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Development of a Wireless Computer Vision Instrument to Detect Biotic Stress in Wheat

Joaquin Casanova, Susan O'Shaughnessy, Steven Evett, Charles Rush
2014 Sensors  
Computer vision offers an inexpensive way to remotely detect crop stress independent of vegetation cover. This paper presents a technique using computer vision to detect disease stress in wheat.  ...  Vegetation hue obtained through a wireless computer vision system in this study is a viable option for determining biotic crop stress in irrigation scheduling.  ...  Texas AgriLife Extension Service, Texas Tech University, and West Texas A&M University.  ... 
doi:10.3390/s140917753 pmid:25251410 pmcid:PMC4208247 fatcat:li43m4w6frcpzkqxmbk54mmam4

Envirotyping for deciphering environmental impacts on crop plants

Yunbi Xu
2016 Theoretical and Applied Genetics  
, agronomic genomics, precision agriculture and breeding, and development of a fourdimensional profile of crop science involving genotype (G), phenotype (P), envirotype (E) and time (T) (developmental  ...  In the future, envirotyping needs to zoom into specific experimental plots and individual plants, along with the development of high-throughput and precision envirotyping platforms, to integrate genotypic  ...  Wheat rust Ug99, detected first in East Africa, is one of the best examples for disease prediction.  ... 
doi:10.1007/s00122-016-2691-5 pmid:26932121 pmcid:PMC4799247 fatcat:zxjrm6eifngtzobfsjjl7kqkpi

Computer Vision, IoT and Data Fusion for Crop Disease Detection Using Machine Learning: A Survey and Ongoing Research

Maryam Ouhami, Adel Hafiane, Youssef Es-Saady, Mohamed El Hajji, Raphael Canals
2021 Remote Sensing  
However, the increasing number and diversity of research studies requires a literature review for further developments and contributions in this area.  ...  In addition, this study examines the role of data fusion for ongoing research in the context of disease detection.  ...  In [90] , the authors developed a detection application using SPOT-6 images with a supervised classification algorithm called spectral angle mapper (SAM) to map powdery mildew of winter wheat.  ... 
doi:10.3390/rs13132486 fatcat:f6u2vvmgvjggrhoqsph6odas3i

Remote Sensing and Machine Learning in Crop Phenotyping and Management, with an Emphasis on Applications in Strawberry Farming

Caiwang Zheng, Amr Abd-Elrahman, Vance Whitaker
2021 Remote Sensing  
; (2) leaf and canopy attributes; (3) water stress; and (4) pest and disease detection.  ...  Meanwhile, computer vision and machine learning methodology have emerged as powerful tools for extracting useful biological information from image data.  ...  Additionally, studies related to the detection of abiotic and biotic stressors were developed.  ... 
doi:10.3390/rs13030531 fatcat:yts5pbuq2zhwrm6rt6c6hmkyti

Sensing technologies for precision specialty crop production

W.S. Lee, V. Alchanatis, C. Yang, M. Hirafuji, D. Moshou, C. Li
2010 Computers and Electronics in Agriculture  
to implement in the field scale and more complex to interpret.  ...  These factors can be measured using diverse types of sensors and instruments such as field-based electronic sensors, spectroradiometers, machine vision, airborne multispectral and hyperspectral remote  ...  Although the reported study was performed only with Sunagoke moss, this method could be extended to both biotic and abiotic stress detection in other plants.  ... 
doi:10.1016/j.compag.2010.08.005 fatcat:tesilbgowvf3vplcwgbcevmhyy

A Revisit of Internet of Things Technologies for Monitoring and Control Strategies in Smart Agriculture

Amjad Rehman, Tanzila Saba, Muhammad Kashif, Suliman Mohamed Fati, Saeed Ali Bahaj, Huma Choudhary
2022 Agronomy  
These radical developments are upending traditional agricultural practices and presenting new options in the face of various obstacles.  ...  IoT aids in collecting data that is useful in the farming sector, such as changes in climatic conditions, soil fertility, amount of water required for crops, irrigation, insect and pest detection, bug  ...  The authors also would like to acknowledge the support of Prince Sultan University for paying the Article Processing Charges (APC) of this publication.  ... 
doi:10.3390/agronomy12010127 fatcat:jwwmeooqcndthkuyduhwai2tae

The challenges posed by global broadacre crops in delivering smart agri-robotic solutions: A fundamental rethink is required

Bruce Donaldson Grieve, Tom Duckett, Martin Collison, Lesley Boyd, Jon West, Hujun Yin, Farshad Arvin, Simon Pearson
2019 Global Food Security  
The output can be accessed at:  ...  However, in common with all biotic stresses, this is not a static scenario as rusts are constantly evolving, shifting their severity profiles to overcome resistance and in some cases evolving tolerance  ...  The latter is key when considering extremely subtle measures, such as detecting the causes of abiotic or biotic stress symptoms (Mahlein et al., 2010) , identifying insect pests (Fennell et al., 2018  ... 
doi:10.1016/j.gfs.2019.04.011 fatcat:4722pga52jaazpft73chfgjzbe

UAS-Based Plant Phenotyping for Research and Breeding Applications

Wei Guo, Matthew E. Carroll, Arti Singh, Tyson L. Swetnam, Nirav Merchant, Soumik Sarkar, Asheesh K. Singh, Baskar Ganapathysubramanian
2021 Plant Phenomics  
This review provides a broad account of the state of the art in UAS-based phenotyping to reduce the barrier to entry to plant science practitioners interested in deploying this imaging modality for phenotyping  ...  Unmanned aircraft system (UAS) is a particularly powerful tool for plant phenotyping, due to reasonable cost of procurement and deployment, ease and flexibility for control and operation, ability to reconfigure  ...  Acknowledgments We thank all members of the ISU's Soynomics team for their feedback on this work. We also thank all technical specialists of the Institute for Sustainable Agro-ecosystem Services,  ... 
doi:10.34133/2021/9840192 fatcat:2jn6v4mscvf7dh355dof376tgm

