Abstract
The aim of this work was to study the potential of near-infrared reflectance spectroscopy (NIRS) to predict non-structural carbohydrates (NSC), water soluble carbohydrates (WSC), in vitro organic dry matter digestibility (IVOMD), organic matter (OM), crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF) and starch in samples of whole plant maize with a wide range of variability. The samples were analyzed in reflectance mode by a spectrophotometer FOSS NIRSystems 6500. Four hundred and fifty samples of wide spectrum from different origin were selected out of 3000 scanned for the calibration set, whereas 87 independent random samples were used in the external validation. The goodness of the calibration models was evaluated using the following statistics: coefficient of determination (R2), standard error of cross-validation (SECV), standard error of prediction for external validation (SEP) and the RPDCV and RPDP indexes [ratios of standard deviation (SD) of reference analysis data to SECV and SEP, respectively]. The smaller the SECV and SEP and the greater the RPDCV and RPDP, the predictions are better. Trait measurement units were g/100g of dry matter (DM), except for IVOMD (g/100g OM). The SECV and RPDCV statistics of the calibration set were 1.34 and 3.2 for WSC, 2.57 and 3 for NSC and 2.3 and 2.2 for IVOMD, respectively. The SEP and RPDP statistics for external validation were 0.74 and 4.7 for WSC, 2.14 and 2.5 for NSC and 1.68 and 1.6 for IVOMD respectively. It can be concluded that the NIRS technique can be used to predict WSC and NSC with good accuracy, whereas prediction of IVOMD showed a lesser accuracy. NIRS predictions of OM, CP, NDF, ADF and starch also showed good accuracy.
Highlights
Forage maize (Zea mays L.) is an important source of fodder for dairy farms in northwest of Spain, where the silage dependence for cow feeding extends over five to seven months per year
The aims of this work were: (i) to determine specific near-infrared reflectance spectroscopy (NIRS) calibration equations for water soluble carbohydrates (WSC), nonstructural carbohydrates (NSC), in vitro organic dry matter digestibility (IVOMD) and other nutritive quality traits such as crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), starch and organic matter (OM) in whole plant forage maize with wide range variability; (ii) to estimate the accuracy of the NIRS technique for these traits by using an external validation set; and (iii) to study the relationships among the nutritive quality traits evaluated in whole plant forage maize
Positive high correlations were obtained between NDF and ADF (0.96), NSC and both OM and starch (0.69 and 0.88, respectively), OM and starch (0.64) and between IVOMD and WSC (0.62)
Summary
Forage maize (Zea mays L.) is an important source of fodder for dairy farms in northwest of Spain, where the silage dependence for cow feeding extends over five to seven months per year. The near infrared spectroscopy (NIRS) technique allows rapid determination of forage nutritional quality compared to routine analysis in laboratories of animal nutrition, without destroying or contaminating the samples (Williams, 2001). This technique has been used to estimate nutritional quality traits of forage from the 1970’s to the present (Norris et al, 1976; Shenk et al, 1976; Garrido et al, 1993; Shenk & Westerhaus, 1995). The technique has been recommended by different authors as an adequate method for evaluating quality traits such as crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), lignin (ADL), hemicellulose (HCEL), starch, pH, etc. Campo et al / Span J Agric Res (2013) 11(2), 463-471
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