Výsledky vyhledávání - "Brian D. Luck"

Multitask Learning of Alfalfa Nutritive Value From UAV-Based Hyperspectral Images

Autor: Jessica L. Drewry, Yuchi Ma, Zhou Zhang, Parker Williams, Brian D. Luck, Qingyun Du, Yazhou Sun, Luwei Feng

Publikováno v: IEEE Geoscience and Remote Sensing Letters. 19:1-5

Alfalfa is a valuable and widely adapted forage crop, and its nutritive value directly affects animal performance and ultimately affects the profitability of livestock production. Traditional nutritive value measurement method is labor-intensive and

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c22c9bbc629a3643bed473afdba428f7
https://doi.org/10.1109/lgrs.2021.3079317

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Assessment of Digital Technology Adoption and Access Barriers Among Agricultural Service Providers and Agricultural Extension Professionals

Autor: Jessica L. Drewry, John M. Shutske, David Trechter, Brian D. Luck

Publikováno v: Journal of the ASABE. 65:1049-1059

HighlightsAgricultural service providers and Extension professionals were surveyed on technology use and barriers.Data privacy and security and hiring qualified IT staff are barriers in the industry.Surveys point to major opportunities for digital ag

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e6b9d4bbdb74a134a760a01e13ada140
https://doi.org/10.13031/ja.15018

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Closing wheel type and row unit downforce can affect corn germination in no‐tillage production systems

Autor: Francisco J. Arriaga, Jessica L. Drewry, Brian D. Luck

Publikováno v: Agronomy Journal. 113:4037-4046

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9dc45df0febcb72716fa8fa0ea843a8a
https://doi.org/10.1002/agj2.20774

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Predicting in situ dry matter disappearance of chopped and processed corn kernels using image-analysis techniques

Autor: Brian D. Luck, Rebeca M. Willett, Jessica L. Drewry, Randy D. Shaver, Luiz F. Ferraretto

Publikováno v: Applied Animal Science. 36:480-488

Objective Corn silage processing score (CSPS) is a well-known and often-used indicator of starch availability in whole-plant corn silage. However, obtaining results from a laboratory can take days or more. The objective of this work was to test an im

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b12094dda1925044f0ae7f417cb10a41
https://doi.org/10.15232/aas.2020-01993

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Impact of Planter Closing Wheels on Corn Emergence in No-Till Systems

Autor: Brian D. Luck, Francisco J. Arriaga, Jessica L. Drewry

Publikováno v: Applied Engineering in Agriculture. 36:727-732

HighlightsAftermarket closing wheels increased corn emergence by 2% over standard rubber wheels.Yield was not significant by closing wheel type.Abstract. Producers are increasingly adopting cover crops and no-till planting for a variety of reasons in

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::fcfbdccf3f234b714f00b79b050fc688
https://doi.org/10.13031/aea.13957

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Assessing kernel processing score of harvested corn silage in real-time using image analysis and machine learning

Autor: Eduardo M.C. Rocha, Jessica L. Drewry, Rebecca M. Willett, Brian D. Luck

Publikováno v: Computers and Electronics in Agriculture. 203:107415

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::31c55fb6f0031ab62e9fd4c60c82b661
https://doi.org/10.1016/j.compag.2022.107415

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Predicting kernel processing score of harvested and processed corn silage via image processing techniques

Autor: Joshua D. Harmon, Eduardo M. C. Rocha, Jessica L. Drewry, Rebecca Willett, Brian D. Luck

Publikováno v: Computers and Electronics in Agriculture. 160:144-152

An image processing algorithm was developed to characterize the size distribution of corn kernel particles from Whole Plant Corn Silage (WPCS). The algorithm determines particle cross sectional area and maximum inscribed circle diameter as well as cu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1da4d7d676e37acf1e044f5c7d2de09a
https://doi.org/10.1016/j.compag.2019.03.020

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Drones That Deliver: Pheromone-Based Mating Disruption Deployed via Uncrewed Aerial Vehicles in U.S. Cranberries

Autor: Brian D. Luck, Shawn A. Steffan, Parker Williams, Elissa M. Chasen

Publikováno v: Journal of economic entomology. 114(5)

Cranberry fruitworm (Acrobasis vaccinii Riley (Lepidoptera: Pyralidae)) and blackheaded fireworm (Rhopobota naevana Hubner (Lepidoptera: Tortricidae)) threaten cranberry production annually by causing significant fruit damage. Up to four pesticide ap

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::403f0b3f11314752c18fabe20306724f
https://pubmed.ncbi.nlm.nih.gov/34180532

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Alfalfa Yield Prediction Using UAV-Based Hyperspectral Imagery and Ensemble Learning

Autor: Luwei Feng, Qingyun Du, Parker Williams, Jessica L. Drewry, Brian D. Luck, Zhou Zhang, Yuchi Ma

Publikováno v: Remote Sensing, Vol 12, Iss 2028, p 2028 (2020)
Remote Sensing; Volume 12; Issue 12; Pages: 2028

Alfalfa is a valuable and intensively produced forage crop in the United States, and the timely estimation of its yield can inform precision management decisions. However, traditional yield assessment approaches are laborious and time-consuming, and

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::236099fc4446fbcb7d2ed3b244a5645a
https://www.mdpi.com/2072-4292/12/12/2028

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