[HTML][HTML] Challenges and opportunities in machine-augmented plant stress phenotyping
Plant stress phenotyping is essential to select stress-resistant varieties and develop better
stress-management strategies. Standardization of visual assessments and deployment of …
stress-management strategies. Standardization of visual assessments and deployment of …
[HTML][HTML] Wild relatives of maize, rice, cotton, and soybean: treasure troves for tolerance to biotic and abiotic stresses
J Mammadov, R Buyyarapu, SK Guttikonda… - Frontiers in plant …, 2018 - frontiersin.org
Global food demand is expected to nearly double by 2050 due to an increase in the world's
population. The Green Revolution has played a key role in the past century by increasing …
population. The Green Revolution has played a key role in the past century by increasing …
The global burden of pathogens and pests on major food crops
S Savary, L Willocquet, SJ Pethybridge… - Nature ecology & …, 2019 - nature.com
Crop pathogens and pests reduce the yield and quality of agricultural production. They
cause substantial economic losses and reduce food security at household, national and …
cause substantial economic losses and reduce food security at household, national and …
Soybean yield loss estimates due to diseases in the United States and Ontario, Canada, from 2015 to 2019
CA Bradley, TW Allen, AJ Sisson… - Plant Health …, 2021 - Am Phytopath Society
Soybean (Glycine max L. Merrill) yield losses as a result of plant diseases were estimated by
university and government plant pathologists in 29 soybean producing states in the United …
university and government plant pathologists in 29 soybean producing states in the United …
An explainable deep machine vision framework for plant stress phenotyping
Current approaches for accurate identification, classification, and quantification of biotic and
abiotic stresses in crop research and production are predominantly visual and require …
abiotic stresses in crop research and production are predominantly visual and require …
[HTML][HTML] Plant disease identification using explainable 3D deep learning on hyperspectral images
Background Hyperspectral imaging is emerging as a promising approach for plant disease
identification. The large and possibly redundant information contained in hyperspectral data …
identification. The large and possibly redundant information contained in hyperspectral data …
Soybean yield loss estimates due to diseases in the United States and Ontario, Canada, from 2010 to 2014
TW Allen, CA Bradley, AJ Sisson… - Plant Health …, 2017 - Am Phytopath Society
Annual decreases in soybean (Glycine max L. Merrill) yield caused by diseases were
estimated by surveying university-affiliated plant pathologists in 28 soybean-producing …
estimated by surveying university-affiliated plant pathologists in 28 soybean-producing …
SoyNet: Soybean leaf diseases classification
A Karlekar, A Seal - Computers and Electronics in Agriculture, 2020 - Elsevier
According to studies, the human population would cross 9 billion by 2050 and the food
demand would increase by 60%. Therefore, increasing and improving the quality of the crop …
demand would increase by 60%. Therefore, increasing and improving the quality of the crop …
[HTML][HTML] Dissecting the economic impact of soybean diseases in the United States over two decades
Soybean (Glycine max L. Merrill) is an economically important commodity for United States
agriculture. Nonetheless, the profitability of soybean production has been negatively …
agriculture. Nonetheless, the profitability of soybean production has been negatively …
[HTML][HTML] Hyperspectral band selection using genetic algorithm and support vector machines for early identification of charcoal rot disease in soybean stems
Background Charcoal rot is a fungal disease that thrives in warm dry conditions and affects
the yield of soybeans and other important agronomic crops worldwide. There is a need for …
the yield of soybeans and other important agronomic crops worldwide. There is a need for …