Potential of imaging spectroscopy as tool for pasture management

• Published in: Grass and forage science Vol. 60; no. 1; pp. 34 - 45
• Main Authors: Schut, A.G.T, Lokhorst, C, Hendriks, M.M.W.B, Kornet, J.G, Kasper, G
• Format: Journal Article
• Language: English
• Published: Oxford, UK Blackwell Science Ltd 01-03-2005
• Subjects: biomass; chemical-composition; deficiency; dry matter content; feeding value; grass swards; herbage; herbage mass; herbage quality; imaging spectroscopy; infrared reflectance spectroscopy; Lolium perenne; mass; mineral composition of herbage; mineral content; nirs; nitrogen; nutritive value; pasture management; quality; reflectance; regression; Netherlands
• ISSN: 0142-5242; 1365-2494
• DOI: 10.1111/j.1365-2494.2005.00449.x

The use of imaging spectroscopy to predict the herbage mass of dry matter (DM), DM content of herbage and crude fibre, ash, total sugars and mineral (N, P, K, S, Ca, Mg, Mn, Zn and Fe) concentrations was evaluated. The experimental system used measured reflectance between 404 and 1650 nm at high spatial (0·28-1·45 mm2) and spectral resolution. Data from two experiments with Lolium perenne L. mini-swards were used where the degree of sward damage or N-fertilizer application varied. Regression models were calibrated and validated and the potential reduction in prediction error with multiple observations was estimated. The mean prediction errors for DM mass, DM content and N, total sugars, ash and crude fibre concentrations were 235-268 kg ha-1, 9·6-16·8 g kg-1, 2·4-3·4 g kg DM-1, 16·2-27·7 g kg DM-1, 5·8-6·5 g kg DM-1 and 8·4-10·4 g kg DM-1 respectively. The predictions for concentrations of P, K, S and Mg allowed identification of deficiency levels, in contrast to the concentrations of Na, Zn, Mn and Ca which could not be predicted with adequate precision. Prediction errors of DM mass may be maximally reduced to 95-142 kg ha-1 with 25 replicate measurements per field. It is concluded that imaging spectroscopy can provide an accurate means for assessment of DM mass of standing grass herbage. Predictions of macronutrient content and feeding value were satisfactory. The methodology requires further evaluation under field conditions.