Results 201 to 210 of about 52,638 (264)

UAV‐based deep transfer learning to improve grain yield prediction in winter wheat across temporal and spatial variability

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Accurate prediction of grain yield (GY) remains a major challenge in plant breeding due to complex interactions between genotype, environment, and management (G × E × M) factors. Remote sensing data from unmanned aerial vehicles (UAVs) equipped with multispectral sensors have emerged as a pivotal resource for high‐throughput phenotyping.
Swas Kaushal, Mohammad Maruf Billah, Mandeep Singh, Dante Koupal, Pradeep Raj Sitaula, Jyotirmoy Halder, Jagdeep Sidhu, Maitiniyazi Maimaitijiang, Sunish K. Sehgal   +8 more
wiley   +1 more source

Genome-Wide Identification and Expression Analysis of Starch Biosynthesis-Related Gene Families in Wheat. [PDF]

Int J Mol Sci
Zhao Q, Hu L, Wu X, Ma B, Song W, Nie X, Lv S.   +6 more
europepmc   +1 more source

Assessing robustness and transferability of image‐based semantic segmentation models for major field crops

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Plant breeding is essential for crop improvement, yet progress is often hindered by slow, laborious, and subjective field phenotyping methods. High‐throughput phenotyping (HTP), particularly image‐based methodologies powered by machine learning, offers a pathway to overcome these limitations.
Gustavo N. Santiago, Pedro Cisdeli, German Mandrini, Mitchell Tuinstra, Ignacio A. Ciampitti   +4 more
wiley   +1 more source

pyRootHair: Machine learning accelerated software for high-throughput phenotyping of plant root hair traits. [PDF]

Gigascience
Tsang I, Percival-Alwyn L, Rawsthorne S, Cockram J, Leigh F, Atkinson JA.   +5 more
europepmc   +1 more source

AGIcam: An open‐source Internet of Things–based camera system for automated in‐field phenotyping and yield prediction

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Continuous, high‐frequency monitoring is essential to capture rapid phenological transitions and dynamic crop responses to the environment. However, most phenotyping platforms lack the temporal resolution and automation required for consistent, season‐long trait assessment.
Worasit Sangjan, Nisit Pukrongta, Trevor Buchanan, Arron H. Carter, Michael O. Pumphrey, Sindhuja Sankaran   +5 more
wiley   +1 more source

Selenium and Sulphur as Elements Modifying Plant Quality: Assessment of the Content of Organic and Mineral Nitrogen Forms in Wheat. [PDF]

Molecules
Brodowska MS, Kurzyna-Szklarek M, Wyszkowski M.   +2 more
europepmc   +1 more source

BerryBox: An affordable computer vision system for postharvest phenotyping of cranberry and other small fruits

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Fruit size, shape, color, and percent fruit rot are important quality traits for breeding cranberry (Vaccinium macrocarpon Ait.). Image analysis can be used to measure these traits, but affordable hardware for standardized image capture and integrated user‐friendly software pipelines are lacking.
Jeffrey L. Neyhart, Collins Wakholi, Devin A. Rippner, John H. Price, Kayla R. Altendorf, Garett C. Heineck, Juan Zalapa, Jenyne Loarca, Gina M. Sideli   +8 more
wiley   +1 more source

Ligation-Driven Electrochemical Magneto-Genoassay Platform Based on PNA Probes for the Multiple Detection of Soy and Mustard DNA in Wheat Flour. [PDF]

Biosensors (Basel)
Fortunati S, Nazir S, Biondi F, Amariglio M, Tosi E, Corradini R, Donofrio G, Lambertini F, Suman M, Manicardi A, Giannetto M, Careri M.   +11 more
europepmc   +1 more source

Induced Mutagenesis Improves Grain Protein and Micronutrient (Fe and Zn) Content in Spring Wheat (<i>Triticum aestivum</i> L.). [PDF]

Biology (Basel)
Gulina D, Saule K, Dinara Z, Saule A, Malika A, Sabina S, Saltanat A, Khava Y.   +7 more
europepmc   +1 more source

Identification of resistance sources and genomic regions regulating spot blotch resistance in Asian bread wheat (Triticum aestivum L.) via genome-wide association study. [PDF]

Plant Genome
Aggarwal N, He X, Rathore M, Jan F, Gupta V, Mir RR, Singh PK.   +6 more
europepmc   +1 more source