Results 81 to 90 of about 59,485 (194)

Additive Variance and Open‐Pollinated Progenies Under Mixed Mating

Plant Breeding, EarlyView.
ABSTRACT Open‐pollinated progeny tests are still widely interpreted as if all the individuals within a maternal family were true half‐sibs. However, in species with mixed mating systems, this assumption is often biologically unrealistic and may bias the estimation of the additive variance, narrow‐sense heritability and expected selection gains.
Evandro Vagner Tambarussi
wiley   +1 more source

Delineating the glycoproteome of elongating cotton fiber cells

Data in Brief, 2015
The data presented here delineates the glycoproteome component in the elongating cotton fiber cells attained using complementary proteomic approaches followed by protein and N-linked glycosylation site identification (Kumar et al., 2013) [1].
Saravanan Kumar, Pankaj Pandey, Krishan Kumar, Vijayalakshmi Rajamani, Kethireddy Venkata Padmalatha, Gurusamy Dhandapani, Mogilicherla Kanakachari, Sadhu Leelavathi, Polumetla Ananda Kumar, Vanga Siva Reddy   +9 more
doaj   +1 more source

Cuticular Waxes in Altered Environments and Their Role in Leaf Water Loss Dynamics

Plant, Cell &Environment, EarlyView.
ABSTRACT Cuticular waxes undeniably form the primary barrier restricting uncontrolled water loss from leaves, yet the functional consequences of environmentally induced wax modifications for residual (cuticular) transpiration remain a matter of debate. This review summarises current knowledge on how major abiotic stimuli influence foliar cuticular wax ...
Lena Herzig, Lukas Schreiber, Paul Grünhofer   +2 more
wiley   +1 more source

Trichomes in Plant Defence, Development and Metabolic Integration Under Environmental Stress

Plant, Cell &Environment, EarlyView.
ABSTRACT Among various plant defence strategies, trichomes are tiny hair‐like structures on the epidermis that aid in defence, environmental adaptation and the production of valuable secondary metabolites. This review features trichomes as frontline guards for plant survival, integrating their structural, physiological and metabolic roles in ...
Debdatta Chatterjee, Madhabi Das, Sanjib Patra, Srijib Chatterjee, Amit Roy, Arunava Mandal   +5 more
wiley   +1 more source

Genome-Wide Mining and Identification of Protein Kinase Gene Family Impacts Salinity Stress Tolerance in Highly Dense Genetic Map Developed from Interspecific Cross between G. hirsutum L. and G. darwinii G. Watt

Agronomy, 2019
Abiotic stress is an important limiting factor in crop growth and yield around the world. Owing to the continued genetic erosion of the upland cotton germplasm due to intense selection and inbreeding, attention has shifted towards wild cotton progenitors
Muhammad Shehzad, Zhongli Zhou, Allah Ditta, Xiaoyan Cai, Majid Khan, Yanchao Xu, Yuqing Hou, Renhai Peng, Fushun Hao, Shafeeq-ur-rahman, Kunbo Wang, Fang Liu   +11 more
doaj   +1 more source

Genomic and Cytogenetic Analysis of Synthetic Polyploids between Diploid and Tetraploid Cotton (Gossypium) Species. [PDF]

Plants (Basel), 2023
Khidirov MT, Ernazarova DK, Rafieva FU, Ernazarova ZA, Toshpulatov AK, Umarov RF, Kholova MD, Oripova BB, Kudratova MK, Gapparov BM, Khidirova MM, Komilov DJ, Turaev OS, Udall JA, Yu JZ, Kushanov FN.   +15 more
europepmc   +1 more source

Harnessing Natural Diversity and Rational Design for Enhanced Plant Immunity

Plant, Cell &Environment, EarlyView.
ABSTRACT Plant pathogens cause crop loss. Genetic resistance, through natural genetic diversity or engineered resistance, can be highly effective in protecting plants from infection. Genetic resistance from wild relatives of crops has been successfully introduced into crops to control pathogen infection.
Nathan Diplock, Jennifer D. Lewis
wiley   +1 more source

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

The 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, Daeun Choi, Damian Adams, Jaehyun Ahn, Kelly Balmant, Raquel Dias, Carlos D. Messina, Rafael Muñoz‐Carpena, Vance M. Whitaker, Haipeng Yu, Ziwen Yu, Chang Zhao, Changying Li   +12 more
wiley   +1 more source

Drone‐based phenotyping of maize for multiple disease resistance and yield in breeding field trials

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Improving selection for multiple disease resistance (MDR) and yield in maize (Zea mays L.) requires high‐throughput, objective phenotyping tools, particularly under field conditions where several foliar diseases co‐occur. We evaluated drone‐based multispectral vegetation indices (VIs) for predicting resistance to northern leaf blight (NLB ...
Danilo E. Moreta, Nina Blahut, Nicholas Kaczmar, Judith M. Kolkman, Gary Bergstrom, Margaret Smith, Michael A. Gore, Rebecca Nelson   +7 more
wiley   +1 more source

Using ecoinformatics to evaluate the impact of crop and herbicide rotations on herbicide intensity

Pest Management Science, Volume 82, Issue 9, Page 8734-8746, September 2026.
Maize fields with cotton in rotation receive lower herbicide application than fields without cotton. Abstract BACKGROUND Crop rotation is a central component of integrated weed management (IWM) under real‐world conditions, yet its impact on herbicide use remains unclear. To address this challenge, we developed an ecoinformatics‐driven analysis approach
Shlomi Aharon, Ran Nisim Lati, Hanan Eizenberg, Eitan Goldshtein, Yafit Cohen   +4 more
wiley   +1 more source