scholarly journals Forage Quality Evaluation

1970 ◽  
Vol 66 (1) ◽  
Author(s):  
Lucien CARLIER ◽  
Chris VAN WAES ◽  
Ioan ROTAR ◽  
Mariana VLAHOVA ◽  
Roxana VIDICAN
Keyword(s):  
Near Infrared ◽  
Animal Husbandry ◽  
Quality Parameters ◽  
Near Infrared Reflectance ◽  
Domestic Ruminants ◽  
In Vitro Technique ◽  
Protein Rich ◽  
Non Destructive ◽  
Destructive Methods

The challenge for the research in crop and animal husbandry is how to determine the quality of a speci¬fied crop as a forage for ruminants by the chemical analysis of only a small amount of sample". Since more than hundred years scientists try to give an answer to that question. The most applied is the Weende and Van Soest system, together with the digestibility in vitro technique developed by Tilley and Terry. During the last decennia also non destructive methods, like the Near Infrared Reflectance Spectroscopy NIRS, are used more frequently. Forages contain a lot of quality parameters (protein, fat, sugars, structural carbohydrates, vitamins, … but some of them contain also anti quality components (alkaloids, nitrates, …). The diet of domestic ruminants exists of more than only 1 component. Other diet components may interfere and mostly result in a synergism. The combination of a protein rich forage (legumes) with starch riches ones results in better animal productions than given as sole diet component. Fast and reliable non destructive methods are more attractive and acceptable than laborious, polluting and animal unfriendly ones.

PREDICTING NITROGEN AND DIGESTIBILITY OF FORAGES USING NEAR INFRARED REFLECTANCE PHOTOMETRY

1981 ◽  
Vol 61 (1) ◽  
pp. 45-51 ◽  
Author(s):  
J. E. WINCH ◽  
HELEN MAJOR
Keyword(s):  
Nitrogen Content ◽  
Near Infrared ◽  
Correlation Coefficients ◽  
Quality Parameters ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance ◽  
Dry Matter Digestibility ◽  
Percent Nitrogen

A Technicon Infra Alyzer 2.5, near infrared reflectance analyzer equipped with the six filters (1.68, 1.94, 2.10, 2.15, 2.23, 2.31 μm) which are used for the estimation of percent nitrogen, oil and moisture of grain crops was evaluated for the analyses of percent total nitrogen, in vitro and in vivo dry matter digestibility in grasses, legumes and grass-legume mixtures. Of the three quality parameters, only percent nitrogen was estimated with an acceptable degree of accuracy. The analyzer, therefore, has a potential for rapid nitrogen analysis of grasses, legumes and grass-legume mixtures. Correlation coefficients of 0.90 and above were obtained between infrared and Kjeldahl nitrogen when the nitrogen content of grasses or legume test samples was derived on either a grass or a legume calibration. A slight decrease in the standard error of prediction occurred when grass and legume calibrations were used to estimate nitrogen content of grass and legume samples, respectively. To insure accuracy, samples used to develop calibrations as well as those to be analyzed should be finely ground. In addition, the moisture content of the samples must be kept within the moisture range of the calibration.

DETERMINATION OF QUALITY PARAMETERS BY NEAR INFRARED REFLECTANCE SPECTROSCOPY IN WHOLE-PLANT CORN SILAGE

1987 ◽  
Vol 67 (3) ◽  
pp. 747-754 ◽  
Author(s):  
E. V. VALDES ◽  
R. B. HUNTER ◽  
L. PINTER
Keyword(s):  
Near Infrared ◽  
Quality Parameters ◽  
Quality Parameter ◽  
Mathematical Treatment ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance ◽  
Dry Matter Digestibility ◽  
Whole Plant ◽  
Percent Protein

The prediction of quality parameters by near infrared reflectance analysis (NIRA) in whole-plant corn (Zea mays L.) was studied. Quality parameters included percent protein and in vitro dry matter digestibility (IVDMD). Calibrations were developed using two types of NIRA instruments: (a) a Neotec 51A, a six-tilting-filters type instrument and (b) a Technicon InfraAlyzer 400R, a 19-fixed-filters type instrument. Plant samples were collected from four locations across Ontario (Brucefield, London, Guelph and Elora). Forty samples were used in the calibration sets (C) for each quality parameter and for each instrument. A second group of samples, a prediction set (P) consisting of 200 samples, was used to validate the calibration equations. Regression analysis between NIRA predicted and IVDMD, indicated that this parameter was well predicted in both C and P sets and with the two instruments. Coefficients of determination (r2) for C and P sets were 0.91 and 0.85 for the InfraAlyzer 400R and 0.92, and 0.81 for the Neotec 51A, respectively. A standard error of the estimate (SEE) of 1.70 was observed for the prediction of IVDMD in both C and P sets with the InfraAlyzer 400R. Values of SEE for IVDMD using the Neotec 51A were 1.76 and 1.73 for C and P sets, respectively. NIRA predictions of percent protein showed differences between instruments. The r2 for C and P sets were 0.95 and 0.81 for the InfraAlyzer 400R and 0.90 and 0.58 for the Neotec 51A, respectively. The low r2 value for percent protein in the P set might be related to the mathematical treatment of the reflectance data chosen for the analysis. The SEE for the prediction of percent protein varied between 0.25 and 0.56.Key words: Corn (whole-plant), quality, infrared reflectance

scholarly journals Methods for predicting the energy value of pet foods

2009 ◽  
Vol 38 (spe) ◽  
pp. 1-14 ◽  
Author(s):  
Carlos Castrillo ◽  
Marta Hervera ◽  
Maria Dolores Baucells
Keyword(s):  
Near Infrared ◽  
Metabolizable Energy ◽  
Apparent Digestibility ◽  
Crude Fibre ◽  
Near Infrared Reflectance ◽  
Energy Value ◽  
Close Relationship ◽  
Accuracy Of Prediction

