Results 201 to 210 of about 189,164 (223)

The progressive modernization of cassava breeding programs at International Institute of Tropical Agriculture and future prospects

Crop Science, Volume 66, Issue 2, March/April 2026.
Abstract Modernizing cassava breeding programs (CBPs) is critical to increase genetic gain, close the yield gap, and ensure food availability, accessibility, and affordability to support livelihood transformation and economic development in sub‐Saharan Africa (SSA).
Edwige Gaby Nkouaya Mbanjo, Afolabi Agbona, John Derera, Alick Mulenga, Ibnou Dieng, Béla Teeken, Hapson Mushoriwa, Jim Lorenzen, Chiedozie Egesi, Peter Kulakow, Ismail Yusuf Rabbi   +10 more
wiley   +1 more source

Revolutionizing hyper spectral image denoising: a squeezenet paradigm. [PDF]

Sci Rep
Nachimuthu N, Murugesan R, Dharmalingam M, Prakash G.   +3 more
europepmc   +1 more source

Target identification with hyperspectral lidar

, 2015
Matleena Myntti
openalex   +1 more source

Drone‐imaging assisted genome‐wide association studies reveal key quantitative trait loci for emergence and late blight resistance in tetraploid potato

Crop Science, Volume 66, Issue 2, March/April 2026.
Abstract Solanum tuberosum L. (potato) is the world's most important vegetable crop, and developing improved cultivars is paramount for global food security. The efficacy of the genomic prediction models that accelerate breeding and genome‐wide association studies (GWAS) depends on large, high‐quality phenotypic datasets, which are often associated ...
Trine Aalborg, Mathias Timmermann Christiansen, Hélène Romé, Aakash Chawade, Merethe Bagge, Kåre Lehmann Nielsen   +5 more
wiley   +1 more source

Hyperspectral coherent anti-Stokes Raman scattering volumetric projection microscopy for assessing drug-cell interaction. [PDF]

Biomed Opt Express
Zhang C, Li Y, Yang Q, Fang Y, Zhang G, Zhou S, Hu R, Qu J, Liu L.   +8 more
europepmc   +1 more source

Noise Learning of Instruments for High-contrast, High-resolution and Fast Hyperspectral Microscopy and Nanoscopy

Hao He, Maofeng Cao, Yun Gao, Peng Zheng, Sen Yan, Jin‐Hui Zhong, Lei Wang, Dayong Jin, Bin Ren   +8 more
openalex   +1 more source

Remote sensing and machine learning models to assess and predict turfgrass performance and soil water stress under deficit irrigation for creeping bentgrass

Crop Science, Volume 66, Issue 2, March/April 2026.
Abstract Turfgrass management faces challenges related to water scarcity, making it essential to explore innovative technologies, such as remote sensing and machine learning (ML), to monitor turf quality (TQ) and soil moisture levels effectively. The objective of this study was to develop ML models using unmanned aerial vehicle and imagery technology ...
Haoguang Yang, Devan Gladden, Stephanie Rossi, Bingru Huang   +3 more
wiley   +1 more source

Hyperspectral imaging with machine learning for non-destructive prediction of quality attributes in Lanzhou frozen pears. [PDF]

Food Chem X
Qiao W, Yang M, Hu J, Yan H, Guo Y, Guo F.   +5 more
europepmc   +1 more source

Estimating Plant Species Richness With Sentinel and Landsat Data Across Ecosystems in China

Ecology and Evolution, Volume 16, Issue 3, March 2026.
438 field plots were used to estimate plant diversity across ecosystems; 18 spectral indices were derived from Sentinel and Landsat data; EVI, DVI, PSRI, NDVI, PRI, GNDVI, and GMEVI were identified as powerful indicators for predicting plant alpha diversity.
Keman Wang, Yu Peng, Ying Ye, Yue Qi, Lizheng He   +4 more
wiley   +1 more source

A Uav-based multisensor framework for legal industrial Cannabis monitoring and open-access dataset development. [PDF]

Data Brief
Rexha G, Papadhopulli I, Biberaj A, Agastra E, Sheme E, Meçe E.   +5 more
europepmc   +1 more source