Researchers have characterized a low-cost optical sensor prototype using visible and near-infrared reflectance spectroscopy to rapidly quantify nitrogen, phosphorus, and ...
Researchers established an aerial remote sensing framework combining red edge vegetation indices and machine learning feature selection to diagnose rice ...
Researchers synthesized findings from sixty studies and two real-world case studies to introduce a data-trust reference architecture for secure cross-organizational ...
Researchers have demonstrated that cross-architecture knowledge distillation enables lightweight mobile models to classify sixty-three dahlia cultivars with 97.51 percent accuracy ...
A lightweight MobileNet model achieved 95.76 percent accuracy in identifying tomato leaf diseases across ten classes, offering an efficient diagnostic ...
A PRISMA-based systematic review of 43 studies published between 2016 and 2025 classifies energy-efficient routing protocols for agricultural wireless sensor ...
A systematic review of IoT and AI-enabled microclimate regulation in poultry farming demonstrates that predictive climate management can achieve thermal ...
A hybrid deep-learning model classified 32 insect species from 4,800 recordings with 99.90% accuracy on the InsectSet32 dataset, but independent ...
A computational benchmarking study found that I-YOLOv8-MCGIRNet outperformed comparison models in tested pig-face recognition, detection and counting tasks, while cross-dataset ...
An international model estimates that smart-farming technologies are already profitable on 42% of global cropland and could pay off on ...
A new lightweight deep learning model called WheatNet detects and counts individual wheat seedlings in complex field images with record ...
A sweeping review of 1,081 studies from 2014 to 2024 shows convolutional neural networks rapidly becoming the world's leading tool ...
A field-validated IoT platform in Türkiye unifies crop monitoring, irrigation scheduling and solar management for agrivoltaic farms.
A new end-to-end AI detector called SFM-DETR combines Mamba state space modeling with frequency-domain analysis to identify maize seedlings and ...
A new taxonomy-aware segmentation framework links every diseased pixel to both its host crop and its disease, delivering state-of-the-art results ...
Researchers have developed a hyperspectral deep learning framework, STAMPformer, that non-destructively predicts continuous frost damage severity in field-grown tea plants ...
Researchers have built a multilingual transformer-based AI system that diagnoses crop diseases, generates farming advice, and delivers market intelligence while ...
A systematic review finds that blockchain, IoT and artificial intelligence are transforming food supply chains, with integrated digital frameworks offering ...
A five-season study shows that GNSS distance data from ordinary baling machinery can predict how many bales remain in a ...
In an era where technological advances have permeated various sectors, the integration of artificial intelligence (AI) into agriculture is revolutionizing ...
