Predicting nutritional content of native forage feed using ATR-FTIR and NIR chemometrics : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Nanoscience at Massey University, Manawatū, New Zealand
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Date
2024
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Massey University
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Abstract
Near infrared (NIR) reflectance spectroscopy has historically dominated the agriculture industry in the prediction of the nutritional content of pasture and forage in New Zealand. This study investigates using an alternative infrared reflectance technique in the mid infrared (MIR) region, Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy, and compares it to NIR, for the prediction of the chemical composition of native forage feed for sheep. Six native forage species and one non-native control species comprised 181 samples, which were recorded with both NIR and ATR-FTIR spectroscopy. Spectral pre-treatment was applied to all spectra in the form of a first-order Savitzky-Golay (SG) smoothening filter. Prediction of nutritional content for six analytes was achieved for both IR methods, using Principal Component Analysis (PCA) and a Partial Least Squares (PLS) regression model. The predictive ability of ATR-FTIR and NIR models was evaluated using the coefficient of determination (R²), Root Mean Square Error of Cross Validation (RMSECV), and Relative Performance Deviation (RPD). NIR had superior R2 and RPD, and similar RMSECV to ATR-FTIR for all analyte predictions. The best models were crude protein (CP) for NIR (R² : 0.95, RPD: 5.58) and metabolisable energy (ME) for FTIR (R² :0.79, RPD: 3.52). Post prediction statistics were also investigated for FTIR and NIR, finding that a ‘one size fits all’ blanket model for all species and tissue types was sufficient for quality prediction of CP, ME, and neutral detergent fiber (NDF) for native shrub species. These models suggested that ME and NDF predictions were similar between NIR and FTIR but NIR was superior to FTIR for CP. Overall, this study demonstrates the considerable potential of ATR-FTIR for quality nutritional content predictions, that are comparable to NIR.