Results 131 to 140 of about 1,669,707 (267)

(Poly)phenols: Mechanisms of action and efficacy of contemporary supplements for exercise recovery and performance

open access: yesExperimental Physiology, EarlyView.
Abstract (Poly)phenols are a diverse group of bioactive chemical compounds present in a wide range of plant‐ and animal‐based foods. Several thousands of (poly)phenols exist; many have potent biological effects, most notably antioxidant, anti‐inflammatory and vasodilatory.
Glyn Howatson, Tom Clifford
wiley   +1 more source

Characterization of Novel Luteoviruses in Canadian Highbush Blueberries Using High-Throughput Sequencing

open access: yesViruses
The Fraser Valley of British Columbia, Canada is among the top ten blueberry producing regions globally. Viral diseases are established in the region and significantly reduce average yields.
Sachithrani Kannangara   +7 more
doaj   +1 more source

Integrated Metabolic and Transcriptomic Profiles Furnish Insights to Flavonoid Variation in Dendrobium officinale From Different Areas in China

open access: yeseFood, Volume 7, Issue 6, December 2026.
Zhejiang‐sourced D. officinale exhibits superior flavonoid content. Integrated metabolomic and transcriptomic analyses reveal key genes regulating flavonoid biosynthesis, elucidating the geographical impact on quality. ABSTRACT Dendrobium officinale (D.
Ziying Wang   +6 more
wiley   +1 more source

Polinização do mirtilo (Vaccinium corymbosum L.) (Ericaceae) cultivares Misty e O'neal no município de Itá, Oeste de SC. [PDF]

open access: yes, 2007
TCC (graduação em Agronomia) - Universidade Federal de Santa Catarina, Centro de Ciências Agrárias, 2007O mirtilo (Vaccinium spp.) (Ericaceae), também conhecido como blueberry, em inglês ou arándano, em espanhol é uma espécie recentemente introduzida em ...
Sezerino, André Amarildo
core  

Artificial intelligence‐powered plant phenomics: Progress, challenges, and opportunities

open access: yesThe Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Artificial intelligence (AI), a key driver of the Fourth Industrial Revolution, is being rapidly integrated into plant phenomics to automate sensing, accelerate data analysis, and support decision‐making in phenomic prediction and genomic selection.
Xu Wang   +12 more
wiley   +1 more source

SMART: Speedy Measurement of Arabidopsis Rosette Traits

open access: yesThe Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Most computer vision‐ and machine learning‐based plant phenotyping systems compute traits such as shape and size rather than the color distribution of the plant surface, even though color can provide important insights into plant physiology. Therefore, we developed Speedy Measurement of Arabidopsis Rosette Traits (SMART), an open‐source plant ...
Suxing Liu   +5 more
wiley   +1 more source

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

open access: yesThe 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   +8 more
wiley   +1 more source

Blueberry plants support a distinctive microbiome as a function of plant genetics and tissue

open access: yes
Abstract Background Fruits, such as blueberries, are critical for food production and ecosystem sustainability as they are largely consumed by humans and animals worldwide. The microbial communities (bacteria, archaea, and fungi) within and on the surface of these fruits play a key role in regulating food quality, alongside supporting crucial ...
Matteo Giese   +10 more
openaire   +1 more source

Philosophy of phenomic prediction and its incompatibility with causal inference

open access: yesThe 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   +2 more
wiley   +1 more source

Time course sensor‐based phenotyping can predict Ascochyta blight disease severity in Cicer species

open access: yesThe Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Ascochyta blight is a widely occurring chickpea fungal disease that can cause severe yield loss. Breeding for crop resistance benefits from high‐throughput evaluation of plant–pathogen interactions in genotypes which can serve as sources of resistance.
Florian Tanner   +9 more
wiley   +1 more source

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