Crop Phenomics: Current Status and Perspectives

Chunjiang Zhao, Ying Zhang, Jianjun Du, Xinyu Guo, Weiliang Wen, Shenghao Gu, Jinglu Wang, Jiangchuan Fan
2019 Frontiers in Plant Science  
With the rapid development in high-throughput phenotyping technologies, research in this area is entering a new era called 'phenomics.'  ...  Finally, we discussed the challenges and prospective of crop phenomics in order to provide suggestions to develop new methods of mining genes associated with important agronomic traits, and propose new  ...  In essence, deep convolutional neural networks (CNNs) are well suited to many vision-based computer problems, e.g., recognition (Lecun, 1990) , classification (He et al., 2015) , and instance detection  ... 
doi:10.3389/fpls.2019.00714 pmid:31214228 pmcid:PMC6557228 fatcat:kzqj3nvh3ndqxnhmrlyiwcihna

Phenomics – technologies to relieve the phenotyping bottleneck

Robert T. Furbank, Mark Tester
2011 Trends in Plant Science  
At the same time the impacts of climate change on global temperatures and rainfall patterns are likely to lead to reduction in yields due to abiotic stress [3] .  ...  Plant phenomics offers a suite of new technologies to accelerate progress in understanding gene function and environmental responses.  ...  Acknowledgements We thank Drs Bettina Berger and Xavier Sirault for valuable comments on the manuscript, and the funding agencies who have allowed the establishment of the Australian Plant Phenomics Facility  ... 
doi:10.1016/j.tplants.2011.09.005 pmid:22074787 fatcat:mh5uwult7ncxbagimo5s2ljyta

Role of Soil-Specific Farming in Converting Blue Water into Green Water [chapter]

2015 Soil-Specific Farming  
Research Area Nature of Contribution Key References GPS Technology adaptation to farming and testing Larsen et al. (1988) , , Tyler (1993) Machinery navigation and autosteer Technology development  ...  development and testing McCann and Stark (1993) , Fraisse (1994) , Evans et al. (1996) Research Area Nature of Contribution Key References Aerial remote sensing Ability to identify spatial patterns  ...  to the energy detected by the instrument (Leamer et al. 1973) .  ... 
doi:10.1201/b18759-19 fatcat:blpnoxxg3fhmlnsek7jqhcmw2u

Remote Sensing for Irrigation of Horticultural Crops

2017 Horticulturae  
detection.  ...  IN order to develop effective irrigation strategies, it is necessary to identify the appropriate indicators for monitoring crop water status at the farm level [27] .  ...  Each instrument is characterized by a specific number and widths of wavelengths detected; some instruments detect discrete bands, while others detect fairly narrow wavelengths or broader bands (multispectral  ... 
doi:10.3390/horticulturae3020040 fatcat:4axxl4k5yfagbdca6sojbu2baq

A Method for Detecting Coffee Leaf Rust through Wireless Sensor Networks, Remote Sensing, and Deep Learning: Case Study of the Caturra Variety in Colombia

David Velásquez, Alejandro Sánchez, Sebastian Sarmiento, Mauricio Toro, Mikel Maiza, Basilio Sierra
2020 Applied Sciences  
Failure to detect pathogens at an early stage can result in infestations that cause massive destruction of plantations and significantly damage the commercial value of the products.  ...  The most common way to detect this disease is by walking through the crop and performing a human visual inspection.  ...  In addition, we want to acknowledge the biology team, formed of undergraduate students Alisson Martínez and Laura Cristina Moreno and led by Luisa Fernanda Posada.  ... 
doi:10.3390/app10020697 fatcat:77kxbhumfre2rgl7fllgz7al4q

High-Throughput Plant Phenotyping Platform (HT3P) as a Novel Tool for Estimating Agronomic Traits From the Lab to the Field

Daoliang Li, Chaoqun Quan, Zhaoyang Song, Xiang Li, Guanghui Yu, Cheng Li, Akhter Muhammad
2021 Frontiers in Bioengineering and Biotechnology  
However, access to large-scale phenotypic data has now become a critical barrier that phenomics urgently must overcome.  ...  This review aims to provide ideas, thoughts, and insights for the optimal selection, exploitation, and utilization of HT3Ps, and thereby pave the way to break through current phenotyping bottlenecks in  ...  ACKNOWLEDGMENTS The authors would like to thank the editors and reviewers for their valuable input, time, and suggestions for improving the overall quality of the manuscript.  ... 
doi:10.3389/fbioe.2020.623705 pmid:33520974 pmcid:PMC7838587 fatcat:5rfrtcrkr5bcphaaemxrvle4ym

Molecular Predicting Drought Tolerance in Maize Inbred Lines by Machine Learning Approaches [article]

2019 bioRxiv   pre-print
Drought is one of the prime abiotic stresses in the world.  ...  A total of 356 SSR reproducible fragment alleles were detected across the 71 polymorphic SSR loci.  ...  ., Rush C.M. (2014) Development of a wireless computer vision instrument to detect biotic stress in wheat. Sensors (Basel), 14(9): 17753-17769.  ... 
doi:10.1101/578880 fatcat:5z3dr3xb2rbwdbjaz7gf7ftpwq
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