Abreu, L.F.; Lana, Â.M.Q.; Climaco, L.C.; Matrangolo, W.J.R.; Barbosa, E.P.; da Silva, K.T.; Rowntree, J.E.; da Silva, E.A.; Simeone, M.L.F. Near-Infrared Spectroscopy and Chemometrics Methods to Predict the Chemical Composition of Cratylia argentea. Agronomy2023, 13, 2525.
Abreu, L.F.; Lana, Â.M.Q.; Climaco, L.C.; Matrangolo, W.J.R.; Barbosa, E.P.; da Silva, K.T.; Rowntree, J.E.; da Silva, E.A.; Simeone, M.L.F. Near-Infrared Spectroscopy and Chemometrics Methods to Predict the Chemical Composition of Cratylia argentea. Agronomy 2023, 13, 2525.
Abreu, L.F.; Lana, Â.M.Q.; Climaco, L.C.; Matrangolo, W.J.R.; Barbosa, E.P.; da Silva, K.T.; Rowntree, J.E.; da Silva, E.A.; Simeone, M.L.F. Near-Infrared Spectroscopy and Chemometrics Methods to Predict the Chemical Composition of Cratylia argentea. Agronomy2023, 13, 2525.
Abreu, L.F.; Lana, Â.M.Q.; Climaco, L.C.; Matrangolo, W.J.R.; Barbosa, E.P.; da Silva, K.T.; Rowntree, J.E.; da Silva, E.A.; Simeone, M.L.F. Near-Infrared Spectroscopy and Chemometrics Methods to Predict the Chemical Composition of Cratylia argentea. Agronomy 2023, 13, 2525.
Abstract
Cratylia argentea is a leguminous shrub with a great potential for livestock feeding in tropical areas. However, time consuming and labor-intensive methods of chemical analysis limits the understanding of its nutritive value. Near infrared spectroscopy (NIRS) is a low-cost technology that has been widely used in forage crops to fasten the assessment of its chemical composition. The objective of this study was to develop prediction models to assess crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF) and dry matter (DM) of Cratylia based on NIRS and partial least square analysis. A total of 155 samples were harvested at different maturity levels and used for model development, whereas 107 were used for calibration and 48 for external validation. The cross-validation presented Root Mean Square Error of Prediction of 0.77, 2.56, 3.43, and 0.42; a Ratio of Performance to Deviation of 4.8, 4.0, 3.8, and 3.4; an R2 of 0.92, 0.92, 0.87, and 0.84 for CP, NDF, ADF, and DM, respectively. Based on the obtained results, we conclude the ability to predict chemical parameters of Cratylia with the current model was accurate. This way, livestock producers and researchers may use it to fasten the assessment of Cratylia’s nutritive value.
Biology and Life Sciences, Agricultural Science and Agronomy
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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