Results 101 to 110 of about 1,165,106 (235)

Image-Based Assessment of Drought Response in Grapevines

Frontiers in Plant Science, 2020
Many plants can modify their leaf profile rapidly in response to environmental stress. Image-based data are increasingly used to retrieve reliable information on plant water status in a non-contact manner that has the potential to be scaled to high ...
Nunzio Briglia, Kevin Williams, Dan Wu, Yaochen Li, Sha Tao, Fiona Corke, Giuseppe Montanaro, Angelo Petrozza, Davide Amato, Francesco Cellini, John H. Doonan, Wanneng Yang, Wanneng Yang, Vitale Nuzzo   +13 more
doaj   +1 more source

Trait ontology analysis based on association mapping studies bridges the gap between crop genomics and Phenomics

BMC Genomics, 2019
Trait ontology (TO) analysis is a powerful system for functional annotation and enrichment analysis of genes. However, given the complexity of the molecular mechanisms underlying phenomes, only a few hundred gene-to-TO relationships in plants have been ...
Qingchun Pan, Junfeng Wei, Feng Guo, Suiyong Huang, Y. Gong, H. Liu, Jianxiao Liu, Lin Li   +7 more
semanticscholar   +1 more source

Affordable Phenomics special topic—Foreword for The Plant Phenome Journal

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract The Affordable Phenomics special topic in The Plant Phenome Journal showcased recent advances that expand the accessibility, cost‐effectiveness, and scalability of plant phenotyping technologies. This collection of 15 articles presented innovative approaches, ranging from low‐cost sensors and open‐source analytical pipelines to artificial ...
Valerio Hoyos‐Villegas, Michael A. Gore   +1 more
wiley   +1 more source

A highly accurate, low‐cost method for detecting and quantifying soybean leaf flipping phenotype during drought stress

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract A genome‐wide association study (GWAS) using digital images was conducted to delineate regions of the genome that govern the leaf flipping quantitative trait in soybean (Glycine max (L.) Merr). However, converting the digital data to numerical scores for downstream analyses was challenging.
Mohammad Anisur Rahaman, Atit Parajuli, Adnan Hossain Khan, Liang Dong, Madan K Bhattacharyya   +4 more
wiley   +1 more source

Interpretable Deep Learning applied to Plant Stress Phenotyping [PDF]

, 2017
Availability of an explainable deep learning model that can be applied to practical real world scenarios and in turn, can consistently, rapidly and accurately identify specific and minute traits in applicable fields of biological sciences, is scarce ...
Blystone, David, Ganapathysubramanian, Baskar, Ganapathysubramanian, Baskar, Ghosal, Sambuddha, Sarkar, Soumik, Singh, Arti, Singh, Asheesh, Singh, Asheesh   +7 more
core   +3 more sources

Spatial and temporal scales in plant phenotyping for crop water stress assessment: A review

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Water stress is a major limiting factor for crop productivity worldwide, and its impacts are intensifying due to climate variability and increasing water scarcity. This review focuses on the spatial and temporal scales in plant phenotyping as a critical approach to improving crop water‐stress assessment and supporting precision water ...
Daniel Kingsley Cudjoe, Yazhou Sun, Sanai Li, Wenxuan Guo   +3 more
wiley   +1 more source

Finding Our Way through Phenotypes [PDF]

, 2015
Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing ...
Anzaldo, Salvatore S., Ashburner, Michael, Balhoff, James P., Blackburn, David C., Blake, Judith A., Burleigh, J. Gordon, Chanet, Bruno, Cooper, Laurel D., Courtot, Mélanie, Csösz, Sándor, Cui, Hong, Deans, Andrew R., Huala, Eva, Lewis, Suzanna E., Others, Smith, Barry   +15 more
core  

Predicting soybean aboveground biomass in the short‐season region of Canada: Integrating vegetative cover and canopy height

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Aboveground biomass (ABM) is a key determinant of soybean (Glycine max [L.] Merr.) yield and can be used to select for stress‐resilient cultivars. The objective of our study was to develop a predictive model describing ABM in short‐season soybean from vegetative cover (VC) and canopy height (CH).
Malcolm J. Morrison, Thomas L. Hotte, A. Claire Gahagan, Nathaniel W. W. Ort, Elroy R. Cober   +4 more
wiley   +1 more source

Combining phenomic and genomic selection for pea breeding improvement

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Pea (Pisum sativum L.) is a strategic crop in the development of sustainable agriculture. However, the genetic gain remains limited despite advances in breeding. Genomic selection holds promise to accelerate varietal improvement, but its high implementation cost restricts its use in crops.
Anthony Klein, Virgilio Freitas, Abdou Wade, Grégoire Aubert, Myriam Naudet‐Huart, Michael Touratier, Jennifer Régulier, Jean‐François Herbommez, Catherine Kraut, Guillaume Roullet, Aude Carlier‐Lézie, Nadim Tayeh, Renaud Rincent, Philippe Dufour, Judith Burstin, Gaëtan Touzy   +15 more
wiley   +1 more source

Unmanned aerial vehicle–based spatiotemporal phenotyping and growth modeling for forecasting potato yield

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Monitoring spatial variations in plant growth and forecasting yield before harvest provides valuable insights for optimizing agronomic decision‐making in potato (Solanum tuberosum L.) cultivation. Although unmanned aerial vehicle (UAV)‐based remote sensing has recently enabled the development of tuber fresh weight (TW) estimation models, their
Yuto Imachi, Kunihiro Tanaka, Minato Miyauchi, Kyosuke Miyamoto, Masahiro Okada, Pieter M. Blok, Wei Guo, Hiroyoshi Iwata   +7 more
wiley   +1 more source