Predicting Forage Nutritional Quality With Near-Infrared Spectroscopy Alessandro Benelli, Riccardo Primi, Chiara Evangelista, Raffaello Spina, Marco Milanesi, et al. Journal of Sustainable Agriculture and Environment, 2025 The quality of green forage is crucial in pasture grazing, influencing both animal welfare, environmental sustainability, and production yield. Traditionally, the evaluation of forage composition requires time‐consuming and costly chemical analysis. In this context, near‐infrared spectroscopy (NIR) emerges as a promising alternative. This study adopted Fourier transform NIR (FT‐NIR) spectroscopy to predict nutritional characteristics of green forages. A total of 324 samples were collected from pastures in central Italy. Partial least squares (PLS) regression models were then developed, applying variable selection methods to improve PLS model accuracy. The interval PLS (iPLS) variable selection method gave the best results for fresh forage, while the genetic algorithm (GA) performed best for dried samples. The best results from the PLS models were obtained for dry matter (DM) and crude protein (CP). The DM model for fresh forage yielded an R2P of 0.96 and an RMSEP of 2.95 g 100 g−1 FW, while the CP model for dried forage yielded an R2P of 0.94 and an RMSEP of 1.84 g 100 g−1 DW, with a normalised root‐mean‐square error of cross‐validation (NRMSECV) of 3.8% and 5.6%, respectively. The results for the neutral detergent fibre (aNDF) were acceptable. NIR spectroscopy has proven to be a useful tool for assessing forage nutritional quality. Variable selection through iPLS also enabled the identification of “core” spectral regions for the development of compact and portable NIR sensors. Future research should further investigate sample preparation and moisture content effects and expand sampling to different geographical areas to enhance model robustness.
Near-Infrared Spectroscopy to Predict Nutritional Factors of Green Forage Alessandro Benelli, Chiara Evangelista, Raffaello Spina, Riccardo Primi, Daniele Pietrucci, et al. 2024 IEEE International Workshop on Metrology for Agriculture and Forestry Metroagrifor 2024 Proceedings, 2024 Green forage quality is crucial for efficient breeding. Therefore, it would be extremely important to provide a method for a rapid and cost-effective analysis of the nutritional factors of green forage. The application of Fourier-Transformed Near-Infrared (FT-NIR) spectroscopy in combination with chemometric techniques could meet the identified requirements. The objective of the present study was to develop optimized partial least squares (PLS) models for the prediction of nutritional factors of green forage, namely dry matter, crude protein, crude ash, ether extract, neutral detergent fiber, acid detergent fiber, acid detergent lignin, and crude fiber. The elected PLS models resulted from a combination of chemometrics techniques applied to FT-NIR absorbance spectra acquired on fresh and $\\mathbf{dried}/ \\mathbf{milled}$ samples of green forage. The most accurate prediction results were obtained for dry matter in the fresh samples (coefficient of determination of cross-validation, $\\mathbf{R}^{2}\\mathbf{CV}=0.95$; root-mean-square error of cross-validation, RMSECV $=3.84\\mathbf{g}100\\mathbf{g}^{-1}$ fresh weight), and crude protein in the $\\mathbf{dried}/\\mathbf{milled}$ samples $(\\mathbf{R}^{2}\\mathbf{CV}$= 0.94, RMSECV = 1.99 g 100 $\\mathrm{g}^{-1}$ dry weight). Future developments will be further focused on improvement of prediction accuracy by applying deep learning techniques.
Computer Vision Technology for Quality Monitoring in Smart Drying System Roberto Moscetti, Swathi Sirisha Nallan Chakravartula, Andrea Bandiera, Giacomo Bedini, Riccardo Massantini 2020 IEEE International Workshop on Metrology for Agriculture and Forestry Metroagrifor 2020 Proceedings, 2020
Recent advances in the use of NIR spectroscopy for qualitative control and protection of extra virgin olive oil Rivista Italiana Delle Sostanze Grasse, 2015
1-methylcyclopropene (1-MCP) effects on fruit and vegetable storage Industrie Alimentari, 2009
The influence of cover crops and double harvest on storage of fresh hazelnuts (Corylus Avellana L.) Advances in Horticultural Science, 2009
Quality maintenance of Catalonian chicory (Cichorium intybus) minimally processed and 1-metylcyclopropene (1-MCP) effect on the browning of the tissues Industrie Alimentari, 2009
Zucchini (Cucurbita pepo L.) minimally processed packed in plastic film Industrie Alimentari, 2009
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