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AI And Satellites Reveal Wildebeest Migration Numbers Are Far Lower Than Believed

For the first time, scientists have used AI and satellite imagery to count the Great Wildebeest Migration, finding fewer than 600,000 animals, less than half the long-standing estimate of 1.3 million. The results highlight new conservation challenges and a breakthrough in wildlife monitoring.

10 Sep 2025

AI And Drone Imaging Predict Wheat Yields With Unmatched Accuracy

This study developed a transformer-based AI model using UAV multispectral and RGB imaging to predict wheat yields with unprecedented accuracy. The approach allows non-destructive, cost-effective, and early identification of high-yield lines, speeding up breeding for climate-resilient wheat.

9 Sep 2025

AI-Powered Dashboard Helps Food Pantries Tackle Disaster Food Insecurity

University of Houston researchers are developing an AI-powered dashboard to help food pantries in Florida coordinate disaster relief and reach food-insecure families more efficiently. The $300,000 USDA-funded project builds on lessons from Hurricane Harvey and aims to expand nationwide.

19 Aug 2025

AI-Powered Model Pinpoints Human Impact on Dryland Water Use and Lake Loss

A new study presents an advanced remote sensing and machine learning model that accurately distinguishes between natural and human-driven water consumption in arid croplands. Findings from the Ebinur Lake Basin show agriculture now drives 77% of cropland water use, with profound implications for regional water security.

26 May 2025

Machine Learning Unlocks Secrets of Crab Seismic Courtship Dances

Male fiddler crabs use vibrational signals during courtship that honestly reflect their physical size, allowing females to assess mate quality from a distance. Oxford researchers used geophones and machine learning to decode over 8,000 seismic signals, revealing clear behavioural patterns.

10 Apr 2025

AI Models Break Barriers in Protein Discovery and Supercharge Precision Medicine

Researchers have developed two advanced AI models, InstaNovo and InstaNovo+, that significantly improve accuracy in de novo peptide sequencing. These tools surpass current methods in identifying unknown proteins, offering breakthroughs in proteomics and personalised medicine.

1 Apr 2025

AI and Big Data Drive the Future of Crop Breeding with Intelligent Precision

Researchers highlight how AI and big data are transforming crop breeding, ushering in "Breeding 4.0" with intelligent, data-driven precision to enhance global food security.

2 Mar 2025

Quantum Deep Learning Boosts Rice Yield Forecasting

A hybrid quantum deep learning model was developed for rice yield forecasting, combining quantum computing with BiLSTM and XGBoost techniques. This model significantly improved prediction accuracy, supporting global agricultural planning and food security efforts.

18 Aug 2024

Advanced ML Model Predicts Potato Blight

Machine learning models predicted potato leaf blight with 98.3% accuracy using over 4000 weather records. Techniques like K-means clustering, PCA, and copula analysis identified key weather factors. Feature selection significantly enhanced model precision, aiding proactive disease management in agriculture.

1 Aug 2024

Predicting Rice Production with Precision Using AI

Researchers in Scientific Reports introduced an AI-based approach to predict rice production in China using multi-source data. Hybrid models, particularly RF-XGB, outperformed single models in accuracy, emphasizing the importance of soil properties and sown area over climate variables in determining rice yields.

8 Jul 2024

Machine Learning Revolutionizes Plant Disease Detection

A recent article in "Artificial Intelligence in Agriculture" reviewed machine learning (ML) techniques for detecting plant diseases in apple, cassava, cotton, and potato crops. The study highlighted the superior accuracy of convolutional neural networks (CNNs) and emphasized ML's potential to enhance crop yield and quality, despite challenges related to data quality and ethical considerations.

22 May 2024

RST-Net: Advancing Plant Disease Prediction Using Enlightened Swin Transformer Networks

Researchers introduced RST-Net, a novel deep learning model for plant disease prediction, combining residual convolutional networks and Swin transformers. Testing on a benchmark dataset showed superior performance over state-of-the-art models, with potential applications in smart agriculture and precision farming.

24 Apr 2024

Enhanced Land Cover Classification in Remote Sensing

Chinese researchers introduce a groundbreaking deep inverse convolutional neural network approach tailored for land cover remote sensing images. This novel method effectively addresses data imbalance, significantly improving classification accuracy and precision, with potential applications in urban planning, agriculture, and environmental monitoring.

2 Apr 2024

LC-Net: Revolutionizing Plant Phenotyping with CNNs for Accurate Leaf Counting

This article introduces LC-Net, a novel convolutional neural network (CNN) model designed for precise leaf counting in rosette plants, addressing challenges in plant phenotyping. Leveraging SegNet for superior leaf segmentation, LC-Net incorporates both original and segmented leaf images, showcasing robustness and outperforming existing models in accurate leaf counting, offering a promising advancement for agricultural research and high-throughput plant breeding efforts.

24 Jan 2024

AI-Driven Robotic Crop Farming for Sustainability

Researchers propose an AI-powered robotic crop farm, Agrorobotix, utilizing deep reinforcement learning (DRL) for enhanced urban agriculture. Tested in simulated conditions, Agrorobotix showcased a 16.3% increase in crop yield, 21.7% reduced water usage, and a 33% decline in chemical usage compared to conventional methods, highlighting its potential to transform urban farming, improve food security, and contribute to smart city development.

3 Jan 2024

Deep Learning for Disease Detection in Cauliflower Plants

This study, published in Nature, explores the application of Convolutional Neural Networks (CNN) to identify and detect diseases in cauliflower crops. By using advanced deep-learning models and extensive image datasets, the research achieved high accuracy in disease classification, offering the potential to enhance agricultural efficiency and ensure food security.

31 Oct 2023

Leveraging Artificial Intelligence for Food Security: A Comprehensive Review

This paper delves into the extensive use of artificial intelligence (AI) models for assessing food security indicators across the globe, with a notable focus on sub-Saharan Africa. The study emphasizes the importance of stakeholder involvement in AI modeling for food security, highlighting three key approaches to integrating AI into food security research.

29 Oct 2023

Harnessing Machine Learning for Drought-Resistant Crops

Researchers explore the power of machine learning models to predict effective microbial strains for combatting drought's impact on crop production. By comparing various models, the study reveals that gradient boosted trees (GBTs) offer high accuracy, though considerations of computational resources and application needs are vital when choosing a model for real-world implementation.

21 Aug 2023

Enhancing Winter Wheat Water Management with Machine Learning

Researchers devise interpretable and non-interpretable ML models optimized by particle swarm optimization to accurately estimate crop evapotranspiration for winter wheat. By utilizing limited meteorological data, these models offer insights into water usage and agricultural sustainability, aiding water management practices in the face of climate challenges.

17 Aug 2023

Top AI Algorithms for Sheep Weight Prediction: Revolutionizing Animal Husbandry

Researchers evaluated various machine learning algorithms to predict sheep body weights, highlighting the effectiveness of models like MARS, BRR, ridge regression, SVM, and gradient boosting for improving animal production decisions, ensuring economic growth and food security. Their study showcases the potential of AI in transforming animal husbandry practices.

17 Aug 2023