Results 171 to 180 of about 78,873 (239)
YOLO-based deep learning framework for real-time multi-class plant health monitoring in precision agriculture. [PDF]
Rana A, Vaidya P.
europepmc +1 more source
This study presents a flexible, battery‐free passive RFID sensing platform for NLoS monitoring of quality deterioration in fresh agricultural products. It utilizes a structurally decoupled spiral antenna‐LC electrode architecture to suppress electromagnetic interference caused by packaging.
Guoping Hu +4 more
wiley +1 more source
MoringaLeafNet: A multi-class leaf disease dataset for precision agriculture and deep learning research. [PDF]
Preanto SA, Paul T, Khan A, Bijoy MHI.
europepmc +1 more source
SiDT1 Defines Plant Architecture Reminiscent of Green Revolution in Foxtail Millet
SiDT1 encodes a GA3‐oxidase that creates a semi‐dwarf, lodging‐resistant architecture reminiscent of the rice Green Revolution. The resulting ideotype performs well under dense planting and provides a valuable genetic resource for high‐yield, mechanized foxtail millet production. ABSTRACT Foxtail millet (Setaria italica) is a drought‐tolerant C4 cereal
Jianzhen Lv +13 more
wiley +1 more source
Plant leaf disease detection using vision transformers for precision agriculture. [PDF]
S M, R G.
europepmc +1 more source
Using grilled lamb skewers as a model system, this work builds a multiscale coupling framework from oral processing to retronasal aroma perception, reveals dual‐kinetic release patterns and Electroencephalogram‐characterized central encoding features, and proposes an interpretable physics‐guided deep learning model validated by multiphysics simulation,
Che Shen +12 more
wiley +1 more source
Advances in surface-enhanced Raman scattering applications for precision agriculture: monitoring plant health and crop quality. [PDF]
Nguyen HA +4 more
europepmc +1 more source
Ti‐doped Zr/Ti bimetallic MOFs activate neighboring Zr sites to selectively capture phospholipids from serum through cooperative interactions. In nontargeted screening, the material minimizes matrix interference, expands detectable feature coverage, and enables broad recovery of diverse chemical hazards, providing a powerful cleanup strategy for LC ...
Yanmin Liang +5 more
wiley +1 more source
Electrochemical (Bio)Sensors Based on Nanotechnologies for the Detection of Important Biomolecules in Plants and Plant-Related Samples: The Future of Smart and Precision Agriculture. [PDF]
Hosu IS, Fierăscu RC, Fierăscu I.
europepmc +1 more source

