AIMC Topic: Gossypium

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Monitoring and predicting cotton leaf diseases using deep learning approaches and mathematical models.

Scientific reports Jul 2, 2025
Cotton, the backbone of global textile production, demands sustainable agricultural practices to ensure fiber, food, and environmental security. Cotton crop play an essential role in farming economies; however, production is sometimes affected by var...
Plant Leaves Neural Networks, Computer Plant Diseases Gossypium Deep Learning Models, Theoretical
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Detection of cotton crops diseases using customized deep learning model.

Scientific reports Mar 28, 2025
The agricultural industry is experiencing revolutionary changes through the latest advances in artificial intelligence and deep learning-based technologies. These powerful tools are being used for a variety of tasks including crop yield estimation, c...
Plant Diseases Gossypium Agriculture Crops, Agricultural Algorithms Deep Learning Artificial Intelligence
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Analysis of the genetic basis of fiber-related traits and flowering time in upland cotton using machine learning.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik Jan 24, 2025
Cotton is an important crop for fiber production, but the genetic basis underlying key agronomic traits, such as fiber quality and flowering days, remains complex. While machine learning (ML) has shown great potential in uncovering the genetic archit...
Machine Learning Phenotype Gossypium Quantitative Trait Loci Flowers Genome-Wide Association Study Polymorphism, Single Nucleotide Cotton Fiber
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Detection of Verticillium infection in cotton leaves using ATR-FTIR spectroscopy coupled with machine learning algorithms.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Sep 12, 2024
Verticillium wilt (VW) is a soil-borne vascular disease that affects upland cotton and is caused by Verticillium dahliae Kleb. A rapid and user-friendly early diagnostic technique is essential for the preventing and controlling VW disease. In this st...
Support Vector Machine Spectroscopy, Fourier Transform Infrared Plant Leaves Machine Learning Algorithms Verticillium Plant Diseases Gossypium
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Machine learning ensembles, neural network, hybrid and sparse regression approaches for weather based rainfed cotton yield forecast.

International journal of biometeorology Apr 27, 2024
Cotton is a major economic crop predominantly cultivated under rainfed situations. The accurate prediction of cotton yield invariably helps farmers, industries, and policy makers. The final cotton yield is mostly determined by the weather patterns th...
Models, Theoretical Regression Analysis Gossypium Rain Weather Machine Learning Forecasting Neural Networks, Computer
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A Review of Successes and Impeding Challenges of IoT-Based Insect Pest Detection Systems for Estimating Agroecosystem Health and Productivity of Cotton.

Sensors (Basel, Switzerland) Apr 20, 2023
Using artificial intelligence (AI) and the IoT (Internet of Things) is a primary focus of applied engineering research to improve agricultural efficiency. This review paper summarizes the engagement of artificial intelligence models and IoT technique...
Gossypium Artificial Intelligence Algorithms Agriculture Insecta Animals
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Use of synthetic images for training a deep learning model for weed detection and biomass estimation in cotton.

Scientific reports Nov 15, 2022
Site-specific treatment of weeds in agricultural landscapes has been gaining importance in recent years due to economic savings and minimal impact on the environment. Different detection methods have been developed and tested for precision weed manag...
Biomass Deep Learning Neural Networks, Computer Poaceae Image Processing, Computer-Assisted Crops, Agricultural Plant Weeds Gossypium
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Supervised and Weakly Supervised Deep Learning for Segmentation and Counting of Cotton Bolls Using Proximal Imagery.

Sensors (Basel, Switzerland) May 12, 2022
The total boll count from a plant is one of the most important phenotypic traits for cotton breeding and is also an important factor for growers to estimate the final yield. With the recent advances in deep learning, many supervised learning approach...
Gossypium Plant Breeding Deep Learning
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Occurrence prediction of pests and diseases in cotton on the basis of weather factors by long short term memory network.

BMC bioinformatics Dec 24, 2019
BACKGROUND: The occurrence of cotton pests and diseases has always been an important factor affecting the total cotton production. Cotton has a great dependence on environmental factors during its growth, especially climate change. In recent years, m...
Neural Networks, Computer Gossypium Area Under Curve Climate Seasons Humidity Temperature Plant Diseases ROC Curve
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Artificial intelligence and regression analysis for Cd(II) ion biosorption from aqueous solution by Gossypium barbadense waste.

Environmental science and pollution research international Dec 12, 2017
In this study, batch biosorption experiments were conducted to determine the removal efficiency of Cd(II) ion from aqueous solutions by Gossypium barbadense waste. The biosorbent was characterized by Fourier transform infrared spectroscopy (FTIR) and...
Gossypium Adsorption Spectroscopy, Fourier Transform Infrared Cadmium Kinetics Regression Analysis Waste Products Water Pollutants, Chemical Particle Size Hydrogen-Ion Concentration Artificial Intelligence Water Purification
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