Using Proximal Hyperspectral Sensing to Predict Herbage Nutritive Value for Dairy Farming

Using Proximal Hyperspectral Sensing to Predict Herbage Nutritive Value for Dairy Farming

This study focuses on calibrating and validating models for hyperspectral canopy reflectance data that are useful to predict the nutritive value of ryegrass-white clover mixed herbage available to the grazing cow. Hyperspectral measurements and herbage cuts were collected from 286 sampling plots fro...

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Bibliographic Details
Main Authors:	Federico N. Duranovich, Ian J. Yule, Nicolas Lopez-Villalobos, Nicola M. Shadbolt, Ina Draganova, Stephen T. Morris
Format:	Article
Language:	English
Published:	MDPI AG 2020-11-01
Series:	Agronomy
Subjects:	proximal hyperspectral sensing herbage nutritive value measurement grazing management partial-least squares regression
Online Access:	https://www.mdpi.com/2073-4395/10/11/1826

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