The feasibility of using near infrared reflectance and near infrared transmission spectroscopy to evaluate the proximate composition and the content in fermentation end-products of fresh silage was investigated. In this study, the silage fermentation characteristics were predicted both by NIR reflectance (NIRSystems 6500 with a coarse sample cell) and by NIR transmittance (Tecator Infratec 1255). The silage was measured immediately on opening the silo with no sample preparation. The analysis of silage in its fresh state prevents volatilisation of fermentation end-products. The best results were obtained in the reflectance mode for all the constituents under investigation, using the full wavelength range. The best R2 values for pH, ammonia-nitrogen, lactic and acetic acids for validation samples were 0.90, 0.93, 0.86 and 0.85, respectively. The corresponding standard error values were 0.23 and 1.07 (% of total nitrogen), 8.35 and 1.65 (g kg−1 dry matter). It is concluded that silage fermentation characteristics can be predicted by NIR analysis on the silage in its fresh state. In this manner, the volatilisation of fermentation end-products is prevented.
The inclusion of dietary fiber (DF) in diets has been suggested as a way to reduce NH(3) emission in pig barns because it contributes to a shift in N excretion from urine to feces owing to enhanced bacterial growth in the intestines. This study compared an in vitro method to measure bacterial protein synthesis during fermentation with an in vivo N excretion shift induced by diets differing in DF concentrations and solubility. The first experiment measured the effect of graded concentrations of sugar beet pulp (SBP; 0, 10, 20, and 30%) in corn- and soybean meal-based diets on in vivo N excretion partitioning between the urine and feces. A second experiment investigated the replacement of SBP, rich in soluble DF, with oat hulls (OH), rich in insoluble DF (20:0, 10.5:10.5, and 0:22%, respectively). In parallel, the fermentation characteristics of the dietary carbohydrates not digested in the small intestine were evaluated in an in vitro gas test, based on their incubation with colonic microbiota, using a mineral buffer solution enriched with (15)N. The N originating from the buffer solution incorporated into the bacterial proteins (BNI) was measured when half the final gas volume was produced (8.5 to 14.5 h of fermentation) and after 72 h of fermentation. Short-chain fatty acids were determined in the liquid phase. In the first experiment, the inclusion of SBP linearly decreased urinary N excretion from 0.285 to 0.215 g of N excreted in the urine per gram of N ingested and decreased the urinary-N:fecal-N excretion ratio from 2.171 to 1.177 (P < 0.01). In the second experiment, substituting SBP with OH linearly increased the urinary-N:fecal-N excretion ratio (P = 0.009). Unlike short-chain fatty acid production, BNI was greater at half-time to asymptotic gas production than at 72 h of fermentation. Sugar beet pulp enhanced BNI linearly (P < 0.001), 2.01, 2.06, and 2.35 mg g(-1) of diet with 10, 20, and 30% SBP, respectively, as compared with 1.51 mg for the control diet. The substitution of SBP with OH decreased BNI (P < 0.01). With the exception of final gas production, all in vitro kinetic characteristics and BNI were correlated with in vivo N excretion parameters, and regression equations for the prediction of N excretion pathways from in vitro data were identified. Even if the presence of resistant starch in the diet might alter the composition of the fibrous residue that is fermented, the in vitro method is a possible useful tool for the formulation of diets, reducing the effects of pig production on the environment.
Summary — The biochemical nature of leaf litter is a key factor in regulation of its decomposition. Conventional wet chemical analysis of samples is destructive, time-consuming and expensive. The objective of this study was to evaluate the potentiality of near infrared reflectance spectroscopy (NIRS) for determining litter chemistry during the decomposition process using a wide range of species and decomposition stages. The litter of 8 species of evergreen and deciduous broad-leaved trees, conifers and shrubs were used in both laboratory and field experiments. Near-infrared reflectance measurements were made with an NIRS Systems 5000 spectrophotometer over the range 1100-2500 nm. Calibration samples were analysed for ash, carbon and nitrogen. Acid-detergent fiber (ADF) and acid-detergent lignin (ADL) were determined using Van
The chemical composition of 1052 samples covering 49 plant species is summarized in this paper. The analyzed biomasses offer a wide range of chemical compositions, monosaccharidic compositions of hemicelluloses, enzymatically digestible organic matter, and bioethanol potential. Nevertheless, their thermal energy value remains in a narrow range on a dry matter basis. Biomasses that were identified as best suited for anaerobic digestion are characterized by low contents of cellulose, hemicelluloses, and lignin and high contents of non-structural constituents. Biomasses most suited for combustion present the lowest content of mineral compounds, and the most adequate biomasses for bioethanol conversion have high contents of total carbohydrates. Interestingly, the observed chemical compositions tend to cluster the biomasses in composition groups that also correspond to phylogenetic groups: commelinids, non-commelinid magnoliophyta, and pinophyta species. Some groups can clearly be subdivided into fibrous and moderately fibrous biomasses.
This paper investigates the effect of spectral data pre-treatment by using scatter correction techniques, detrending and derivatives on the standard error of NIR predictive models. It is shown that no particular spectral pre-treatment or no single derivative works best for the three constituents (protein, cellulose, organic matter digestibility) of the three forage databases which we investigated (grass-hay, tropical forages, maize whole plants). The best analytical results are obtained with SNVD, MSC or WMSC treatments. The best results are obtained with a first or second derivative with a segment and a gap of five data points. Local Regression was investigated for the prediction of forage quality. The standard errors of prediction were compared with those obtained with the best global calibration. Trial and error is the only way to fix the number of samples in the subset and the number of terms to retain in the model. Compared to the results for the traditional universal calibration method, the gain in SEP for protein, cellulose and digestibility in grass-hay, tropical forages or maize ranges between 5 and 11%.
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