The energy value of foods as well as energy requirements of dogs and cats is currently expressed in terms of metabolizable energy (ME). The determination of ME content of foods requires experimental animals and is too expensive and time consuming to be used routinely. Consequently, different indirect methods have been proposed in order to estimate as reliably an accurately as possible the ME content of pet food. This work analyses the main approaches proposed to date to estimate the ME content of foods for cats and dogs. The former method proposed by the NRC estimates the ME content of pet foods from proximal chemical analysis using the modified Atwater factors, assuming constant apparent digestibility coefficients for each analytical fraction. Modified Atwater factors systematically underestimate the ME content of low-fibre foods whereas they overestimate those that are high in fibre. Recently, different equations have been proposed for dogs and cats based in the estimation of apparent digestibility of energy by the crude fibre content, which improve the accuracy of prediction. In any case, whatever the method of analysis used, differences in energy digestibility related with food processing and fibre digestibility are unlikely to be accounted for. A simple in vitro enzymatic method has been recently proposed based in the close relationship that exist between energy digestibility and organic matter disappearance after two consecutive enzymatic (pepsin-pancreatin) incubation of food sample. Nutrient composition and energy value of pet foods can be also accurately and simultaneously predicted using near infrared reflectance spectroscopy (NIRS).

scholarly journals COMPARISON OF NEAR INFRARED CALIBRATIONS FOR ESTIMATING IN VITRO DIGESTIBILITY IN WHOLE-PLANT CORN HYBRIDS

1987 ◽  
Vol 67 (2) ◽  
pp. 557-562 ◽  
Author(s):  
E. V. VALDES ◽  
R. B. HUNTER ◽  
G. E. JONES
Keyword(s):  
Dry Matter ◽  
Near Infrared ◽  
Mature Stage ◽  
In Vitro Digestibility ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance ◽  
Corn Hybrids ◽  
Dry Matter Digestibility ◽  
Whole Plant

A comparison of two near infrared (NIRA) calibrations (C1 and C2) for the prediction of in vitro dry matter digestibility (IVDM) in whole-plant corn (WPC) was conducted. C1 consisted of 40 WPC samples collected from four locations across Ontario (Brucefield, London, Guelph and Elora). C2 consisted of 90 samples and included the above locations plus Pakenham and Winchester. Nine wavelengths were used in both equations but only three were common in C1 and C2 equations. These wavelengths were 2139 nm, 2100 nm, and 1445 nm, respectively. The predictions of IVDM utilizing both C1 and C2 were good. Coefficients of determination (r2) and standard error of the estimate (SEE) for calibration and prediction sets were 0.91, 1.7; 0.85, 1.7 for C1 and 0.88, 1.6; 0.77, 1.6 for C2 respectively. Regression analysis within location, however, showed low r2 values for the prediction of IVDM for Pakenham and Winchester in both calibrations. The more mature stage of harvest at these locations might be the cause of the poorer predictions. Key words: In vitro digestibility, whole-plant corn, near infrared reflectance

scholarly journals The Relative Performance of a Benchtop Scanning Monochromator and Handheld Fourier Transform Near-Infrared Reflectance Spectrometer in Predicting Forage Nutritive Value

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 658
Author(s):  
Matthew F. Digman ◽  
Jerry H. Cherney ◽  
Debbie J. R. Cherney
Keyword(s):  
Nutritive Value ◽  
Near Infrared ◽  
Prediction Models ◽  
Low Cost ◽  
Neutral Detergent Fiber ◽  
In Vitro Digestibility ◽  
Near Infrared Reflectance ◽  
Average Decrease ◽  
Manufacturing Techniques

Advanced manufacturing techniques have enabled low-cost, on-chip spectrometers. Little research exists, however, on their performance relative to the state of technology systems. The present study compares the utility of a benchtop FOSS NIRSystems 6500 (FOSS) to a handheld NeoSpectra-Scanner (NEO) to develop models that predict the composition of dried and ground grass, and alfalfa forages. Mixed-species prediction models were developed for several forage constituents, and performance was assessed using an independent dataset. Prediction models developed with spectra from the FOSS instrument had a standard error of prediction (SEP, % DM) of 1.4, 1.8, 3.3, 1.0, 0.42, and 1.3, for neutral detergent fiber (NDF), true in vitro digestibility (IVTD), neutral detergent fiber digestibility (NDFD), acid detergent fiber (ADF), acid detergent lignin (ADL), and crude protein (CP), respectively. The R2P for these models ranged from 0.90 to 0.97. Models developed with the NEO resulted in an average increase in SEP of 0.14 and an average decrease in R2P of 0.002.

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