependent on the use of yield and several key physiological attributes as selection indices. The attempt to identify the optimal genotype by evaluating the phenotype is undermining progress in such breeding programs. Osmotic adjustment (OA) is an effective drought resistance mechanism in many crop plants. Evidence exists that there is a genetic variation for OA in wheat and that high OA capacity supports wheat yields under drought stress. The major objective of this research was to identify molecular markers (RFLPs, restriction fragment length polymorphisms; and AFLPs, amplified fragment length polymorph isms) linked to OA as a major attribute of drought resistance in wheat and thus to facilitate marker-assisted selection for drought resistance. We identified high and low OA lines of wheat and from their cross developed recombinant inbred lines (RILs) used in the molecular tagging of OA in relation to drought resistance in terms of plant production under stress. The significant positive co-segregation of OA, plant water status and yield under stress in this RIL population provided strong support for the important role of OA as a drought resistance mechanism sustaining wheat production under drought stress. This evidence was obtained in addition to the initial study of parental materials for constructing this RIL population, which also gave evidence for a strong correlation between OA and grain yield under stress. This research therefore provides conclusive evidence on the important role of OA in sustaining wheat yield under drought stress. The measurement of OA is difficult and the selection for drought resistance by the phenotypic expression of OA is practically impossible. This research provided information on the genetic basis of OA in wheat in relations to yield under stress. It provided the basic information to indicate that molecular marker assisted selection for OA in wheat is possible. The RIL population has been created by a cross between two agronomic spring wheat lines and the high OA recombinants in this population presented very high OA values, not commonly observed in wheat. These recombinants are therefore an immediate valuable genetic recourse for breeding well-adapted drought resistant wheat in Texas and Israel. We feel that this work taken as a whole eliminate the few previous speculated . doubts about the practical role of OA as an important mechanism of drought resistance in economic crop plants. As such it should open the way, in terms of both concept and the use of marker assisted selection, for improving drought resistance in wheat by deploying high osmotic adjustment.
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Weil, Clifford F., Anne B. Britt, and Avraham Levy. Nonhomologous DNA End-Joining in Plants: Genes and Mechanisms. United States Department of Agriculture, July 2001. http://dx.doi.org/10.32747/2001.7585194.bard.
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Repair of DNA breaks is an essential function in plant cells as well as a crucial step in addition of modified DNA to plant cells. In addition, our inability to introduce modified DNA to its appropriate locus in the plant genome remains an important hurdle in genetically engineering crop species.We have taken a combined forward and reverse genetics approach to examining DNA double strand break repair in plants, focusing primarily on nonhomologous DNA end-joining. The forward approach utilizes a gamma-plantlet assay (miniature plants that are metabolically active but do not undergo cell division, due to cell cycle arrest) and has resulted in identification of five Arabidopsis mutants, including a new one defective in the homolog of the yeast RAD10 gene. The reverse genetics approach has identified knockouts of the Arabidopsis homologs for Ku80, DNA ligase 4 and Rad54 (one gene in what proves to be a gene family involved in DNA repair as well as chromatin remodeling and gene silencing)). All these mutants have phenotypic defects in DNA repair but are otherwise healthy and fertile. Additional PCR based screens are in progress to find knockouts of Ku70, Rad50, and Mre11, among others. Two DNA end-joining assays have been developed to further our screens and our ability to test candidate genes. One of these involves recovering linearized plasmids that have been added to and then rejoined in plant cells; plasmids are either recovered directly or transformed into E. coli and recovered. The products recovered from various mutant lines are then compared. The other assay involves using plant transposon excision to create DNA breaks in yeast cells and then uses the yeast cell as a system to examine those genes involved in the repair and to screen plant genes that might be involved as well. This award supported three graduate students, one in Israel and two in the U.S., as well as a technician in the U.S., and is ultimately expected to result directly in five publications and one Masters thesis.
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Sherman, Amir, Rebecca Grumet, Ron Ophir, Nurit Katzir, and Yiqun Weng. Whole genome approach for genetic analysis in cucumber: Fruit size as a test case. United States Department of Agriculture, December 2013. http://dx.doi.org/10.32747/2013.7594399.bard.
