Use of traditional, modern, and hybrid modelling approaches for in situ prediction of dry matter yield and nutritive characteristics of pasture using hyperspectral datasets
Anna L Thomson, Senani B Karunaratne, Amy Copland, Danielle Stayches, Elizabeth Morse McNabb, Joe Jacobs
ANIMAL FEED SCIENCE AND TECHNOLOGY | ELSEVIER | Published : 2020
To optimise grazing livestock nutrition, it is necessary to know both the available dry matter yield and the nutritive characteristics of pasture at the farm-scale in near real time. Previous studies have shown the potential of using field spectrophotometers that measure the reflectance of light across the visible to near infrared spectrums to gather information on pasture dry matter yield (DMY) and nutritive characteristics. This study sought to calibrate and validate new mathematical models for ten parameters including dry matter yield and nine nutritive characteristics of relevance to ruminant nutrition. As a part of the analysis process, two innovative approaches were tested: the use of ..View full abstract
The work was supported by the Dairy Feedbase Program. A joint venture between Dairy Australia, Gardiner Dairy Foundation and Agriculture Victoria.