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

被引:15
作者
Duranovich, Federico N. [1 ]
Yule, Ian J. [2 ]
Lopez-Villalobos, Nicolas [1 ]
Shadbolt, Nicola M. [1 ]
Draganova, Ina [1 ]
Morris, Stephen T. [1 ]
机构
[1] Massey Univ, Sch Agr & Environm, Coll Sci, Private Bag 11-222, Palmerston North 4442, New Zealand
[2] Massey Univ, Sch Food & Adv Technol, Coll Sci, Massey AgriFood Digital Lab, Private Bag 11-222, Palmerston North 4442, New Zealand
来源
AGRONOMY-BASEL | 2020年 / 10卷 / 11期
关键词
proximal hyperspectral sensing; herbage nutritive value measurement; grazing management; partial-least squares regression; SPECTRAL REFLECTANCE; CANOPY REFLECTANCE; FEEDING VALUE; QUALITY; VARIABILITY; BIOMASS; VEGETATION; SELECTION; REGROWTH; PASTURES;
D O I
10.3390/agronomy10111826
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
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 from a dairy farm from July 2017 to May 2018. Hyperspectral data were pre-treated by applying a Savitzky-Golay filter followed by a Gap-segment derivative algorithm. Herbage samples were analyzed for determination of herbage nutritive value traits, digestible organic matter in dry matter (DOMD), metabolizable energy (ME), crude protein (CP), neutral detergent fiber (NDF) and acid detergent fiber (ADF). Partial least squares regression was performed to calibrate the spectra against the five nutritive value traits. Results indicate that accuracy was moderately high for the CP model (R-2 = 0.78) and moderate for the DOMD, ME, NDF and ADF models (0.54 < R-2 < 0.67). The possibility of being able to use proximal sensing for the estimation of herbage nutritive value in the field could potentially contribute to more efficient grazing management with potential economic benefits for the farm business.
引用
收藏
页数:15
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