Machine and deep learning: Artificial intelligence application in biotic and abiotic stress management in plants

C Gou, S Zafar, N Fatima, Z Hasnain, N Aslam… - Frontiers in Bioscience …, 2024 - osti.gov
Biotic and abiotic stresses significantly affect plant fitness, resulting in a serious loss in food
production. Biotic and abiotic stresses predominantly affect metabolite biosynthesis, gene …

Image‐based assessment of plant disease progression identifies new genetic loci for resistance to Ralstonia solanacearum in tomato

V Meline, DL Caldwell, BS Kim, RS Khangura… - The Plant …, 2023 - Wiley Online Library
SUMMARY A major challenge in global crop production is mitigating yield loss due to plant
diseases. One of the best strategies to control these losses is through breeding for disease …

A deep learning model for predicting risks of crop pests and diseases from sequential environmental data

S Lee, CM Yun - Plant Methods, 2023 - Springer
Crop pests reduce productivity, so managing them through early detection and prevention is
essential. Data from various modalities are being used to predict crop diseases by applying …

A field study integrating plant physiology-soil response for quantifying wilting and plant survival time in a polymer-amended soil

B Rattan, M Shankar, A Garg, L Sahoo, S Pekkat… - Soil and Tillage …, 2025 - Elsevier
Water deficiency caused by climate change is a global challenge for food security. Viable
sustainable alternatives for enhancing water storage in the soil is a necessity for arid and …

Integrated web portal for non-destructive salt sensitivity detection of Camelina sativa seeds using fluorescent and visible light images coupled with machine learning …

E Vello, M Letourneau, J Aguirre… - Frontiers in Plant …, 2024 - frontiersin.org
Climate change has created unprecedented stresses in the agricultural sector, driving the
necessity of adapting agricultural practices and develo** novel solutions to the food crisis …

[HTML][HTML] A Quantitative Index for Evaluating Maize Leaf Wilting and Its Sustainable Application in Drought Resistance Screening

L Zhang, H Tang, X **/24602604/1/files/43411407.pdf" data-clk="hl=ko&sa=T&oi=gga&ct=gga&cd=9&d=13491723631051090784&ei=1hqvZ7WEHI_B6rQPrNOHuAc" data-clk-atid="YCuLBCk7PLsJ" target="_blank">[PDF] purdue.edu

Machine Learning for Spacecraft Time-Series Anomaly Detection and Plant Phenoty**

S Baireddy - 2023 - hammer.purdue.edu
Detecting anomalies in spacecraft time-series data is a high priority, especially considering
the harshness of the spacecraft operating environment. These anomalies often function as …