Results 111 to 120 of about 3,348 (213)

Philosophy of phenomic prediction and its incompatibility with causal inference

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Breeding programs need to make decisions frequently to improve populations and develop varieties efficiently. These needs led to the development of genomic prediction in the early 2000s and phenomic prediction in the mid‐2010s. In practice, phenomic prediction techniques rely on the same statistical tools and computational frameworks as other ...
Mitchell J. Feldmann, Fangyi Wang, Daniel E. Runcie   +2 more
wiley   +1 more source

Phenomics: Emerging Artificial Intelligence Tool in Crop Improvement

International Journal of Environment and Climate Change
Phenomics, which involves the holistic analysis of plant phenotypes using cutting-edge sensing and data processing technologies, has emerged as an AI-powered technique in plant breeding. Genomics tells us about a plant's genetic potential, whereas phenomics describes the dynamic manifestation of the genes under different environmental conditions.
N. Vairam, N. Murugan
openaire   +1 more source

LabEmbryoCam: An opensource phenotyping system for developing aquatic animals

HardwareX
Phenomics is the acquisition of high-dimensional data on an individual-wide scale and is proving transformational in areas of biological research related to human health including medicine and the crop sciences.
Ziad Ibbini, Maria Bruning, Sakina Allili, Luke A Holmes, Ellen Tully, Jamie McCoy, Benjamin Larsen, Tony Wilson, Guy Ludford, Jack Barrett-Kelly, John I. Spicer, Oliver Tills   +11 more
doaj   +1 more source

Bayesian optimized color filter: A fast method for segmentation of plant phenotypes from 3D point cloud images

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Multispectral three‐dimensional (3D) imaging offers substantial potential for plant phenotyping, yet manual segmentation of plant organs remains a bottleneck in breeding programs. We developed a color‐based filtering workflow for faba bean (Vicia faba L.) point clouds that optimizes lower and upper thresholds of spectral indices and broadband ...
Lennart Scheer, Benjamin Wittkop, Andreas Stahl, Olaf Sass, Gregor Welna, Hanna Tietgen, Rod J. Snowdon   +6 more
wiley   +1 more source

Genotype selection in soybean using WAASB and MTSI for seed yield, composition, and fatty acid profiles under irrigated and rainfed conditions

Agrosystems, Geosciences &Environment, Volume 9, Issue 3, September 2026.
Abstract Soybean (Glycine max) seed yield and quality are strongly affected by drought, particularly during reproductive stages. We evaluated 22 genotypes under irrigated and rainfed conditions across three Missouri environments (2023–2024) for seed yield, 100 seed weight, protein, oil, and five fatty acids. Mixed models were used to partition genotype,
Francia Ravelombola, Harmeet Singh‐Bakala, Cheryl Adeva, Maiara de Oliveira, Destiny Hunt, Ben Fallen, Grover Shannon, Feng Lin   +7 more
wiley   +1 more source

Integrating Genomics and Phenomics in Agricultural Breeding: A Comprehensive Review [PDF]

One of the key roles of plant breeders is to improve crop productivity through development of varieties with desirable traits to feed the growing population. The merger of genomics and phenomics - where genomics refer to the study of an organism’s entire
Shakshi, Singh, Mukesh Kumar, Yadav, Sachin, Srivastava, R P   +3 more
core   +1 more source

Optimization of γ-Aminobutyric Acid Production in Brown Rice via Prolonged Seed Priming

Plants
Germinated whole seeds possess elevated levels of bioactive nutrients; however, their application is hindered by several constraints. The germination process is typically time-consuming, and germinated seeds present challenges in terms of storage and ...
Lingxiang Xu, Xiaoan Wang, Qixiang Li, Yuqing Niu, Guohui Ding, Jiawei He, Weiping Chen, Dagang Tian   +7 more
doaj   +1 more source

Genomic Innovations in High‐Oil Soybean Breeding: Overcoming Yield Barriers and Climate Resilience Challenges

Legume Science, Volume 8, Issue 3, September 2026.
ABSTRACT Soybean (Glycine max L.) is the world's most important oilseed crop, supplying 25% of world‘s edible oil and 66% of feed protein. This review address genomic innovations to overcome yield constraints and climate vulnerability (especially drought stress) in high‐oil soybean breeding.
Mujeeb Ur Rehman, Muhammad Azam, Muhammad Ahsan, Azhar Iqbal, Lili Yu, Jhon Larzabal, Juan E. Rosas, Li‐Juan Qiu   +7 more
wiley   +1 more source

Advancing Thermotolerance in Beans: Integrating Physiology, Genomics, and Breeding for Climate Adaptation

Legume Science, Volume 8, Issue 3, September 2026.
ABSTRACT Rising global temperatures increasingly threaten bean production and the food security of millions of people who depend on these protein‐rich legumes. Heat stress during the reproductive stages induces pollen sterility, flower abscission, and disruptions in source–sink relationships, resulting in yield losses of 30%–40% or more when critical ...
Aastha Sharda, Shikha Chaudhary, Bhawna Kumari, Uday C. Jha, Mohar Singh, Inderjit Singh, Kamal Dev Sharma, Kadambot H. M. Siddique, P. V. Vara Prasad, Harsh Nayyar   +9 more
wiley   +1 more source

Genome–phenome association prediction using weighted deep matrix factorization with a multisource graph attention network

Quantitative Biology, Volume 14, Issue 3, September 2026.
Abstract Genome–phenome association (GPA) prediction can broaden the understanding of biological mechanisms underlying complex phenotypic traits (e.g., diseases and agronomic traits). Traditional deep matrix factorization (DMF)‐based GPA methods can integrate multiple data types and uncover nonlinear associations but often rely on low‐dimensional ...
Ran Duan, Wei Cao, Maozu Guo, Le Tian, Lingling Zhao   +4 more
wiley   +1 more source