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The Cucurbitaceae family includes a broad array of economically and nutritionally important crop species that are consumed as vegetables, staple starches and desserts. Fruit of these species, and types within species, exhibit extensive diversity as evidenced by variation in size, shape, color, flavor, and others. Fruit size and shape are critical quality determinants that delineate uses and market classes and are key traits under selection in breeding programs. However, the underlying genetic bases for variation in fruit size remain to be determined. A few species the Cucurbitaceae family were sequenced during the time of this project (cucumber was already sequenced when the project started watermelon and melon sequence became available during the project) but functional genomic tools are still missing. This research program had three major goals: 1. Develop whole genome cucumber and melon SNP arrays. 2. Develop and characterize cucumber populations segregating for fruit size. 3. Combine genomic tools, segregating populations, and phenotypic characterization to identify loci associated with fruit size. As suggested by the reviewers the work concentrated mostly in cucumber and not both in cucumber and melon. In order to develop a SNP (single nucleotide polymorphism) array for cucumber, available and newly generated sequence from two cucumber cultivars with extreme differences in shape and size, pickling GY14 and Chinese long 9930, were analyzed for variation (SNPs). A large set of high quality SNPs was discovered between the two parents of the RILs population (GY14 and 9930) and used to design a custom SNP array with 35000 SNPs using Agilent technology. The array was validated using 9930, Gy14 and F1 progeny of the two parents. Several mapping populations were developed for linkage mapping of quantitative trait loci (QTL) for fruit size These includes 145 F3 families and 150 recombinant inbred line (RILs F7 or F8 (Gy14 X 9930) and third population contained 450 F2 plants from a cross between Gy14 and a wild plant from India. The main population that was used in this study is the RILs population of Gy14 X 9930. Phenotypic and morphological analyses of 9930, Gy14, and their segregating F2 and RIL progeny indicated that several, likely independent, factors influence cucumber fruit size and shape, including factors that act both pre-anthesis and post-pollination. These include: amount, rate, duration, and plane of cell division pre- and post-anthesis and orientation of cell expansion. Analysis of F2 and RIL progeny indicated that factors influencing fruit length were largely determined pre-anthesis, while fruit diameter was more strongly influenced by environment and growth factors post-anthesis. These results suggest involvement of multiple genetically segregating factors expected to map independently onto the cucumber genome. Using the SNP array and the phenotypic data two major QTLs for fruit size of cucumber were mapped in very high accuracy (around 300 Kb) with large set of markers that should facilitate identification and cloning of major genes that contribute to fruit size in cucumber. In addition, a highly accurate haplotype map of all RILS was created to allow fine mapping of other traits segregating in this population. A detailed cucumber genetic map with 6000 markers was also established (currently the most detailed genetic map of cucumber). The integration of genetics physiology and genomic approaches in this project yielded new major infrastructure tools that can be used for understanding fruit size and many other traits of importance in cucumber. The SNP array and genetic population with an ultra-fine map can be used for future breeding efforts, high resolution mapping and cloning of traits of interest that segregate in this population. The genetic map that was developed can be used for other breeding efforts in other populations. The study of fruit development that was done during this project will be important in dissecting function of genes that that contribute to the fruit size QTLs. The SNP array can be used as tool for mapping different traits in cucumber. The development of the tools and knowledge will thus promote genetic improvement of cucumber and related cucurbits.
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Rowe, Randall C., Jaacov Katan, Talma Katan, and Leah Tsror. Sub-Specific Populations of Verticillium dahliae and their Roles in Vascular Wilt Pathogsystems. United States Department of Agriculture, October 1996. http://dx.doi.org/10.32747/1996.7574343.bard.
