Zobrazeno 1 - 10 of 226 pro vyhledávání: '"W. Franzen"'
1
Akademický článek
Fertilizer Management Strategies of Glycine max L. (Soybean) in Northcentral and North-Western North Dakota
Autor: Christopher Lee Augustin, David W. Franzen
Publikováno v: Agronomy, Vol 14, Iss 3, p 545 (2024)
Soybean (Glycine max L.) is a new cash crop grown in north central and northwestern North Dakota (ND). Soils and climate in these new soybean areas differ from current fertilizer guidelines. A three-year study to evaluate soybean fertility best manag
Externí odkaz: https://doaj.org/article/472a8d0bfa144e8fa0165948f5da149c
Zobrazit plný text záznamu
2
Akademický článek
Evaluating Critical Nitrogen Dilution Curves for Assessing Maize Nitrogen Status across the US Midwest
Autor: Hui Shao, Yuxin Miao, Fabián G. Fernández, Newell R. Kitchen, Curtis J. Ransom, James J. Camberato, Paul R. Carter, Richard B. Ferguson, David W. Franzen, Carrie A. M. Laboski, Emerson D. Nafziger, John E. Sawyer, John F. Shanahan
Publikováno v: Agronomy, Vol 13, Iss 7, p 1948 (2023)
Plant N concentration (PNC) has been commonly used to guide farmers in assessing maize (Zea mays L.) N status and making in-season N fertilization decisions. However, PNC varies based on the development stage. Therefore, a relationship between biomas
Externí odkaz: https://doaj.org/article/dd0564f1b50741e79acd12a212e58ec8
Zobrazit plný text záznamu
3
Akademický článek
Do crops' responses to sulfur vary with its forms?
Autor: Diksha Goyal, David W. Franzen, Amitava Chatterjee
Publikováno v: Agrosystems, Geosciences & Environment, Vol 4, Iss 3, Pp n/a-n/a (2021)
Abstract The most common formsof S fertilizers in the northern Great Plains are ammonium sulfate (AS), ammonium thiosulfate (ATS), and elemental S (ES). Among these, AS is preferred over the others because of its readily available SO42– form, and i
Externí odkaz: https://doaj.org/article/1d0485127b104ef18e7d8556560ed8ed
Zobrazit plný text záznamu
4
Akademický článek
Corn Nitrogen Nutrition Index Prediction Improved by Integrating Genetic, Environmental, and Management Factors with Active Canopy Sensing Using Machine Learning
Autor: Dan Li, Yuxin Miao, Curtis J. Ransom, Gregory Mac Bean, Newell R. Kitchen, Fabián G. Fernández, John E. Sawyer, James J. Camberato, Paul R. Carter, Richard B. Ferguson, David W. Franzen, Carrie A. M. Laboski, Emerson D. Nafziger, John F. Shanahan
Publikováno v: Remote Sensing, Vol 14, Iss 2, p 394 (2022)
Accurate nitrogen (N) diagnosis early in the growing season across diverse soil, weather, and management conditions is challenging. Strategies using multi-source data are hypothesized to perform significantly better than approaches using crop sensing
Externí odkaz: https://doaj.org/article/e02d778071434c8b8b9a5ae8d79759e2
Zobrazit plný text záznamu
7
Akademický článek
Active-Optical Sensors Using Red NDVI Compared to Red Edge NDVI for Prediction of Corn Grain Yield in North Dakota, U.S.A.
Autor: Lakesh K. Sharma, Honggang Bu, Anne Denton, David W. Franzen
Publikováno v: Sensors, Vol 15, Iss 11, Pp 27832-27853 (2015)
Active-optical sensor readings from an N non-limiting area standard established within a farm field are used to predict yield in the standard. Lower yield predictions from sensor readings obtained from other parts of the field outside of the N non-li
Externí odkaz: https://doaj.org/article/4874323b07814c9b9aaa9c754119a4ea
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje