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Full-Text Articles in Life Sciences
Regenerating Agricultural Landscapes With Perennial Groundcover For Intensive Crop Production, Kenneth J. Moore, Robert P. Anex, Amani E. Elobeid, Shuizhang Fei, Cornelia B. Flora, A. Susana Goggi, Keri L. Jacobs, Prashant Jha, Amy L. Kaleita, Douglas L. Karlen, David A. Laird, Andrew W. Lenssen, Thomas Lubberstedt, Marshall D. Mcdaniel, D. Raj Raman, Sharon L. Weyers
Regenerating Agricultural Landscapes With Perennial Groundcover For Intensive Crop Production, Kenneth J. Moore, Robert P. Anex, Amani E. Elobeid, Shuizhang Fei, Cornelia B. Flora, A. Susana Goggi, Keri L. Jacobs, Prashant Jha, Amy L. Kaleita, Douglas L. Karlen, David A. Laird, Andrew W. Lenssen, Thomas Lubberstedt, Marshall D. Mcdaniel, D. Raj Raman, Sharon L. Weyers
Douglas L Karlen
The Midwestern U.S. landscape is one of the most highly altered and intensively managed ecosystems in the country. The predominant crops grown are maize (Zea mays L.) and soybean [Glycine max (L.) Merr]. They are typically grown as monocrops in a simple yearly rotation or with multiple years of maize (2 to 3) followed by a single year of soybean. This system is highly productive because the crops and management systems have been well adapted to the regional growing conditions through substantial public and private investment. Furthermore, markets and supporting infrastructure are highly developed for both crops. As maize and …
Mid To Late Season Weed Detection In Soybean Production Fields Using Unmanned Aerial Vehicle And Machine Learning, Arun Narenthiran Veeranampalayam Sivakumar
Mid To Late Season Weed Detection In Soybean Production Fields Using Unmanned Aerial Vehicle And Machine Learning, Arun Narenthiran Veeranampalayam Sivakumar
Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research
Mid-late season weeds are those that escape the early season herbicide applications and those that emerge late in the season. They might not affect the crop yield, but if uncontrolled, will produce a large number of seeds causing problems in the subsequent years. In this study, high-resolution aerial imagery of mid-season weeds in soybean fields was captured using an unmanned aerial vehicle (UAV) and the performance of two different automated weed detection approaches – patch-based classification and object detection was studied for site-specific weed management. For the patch-based classification approach, several conventional machine learning models on Haralick texture features were …
Rapid Profiling Of Soybean Aromatic Compounds Using Electronic Nose, Ramasamy Ravi, Ali Taheri, Durga Khandekar, Reneth Millas
Rapid Profiling Of Soybean Aromatic Compounds Using Electronic Nose, Ramasamy Ravi, Ali Taheri, Durga Khandekar, Reneth Millas
Agricultural and Environmental Sciences Faculty Research
Soybean (Glycine max (L.)) is the world’s most important seed legume, which contributes to 25% of global edible oil, and about two-thirds of the world’s protein concentrate for livestock feeding. One of the factors that limit soybean’s utilization as a major source of protein for humans is its characteristic soy flavor. This off-flavor can be attributed to the presence of various chemicals such as phenols, aldehydes, ketones, furans, alcohols, and amines. In addition, these flavor compounds interact with protein and cause the formation of new off-flavors. Hence, studying the chemical profile of soybean seeds is an important step in understanding …