Full textAbstract:
Verticillium dahliae is an economically important pathogen causing vascular wilt on over 160 plant species. In North America, potato early dying is a significant disease of potato, especially in the midwest and Pacific northwest states. This disease is caused by the fungus Verticillium dahliae and in some cases involves a synergistic interaction with root-lesion nematodes, primarily Pratylenchus penetrans. In Israel, Verticillium wilt occurs in many regions and inflicts serious losses in potato, cotton, and other crops. Objectives of this project were to establish a large collection of isolates of Verticillium dahliae from potato (USA) and several host plants (Israel) and to characterize and compare the isolates with regard to morphology, vegetative compatibility group (VCG), and pathogenic capabilities on several hosts. Isolations were made from 224 commercial lots of certified potato seed tubers from across N. America and 87 potato fields located in the Columbia Basin of Oregon and Washington. A large collection of isolates from central U.S. states already existed. In Israel, 47 field sites were sampled and isolates of Verticillium dahliae were recovered from 13 host plant species and from soil. Potato isolates from N. America were tested for vegetative compatibility and all found to be in VCG 4 with about 2/3 in VCG 4A and the rest in VCG 4B. VCG 4A isolates were significantly more aggressive on potato than VCG 4B isolates and were more likely to interact synergistically with P. penetrans. The Israeli isolates fell into three vegetative compatibility groups. Nearly all (> 90%) VCG2B and VCG 4B isolates were recovered from the northern and southern parts of Israel, respectively, with some overlap in central areas. Several pathotypes were defined in cotton, using cotton and eggplant together as differentials. All VCG 2B isolates from cotton caused severe disease in cotton, while VCG 2A and VCG 4B isolates from several crops were much less aggressive to cotton. When Israeli isolates of VCGs 2A, 2B and 4B were inoculated to potato and tomato, VCG 4B isolates caused much more severe disease on potato and VCG 2A isolates caused much more severe disease in tomato. Differential patterns of pathogenicity and aggressiveness of these VCGs on potato and tomato were consistent regardless of the host plant of origin. Isolates of the same VCG resembled one another more than isolates from different VCGs based on colony and microsclerotial morphology, temperature responses and, partially, in pathogenicity. Vegetative compatibility grouping of V. dahliae in Israel appears closely associated with specific pathogenicity and other phenotypic traits. The absence of VCG 4A in Israel is significant. VCG patterns among Verficillium populations are useful to predict relatedness and pathogenic potential in both countries.
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Abbo, Shahal, Hongbin Zhang, Clarice Coyne, Amir Sherman, Dan Shtienberg, and George J. Vandemark. Winter chickpea; towards a new winter pulse for the semiarid Pacific Northwest and wider adaptation in the Mediterranean basin. United States Department of Agriculture, January 2011. http://dx.doi.org/10.32747/2011.7597909.bard.
Full textAbstract:
Original objectives: [a] Screen an array of chickpea and wild annual Cicer germplasm for winter survival. [b] Genetic analysis of winter hardiness in domesticated x wild chickpea crosses. [c] Genetic analysis of vernalization response in domesticated x wild chickpea crosses. [d] Digital expression analysis of a core selection of breeding and germplasm lines of chickpea that differ in winter hardiness and vernalization. [e] Identification of the genes involved in the chickpea winter hardiness and vernalization and construction of gene network controlling these traits. [f] Assessing the phenotypic and genetic correlations between winter hardiness, vernalization response and Ascochyta blight response in chickpea. The complexity of the vernalization response and the inefficiency of our selection experiments (below) required quitting the work on ascochyta response in the framework of this project. Background to the subject: Since its introduction to the Palouse region of WA and Idaho, and the northern Great Plains, chickpea has been a spring rotation legume due to lack of winter hardiness. The short growing season of spring chickpea limits its grain yield and leaves relatively little stubble residue for combating soil erosion. In Israel, chilling temperatures limit pod setting in early springs and narrow the effective reproductive time window of the crop. Winter hardiness and vernalization response of chickpea alleles were lost due to a series of evolutionary bottlenecks; however, such alleles are prevalent in its wild progenitor’s genepool. Major conclusions, solutions, achievements: It appears that both vernalization response and winter hardiness are polygenic traits in the wild-domesticated chickpea genepool. The main conclusion from the fieldwork in Israel is that selection of domesticated winter hardy and vernalization responsive types should be conducted in late flowering and late maturity backgrounds to minimize interference by daylength and temperature response alleles (see our Plant Breeding paper on the subject). The main conclusion from the US winter-hardiness studies is that excellent lines have been identified for germplasm release and continued genetic study. Several of the lines have good seed size and growth habit that will be useful for introgressing winter-hardiness into current chickpea cultivars to develop releases for autumn sowing. We sequenced the transcriptomes and profiled the expression of genes in 87 samples. Differential expression analysis identified a total of 2,452 differentially expressed genes (DEGs) between vernalized plants and control plants, of which 287 were shared between two or more Cicer species studied. We cloned 498 genes controlling vernalization, named CVRN genes. Each of the CVRN genes contributes to flowering date advance (FDA) by 3.85% - 10.71%, but 413 (83%) other genes had negative effects on FDA, while only 83 (17%) had positive effects on FDA, when the plant is exposed to cold temperature. The cloned CVRN genes provide new toolkits and knowledge to develop chickpea cultivars that are suitable for autumn-sowing. Scientific & agricultural implications: Unlike the winter cereals (barley, wheat) or pea, in which a single allelic change may induce a switch from winter to spring habit, we were unable to find any evidence for such major gene action in chickpea. In agricultural terms this means that an alternative strategy must be employed in order to isolate late flowering – ascochyta resistant (winter types) domesticated forms to enable autumn sowing of chickpea in the US Great Plains. An environment was identified in U.S. (eastern Washington) where autumn-sown chickpea production is possible using the levels of winter-hardiness discovered once backcrossed into advanced cultivated material with acceptable agronomic traits. The cloned CVRN genes and identified gene networks significantly advance our understanding of molecular mechanisms underlying plant vernalization in general, and chickpea in particular, and provide a new toolkit for switching chickpea from a spring-sowing to autumn-sowing crop.
