Hot topic: application of support vector machine method in prediction of alfalfa protein fractions by near infrared reflectance spectroscopy

Nutritional Characterization of Hay Produced in Campania Region: Analysis by the near Infrared Spectroscopy (NIRS) Technology

Since the dietary characteristics of hays can be very variable, it is of great importance for nutritionists to know their chemical composition in order to formulate adequate rations for the animals. Laboratory analyses are time-consuming and expensive while the Near Infrared Spectroscopy offers several advantages, including obtaining information on feeds nutritional characteristics very quickly and in situ at the farm, thanks to portable NIRS. In this trial, over 400 hay samples collected in the Campania region (Italy) were analyzed with portable NIRS device. The final aim was to analyze the differences in hay quality in different production areas, highlighting the possible factors involved and suggesting possible corrective measures. All the analyzed hays (polyphite, Gramineae and alfalfa) were significantly (p < 0.05) influenced by the area of cultivation/preservation. In particular, the polyphite and Gramineae hays produced in most of the areas of Campania region showed poor nutritional value due to the low protein content and high structural carbohydrate that significantly reduced its digestibility. The use of high-quality forages in the ration represents a pivotal factor to allow the production of high-quality products of animal origin. The use of NIRS seems to be a valuable strategy to select potential treatments that can increase feed digestibility and to avoid long chemical analysis.

Comparison of two in situ reference methods to estimate indigestible NDF by near infrared reflectance spectroscopy in alfalfa

Undigested forage neutral detergent fiber (uNDF) from long-term ruminal in situ incubations are used to estimate indigestible neutral detergent fiber (iNDF). Measurement of iNDF is important in forage evaluation because it defines the potentially digestible pool of neutral detergent fiber (NDF). Near-infrared reflectance spectroscopy (NIRS) can be calibrated to in situ reference sets to rapidly predict uNDF. Our objective was to compare uNDF estimates after 240 h of incubation when two types of bags were used in the in situ reference method. The bags compared were 4 cm × 5 cm Ankom F57 bags (25 micron pore size), and 5 cm × 10 cm Ankom in situ bags (50 micron pore size). Alfalfa samples from Pennsylvania and Wisconsin (n = 144) of different varieties and harvest intervals were used. One-half or two gram samples, respectively, were weighed into the small and large bags in triplicate. Mass to surface area was 0.05 and 0.02 g/cm² for the small and large bags, respectively. The iNDF content after 240 h incubation was evaluated by two types bags in three rumen-cannulated Holstein cows. Each dried and ground forage was also scanned to determine the visible-near-infrared-reflectance spectra with a FOSS 6500 spectrophotometer. Prediction equations were developed for each bag type using modified partial least square regressions. The estimated iNDF fraction from small and large bags were 13.75% and 9.97%, respectively (SED = 0.39, P < 0.001). The coefficient of determination for calibration (R²), cross-validation (1 - VR), calibration standard deviation (SEC), and interactive authentication standard deviation (SECV) was 0.94, 0.92, 0.85 and 0.98 for values determined with the small bag and 0.88, 0.85, 1.12 and 1.27 for iNDF for values determined with the large bag, respectively. Results indicate that iNDF varies among alfalfa cultivars and NIRS can be used to quickly and quantitatively estimate iNDF content in alfalfa. Bag type influences 240h NDF residues. NIRS predictions of iNDF from the small bag calibration set had higher R² and lower SEC and SECV than the large bag calibrations.

Predicting timothy mineral concentrations, dietary cation-anion difference, and grass tetany index by near-infrared reflectance spectroscopy

The mineral concentration of forage grasses plays a significant role in 2 metabolic disorders in dairy cattle production, namely, hypocalcemia (milk fever) and hypomagnesemia (grass tetany). Risks of occurrence of these 2 metabolic disorders can be evaluated by determining the dietary cation-anion difference (DCAD) and the grass tetany (GT) index of forages and specific rations. The objective of this study was to evaluate the feasibility of predicting timothy (Phleum pratense L.) mineral concentrations of Na, K, Ca, Mg, Cl, S, and P, the DCAD, and the GT index by near-infrared reflectance spectroscopy (NIRS). Timothy samples (n = 1,108) were scanned using NIRS and analyzed for the concentration of 7 mineral elements. Calculations of the DCAD were made using 3 different formulas, and the GT index was also calculated. Samples were divided into calibration (n = 240) and validation (n = 868) sets. The calibration, cross-validation, and prediction for mineral concentrations, the DCAD, and the GT index were performed using modified partial least squares regression. Concentrations of K, Ca, Mg, Cl, and P were successfully predicted with coefficients of determination of prediction (R(P)2) of 0.69 to 0.92 and coefficients of variation of prediction (CV(P)) ranging from 6.6 to 11.4%. The prediction of Na and S concentrations failed, with respective R(P)2 of 0.58 and 0.53 and CV(P) of 82.2 and 12.9%. The 3 calculated DCAD and the GT index were predicted successfully, with R(P)2 >0.90 and CV(P) <20%. Our results confirm the feasibility of using NIRS to predict K, Ca, Mg, and Cl concentrations, as well as the DCAD and the GT index, in timothy.