Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Seyed Vahid Mirnezami"'
Publikováno v:
International Journal of Recycling of Organic Waste in Agriculture, Vol 3, Iss 2 (2024)
Background Making powder from whey is one of the most challenging parts of whey processing. The present study investigates the performance of a spray dryer for the preparation of whey powder. Its main objective is to categorize unknown samples using
Externí odkaz:
https://doaj.org/article/d50c9fef3b214e42ae1771672565fe5e
Autor:
Seyed Vahid Mirnezami, Srikant Srinivasan, Yan Zhou, Patrick S. Schnable, Baskar Ganapathysubramanian
Publikováno v:
Plant Phenomics, Vol 2021 (2021)
The tassel of the maize plant is responsible for the production and dispersal of pollen for subsequent capture by the silk (stigma) and fertilization of the ovules. Both the amount and timing of pollen shed are physiological traits that impact the pr
Externí odkaz:
https://doaj.org/article/e61e4076c5dc4d7f8c1e39ad2924203a
Autor:
Koushik Nagasubramanian, Talukder Jubery, Fateme Fotouhi Ardakani, Seyed Vahid Mirnezami, Asheesh K Singh, Arti Singh, Soumik Sarkar, Baskar Ganapathysubramanian
Publikováno v:
Plant Phenome Journal, Vol 4, Iss 1, Pp n/a-n/a (2021)
Abstract Deep learning models have been successfully deployed for a diverse array of image‐based plant phenotyping applications including disease detection and classification. However, successful deployment of supervised deep learning models requir
Externí odkaz:
https://doaj.org/article/1ce4128f51e34cfa91aaea434685c8f2
Autor:
Seyed Vahid Mirnezami, Therin Young, Teshale Assefa, Shelby Prichard, Koushik Nagasubramanian, Kulbir Sandhu, Soumik Sarkar, Sriram Sundararajan, Matt E. O’Neal, Baskar Ganapathysubramanian, Arti Singh
Publikováno v:
Applications in Plant Sciences, Vol 8, Iss 7, Pp n/a-n/a (2020)
Premise Trichomes are hair‐like appendages extending from the plant epidermis. They serve many important biotic roles, including interference with herbivore movement. Characterizing the number, density, and distribution of trichomes can provide val
Externí odkaz:
https://doaj.org/article/6e44cd50b42348fb86c5e020c457c9bf
Publikováno v:
Transactions of the ASABE. 63:1969-1980
HighlightsCorn damage detection was possible using advanced deep learning and computer vision techniques trained with images of simulated corn lodging.RetinaNet and YOLOv2 both worked well at identifying regions of lodged corn.Automating crop damage
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a7c6af1e2f39a52396e4beb434e55087
https://doi.org/10.13031/trans.13791
https://doi.org/10.13031/trans.13791
Autor:
Seyed Vahid Mirnezami, Timothy K. Egner, Lin Ma, Oskar Siemianowski, Yichao Shi, Kara R. Lind, Vincenzo Venditti, Ludovico Cademartiri, Bin Yuan, Baskar Ganapathysubramanian
Publikováno v:
Proceedings of the National Academy of Sciences. 116:11063-11068
Root phenotypes are increasingly explored as predictors of crop performance but are still challenging to characterize. Media that mimic field conditions (e.g., soil, sand) are opaque to most forms of radiation, while transparent media do not provide
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::175c166d2c67f8f9fa8b7eea1ca7c523
https://doi.org/10.1073/pnas.1820334116
https://doi.org/10.1073/pnas.1820334116
Autor:
Seyed Vahid Mirnezami, Aaron Kusmec, Lakshmi Attigala, Talukder Z. Jubery, Yan Zhou, Baskar Ganapathysubramanian, James C. Schnable, Maria G. Salas-Fernandez, Srikant Srinivasan, Patrick S. Schnable
Publikováno v:
Plant Cell
The accuracy of trait measurements greatly affects the quality of genetic analyses. During automated phenotyping, trait measurement errors, i.e. differences between automatically extracted trait values and ground truth, are often treated as random ef
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::339ce788614dc95b7f705c586143089a
https://europepmc.org/articles/PMC8408462/
https://europepmc.org/articles/PMC8408462/
Autor:
Arti Singh, Talukder Z. Jubery, Asheesh K. Singh, Baskar Ganapathysubramanian, Seyed Vahid Mirnezami, Koushik Nagasubramanian, Fateme Fotouhi Ardakani, Soumik Sarkar
Publikováno v:
Plant Phenome Journal, Vol 4, Iss 1, Pp n/a-n/a (2021)
Deep learning models have been successfully deployed for a diverse array of image‐based plant phenotyping applications including disease detection and classification. However, successful deployment of supervised deep learning models requires large
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::88cee0aa0b704df0ad023ff5eb139538
https://doaj.org/article/1ce4128f51e34cfa91aaea434685c8f2
https://doaj.org/article/1ce4128f51e34cfa91aaea434685c8f2
Autor:
Therin J. Young, Koushik Nagasubramanian, Jiaoping Zhang, William T. Schapaugh, Seyed Vahid Mirnezami, Sarah Jones, Kevin G. Falk, Matthew E. Carroll, Arti Singh, Clayton N. Carley, Johnathon M. Shook, Baskar Ganapathysubramanian, Soumik Sarkar, Fernando E. Miguez, Liza Van der Laan, Kyle A. Parmley, Asheesh K. Singh, Kevin O. Chiteri, Talukder Z. Jubery, Mariana Victoria Chiozza, Ashlyn M. Rairdin
Publikováno v:
Concepts and Strategies in Plant Sciences ISBN: 9783030737337
Soybean [Glycine max (L.) Merr.] breeders and geneticists routinely evaluate thousands of plots per year in order to characterize various accessions and breeding populations for a multitude of traits, for example, morphological, physiological, abioti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3147aaf01dea0e036c4f82e16b2ac6ab
https://doi.org/10.1007/978-3-030-73734-4_7
https://doi.org/10.1007/978-3-030-73734-4_7
Publikováno v:
ICVISP
Apricot which is a cultivated type of Zerdali (wild apricot) has an important place in human nutrition and its medical properties are essential for human health. The objective of this research was to obtain a model for apricot mass and separate apric
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ce45c660732030259892205a50e3ff60
https://doi.org/10.1145/3448823.3448856
https://doi.org/10.1145/3448823.3448856