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Lers, Amnon, and Gan Susheng. Study of the regulatory mechanism involved in dark-induced Postharvest leaf senescence. United States Department of Agriculture, January 2009. http://dx.doi.org/10.32747/2009.7591734.bard.
Full textAbstract:
Postharvest leaf senescence contributes to quality losses in flowers and leafy vegetables. The general goal of this research project was to investigate the regulatory mechanisms involved in dark-induced leaf senescence. The regulatory system involved in senescence induction and control is highly complex and possibly involves a network of senescence promoting pathways responsible for activation of the senescence-associated genes. Pathways involving different internal signals and environmental factors may have distinctive importance in different leaf senescence systems. Darkness is known to have a role in enhancement of postharvest leaf senescence and for getting an insight into its regulatory mechanism/s we have applied molecular genetics and functional genomics approaches. The original objectives were: 1. Identification of dark-induced SAGs in Arabidopsis using enhancer/promoter trap lines and microarray approaches; 2. Molecular and functional characterization of the identified genes by analyzing their expression and examining the phenotypes in related knockout mutant plants; 3. Initial studies of promoter sequences for selected early dark-induced SAGs. Since genomic studies of senescence, with emphasis on dark-induced senescence, were early-on published which included information on potential regulatory genes we decided to use this new information. This is instead of using the uncharacterized enhancer/promoter trap lines as originally planned. We have also focused on specific relevant genes identified in the two laboratories. Based on the available genomic analyses of leaf senescence 10 candidate genes hypothesized to have a regulatory role in dark-induced senescence were subjected to both expression as well as functional analyses. For most of these genes senescence-specific regulation was confirmed, however, functional analyses using knock-out mutants indicated no consequence to senescence progression. The transcription factor WARK75 was found to be specifically expressed during natural and dark-induced leaf senescence. Functional analysis demonstrated that in detached leaves senescence under darkness was significantly delayed while no phenotypic consequences could be observed on growth and development, including no effect on natural leaf senescence,. Thus, WARKY75 is suggested to have a role in dark-induced senescence, but not in natural senescence. Another regulatory gene identified to have a role in senescence is MKK9 encoding for a Mitogen-Activated Protein Kinase Kinase 9 which is upregulated during senescence in harvested leaves as well as in naturally senescing leaves. MKK9 can specifically phosphorylate another kinase, MPK6. Both knockouts of MKK9 and MPK6 displayed a significantly senescence delay in harvested leaves and possibly function as a phosphorelay that regulates senescence. To our knowledge, this is the first report that clearly demonstrates the involvement of a MAP kinase pathway in senescence. This research not only revealed a new signal transduction pathway, but more important provided significant insights into the regulatory mechanisms underlying senescence in harvested leaves. In an additional line of research we have employed the promoter of the senescence-induced BFN1 gene as a handle for identifying components of the regulatory mechanism. This gene was shown to be activated during darkinduced senescence of detached leaves, as well as natural senescence. This was shown by following protein accumulation and promoter activity which demonstrated that this promoter is activated during dark-induced senescence. Analysis of the promoter established that, at least some of the regulatory sequences reside in an 80 bps long fragment of the promoter. Overall, progress was made in identification of components with a role in dark-induced senescence in this project. Further studies should be done in order to better understand the function of these components and develop approaches for modulating the progress of senescence in crop plants for the benefit of agriculture.
