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Acta Agriculturae Scandinavica, Section B — Soil & Plant Science Volume 67, 2017 - Issue 4
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Original Articles

Prediction of nutritive values, morphology and agronomic characteristics in forage maize using two applications of NIRS spectrometry

Mårten HettaDepartment of Agricultural Research for Northern Sweden, Swedish University of Agricultural Sciences, Umeå, SwedenCorrespondence[email protected]
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,
Zohaib MussadiqDepartment of Agricultural Research for Northern Sweden, Swedish University of Agricultural Sciences, Umeå, SwedenView further author information
,
Johanna WallstenDepartment of Agricultural Research for Northern Sweden, Swedish University of Agricultural Sciences, Umeå, SwedenView further author information
,
Magnus HallingDepartment of Crop Production Ecology, Swedish University of Agricultural Sciences, Uppsala, SwedenView further author information
,
Christian SwenssonDepartment of Biosystems and Technology, Swedish University of Agricultural Sciences, Alnarp, SwedenView further author information
&
Paul GeladiDepartment of Forest Biomaterials and Technology, Swedish University of Agricultural Sciences, Umeå, SwedenView further author information
Pages 326-333 | Received 19 Oct 2016, Accepted 30 Dec 2016, Published online: 18 Jan 2017

Citations (7)

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Read on this site (2)

Haruna Gado Yakubu, Zoltan Kovacs, Tamas Toth & George Bazar. (2022) The recent advances of near-infrared spectroscopy in dairy production—a review. Critical Reviews in Food Science and Nutrition 62:3, pages 810-831.
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Shengxiang Xu, Meiyan Wang & Xuezheng Shi. (2019) Comparison of multivariate models and variable selection algorithms for rapid analysis of the chemical composition of field crops. Acta Agriculturae Scandinavica, Section B — Soil & Plant Science 69:5, pages 452-464.
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Articles from other publishers (5)

Fei Gao, Yuejing Zhang & Xian Liu. (2022) A Study of the Reliability and Accuracy of the Real-Time Detection of Forage Maize Quality Using a Home-Built Near-Infrared Spectrometer. Foods 11:21, pages 3490.
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Xianguo Ren, Haiqing Tian, Kai Zhao, Dapeng Li, Ziqing Xiao, Yang Yu & Fei Liu. (2022) Research on pH Value Detection Method during Maize Silage Secondary Fermentation Based on Computer Vision. Agriculture 12:10, pages 1623.
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Silvia Parrini, Nicolina Staglianò, Riccardo Bozzi & Giovanni Argenti. (2021) Can Grassland Chemical Quality Be Quantified Using Transform Near-Infrared Spectroscopy?. Animals 12:1, pages 86.
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Lea Antonia Frey, Philipp Baumann, Helge Aasen, Bruno Studer & Roland Kölliker. (2020) A Non-destructive Method to Quantify Leaf Starch Content in Red Clover. Frontiers in Plant Science 11.
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Yang Gao, Junwei Qiu, Yanlong Miao, Ruicheng Qiu, Han Li & Man Zhang. (2019) Prediction of Leaf Water Content in Maize Seedlings Based on Hyperspectral Information. IFAC-PapersOnLine 52:30, pages 263-269.
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