Results 161 to 170 of about 22,984 (222)

Effects of foliar nitrogen application on morphological and physiological characteristics in newly emerged leaves of <i>Bambusa emeiensis</i>. [PDF]

Front Plant Sci
Feng J, Wang D, Wang X, Yu B, Yu L, Fan H, Li L, Zhan H, Wang S, Li L.   +9 more
europepmc   +1 more source

Selection of native Atlantic Forest species for urban greening under air pollution stress

Restoration Ecology, EarlyView.
Abstract Introduction The Air Pollution Tolerance Index (APTI) is widely used to identify pollution‐tolerant species for afforestation; however, it was not designed to account for traits such as pollutant accumulation or biomass storage, which are also relevant for evaluating environmental resilience.
Ricardo K. Nakazato, Marisia P. E. Soeiro, Mirian C. S. Rinaldi, Eduardo L. M. Catharino, Eduardo H. P. Barretto, Eduardo P. C. Gomes, Mauricio L. Ferreira, Marisa Domingos   +7 more
wiley   +1 more source

Foliar application of nano-NPK and calcium-boron during the 'off-year' season enhances yield, improves oil quality, and mitigates biennial bearing in 'Picual' olive cultivar. [PDF]

BMC Plant Biol
Shaban A, Korkar HM, Ahmed I, El-Hamied AGA, Hmmam I.   +4 more
europepmc   +1 more source

SMART: Speedy Measurement of Arabidopsis Rosette Traits

The 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, Allison E. Harris, Jiamei Li, Fiona L. Goggin, David G. Mendoza‐Cozatl, Alexander Bucksch   +5 more
wiley   +1 more source

Nano zinc oxide (ZnO) foliar nutrition improves yield, antioxidant defence, and zinc content in rice grown under Zn-deficient soil. [PDF]

Discov Nano
Rajendran G, Quadriya H, Shanmugam V, Vakada M, Kuchi S, Durbha SR, Pc L, Parmar B, Sonth B, Mbb PB, Palaniappan K, Raman Meenakshi S.   +11 more
europepmc   +1 more source

Phenotypic scoring of canola blackleg severity using machine learning image analysis

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Canola blackleg is a fungal disease that causes significant yield loss and plant death of infected canola (Brassica napus L., Brassica rapa L., Brassica juncea L.) fields worldwide. One of the most effective methods for controlling blackleg is through the cultivation of resistant varieties.
Qiao Hu, Sarah Anderson, Stuart Gardner, Thomas W. Ernst, Chadwick B. Koscielny, Navratan S. Bahia, Charles G. Johnson Jr, Andrew C. Jarvis, Joseph S. Hynek, Nathan Coles, Igor Falak, David R. Charne, Manuel E. Ruidiaz, Julien Linares, Anastasios Mazis, Daniel J. Stanton   +15 more
wiley   +1 more source

CKM-YOLO11: A Lightweight Maize Foliar Disease Detection Model for Complex Natural Field Environments. [PDF]

Sensors (Basel)
Zhu H, Xiao F, Xiang J, Guo J, Mu H.
europepmc   +1 more source

Developing and deploying an unmanned aerial system–based phenotyping program for maturity to support soybean breeding

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Soybean [Glycine max (L.) Merr.] varieties are categorized into different relative maturity groups (MGs) that correspond to the approximate region that the variety is best adapted. Maturity is an important trait that growers consider when deciding which varieties to plant and for breeders as a covariate to compare genotypes.
Nathaniel Burner, Leonardo M. Bastos, Zenglu Li   +2 more
wiley   +1 more source

Flowering and Flower Maturation in Valley Oak <i>Quercus lobata</i>. [PDF]

Ecol Evol
Koenig WD, Pearse IS, Pesendorfer MB, Carmen WJ, Knops JMH.   +4 more
europepmc   +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