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Aharoni, Asaph, Zhangjun Fei, Efraim Lewinsohn, Arthur Schaffer, and Yaakov Tadmor. System Approach to Understanding the Metabolic Diversity in Melon. United States Department of Agriculture, July 2013. http://dx.doi.org/10.32747/2013.7593400.bard.
Full textAbstract:
Fruit quality is determined by numerous genetic factors that affect taste, aroma, color, texture, nutritional value and shelf life. To unravel the genetic components involved in the metabolic pathways behind these traits, the major goal of the project was to identify novel genes that are involved in, or that regulate, these pathways using correlation analysis between genotype, metabolite and gene expression data. The original and specific research objectives were: (1) Collection of replicated fruit from a population of 96 RI lines derived from parents distinguished by great diversity in fruit development and quality phenotypes, (2) Phenotypic and metabolic profiling of mature fruit from all 96 RI lines and their parents, (3) 454 pyrosequencing of cDNA representing mRNA of mature fruit from each line to facilitate gene expression analysis based on relative EST abundance, (4) Development of a database modeled after an existing database developed for tomato introgression lines (ILs) to facilitate online data analysis by members of this project and by researchers around the world. The main functions of the database will be to store and present metabolite and gene expression data so that correlations can be drawn between variation in target traits or metabolites across the RI population members and variation in gene expression to identify candidate genes which may impact phenotypic and chemical traits of interest, (5) Selection of RI lines for segregation and/or hybridization (crosses) analysis to ascertain whether or not genes associated with traits through gene expression/metabolite correlation analysis are indeed contributors to said traits. The overall research strategy was to utilize an available recombinant inbred population of melon (Cucumis melo L.) derived from phenotypically diverse parents and for which over 800 molecular markers have been mapped for the association of metabolic trait and gene expression QTLs. Transcriptomic data were obtained by high throughput sequencing using the Illumina platform instead of the originally planned 454 platform. The change was due to the fast advancement and proven advantages of the Illumina platform, as explained in the first annual scientific report. Metabolic data were collected using both targeted (sugars, organic acids, carotenoids) and non-targeted metabolomics analysis methodologies. Genes whose expression patterns were associated with variation of particular metabolites or fruit quality traits represent candidates for the molecular mechanisms that underlie them. Candidate genes that may encode enzymes catalyzingbiosynthetic steps in the production of volatile compounds of interest, downstream catabolic processes of aromatic amino acids and regulatory genes were selected and are in the process of functional analyses. Several of these are genes represent unanticipated effectors of compound accumulation that could not be identified using traditional approaches. According to the original plan, the Cucurbit Genomics Network (http://www.icugi.org/), developed through an earlier BARD project (IS-3333-02), was expanded to serve as a public portal for the extensive metabolomics and transcriptomic data resulting from the current project. Importantly, this database was also expanded to include genomic and metabolomic resources of all the cucurbit crops, including genomes of cucumber and watermelon, EST collections, genetic maps, metabolite data and additional information. In addition, the database provides tools enabling researchers to identify genes, the expression patterns of which correlate with traits of interest. The project has significantly expanded the existing EST resource for melon and provides new molecular tools for marker-assisted selection. This information will be opened to the public by the end of 2013, upon the first publication describing the transcriptomic and metabolomics resources developed through the project. In addition, well-characterized RI lines are available to enable targeted breeding for genes of interest. Segregation of the RI lines for specific metabolites of interest has been shown, demonstrating the utility in these lines and our new molecular and metabolic data as a basis for selection targeting specific flavor, quality, nutritional and/or defensive compounds. To summarize, all the specific goals of the project have been achieved and in many cases exceeded. Large scale trascriptomic and metabolomic resources have been developed for melon and will soon become available to the community. The usefulness of these has been validated. A number of novel genes involved in fruit ripening have been selected and are currently being functionally analyzed. We thus fully addressed our obligations to the project. In our view, however, the potential value of the project outcomes as ultimately manifested may be far greater than originally anticipated. The resources developed and expanded under this project, and the tools created for using them will enable us, and others, to continue to employ resulting data and discoveries in future studies with benefits both in basic and applied agricultural - scientific research.