scholarly journals Estimation of dry matter, crude protein and starch values in mixed feeds by near-infrared reflectance (NIR) spectroscopy

2020 ◽  
Vol 4 (3) ◽  
pp. 125-130
Author(s):  
Hasan ATALAY ◽  
Fatih KAHRIMAN ◽  
Firat ALATÜRK
Keyword(s):  
Crude Protein ◽  
Dry Matter ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance ◽  
Mixed Feeds

Validation of near-infrared reflectance spectroscopy to estimate the potential intake of Eucalyptus foliage by folivorous marsupials

2003 ◽  
Vol 51 (1) ◽  
pp. 95 ◽  
Author(s):  
I. R. Wallis ◽  
W. J. Foley
Keyword(s):  
Food Intake ◽  
Dry Matter ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Infrared Reflectance ◽  
Feeding Rates ◽  
Near Infrared Reflectance ◽  
Pseudocheirus Peregrinus ◽  
Remotely Sense ◽  
Animal Habitat

We validated an existing model of food intake by captive common ringtail possums (Pseudocheirus peregrinus), a folivorous marsupial, by feeding foliage from 18 individual Eucalyptus polyanthemos trees and measuring dry matter intake. Near-infrared reflectance (NIR) spectra of a sample of each foliage were recorded and compared against a previously derived model relating food intake in common ringtails and NIR spectra. We found excellent agreement between the predicted and measured food intake, with the standard error of prediction being 3.6 g kg(body mass)–0.75 day–1. NIR spectroscopy is a suitable tool for modelling complex attributes such as potential feeding rates of mammals. This makes it theoretically possible to remotely sense critical nutritional determinants of animal habitat on a landscape scale.

NEAR INFRARED REFLECTANCE SPECTROSCOPY FOR PREDICTING FORAGE COMPOSITION AND VOLUNTARY CONSUMPTION AND DIGESTIBILITY IN CATTLE AND SHEEP

1986 ◽  
Vol 66 (1) ◽  
pp. 103-115 ◽  
Author(s):  
E. S. REDSHAW ◽  
R. D. WEISENBURGER ◽  
G. W. MATHISON ◽  
L. P. MILLIGAN
Keyword(s):  
Crude Protein ◽  
Dry Matter ◽  
Near Infrared ◽  
Energy Content ◽  
Neutral Detergent Fiber ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance ◽  
Digestible Energy ◽  
Voluntary Intake ◽  
Cattle And Sheep

Near infrared reflectance spectroscopic (NIR) measurements were made on 82 samples of legume (alfalfa and clover), grass (brome, timothy, reed canary grass and meadow foxtail) and legume-grass mixtures using a Neotec model 6100 scanning monochromator. Data on the forages, used for establishing NIR calibrations for predictive relationships and appraising them, were chemical composition and measurements of digestibility and voluntary consumption for cattle and sheep. The primary wavelengths selected by multiple regression techniques were similar to those obtained by other researchers for crude protein, acid and neutral detergent fiber, calcium and phosphorus. Similar primary wavelengths were selected for prediction of digestibility and voluntary intake (g kg−0.75) of forages for cattle and sheep, but those selected for voluntary intake on the basis of percentage of body weight differed between animal species. The wavelengths which best predicted animal intake and digestibility in our trials differed from those reported by other researchers. Crude protein, acid detergent fiber, neutral detergent fiber, lignin, acid detergent insoluble nitrogen, calcium, phosphorus and ash concentrations in forage were predicted with standard errors of 1.0, 2.2, 2.9, 1.1, 0.07, 0.15, 0.02, and 1.2%, respectively. The accuracy of predictions for these chemical constituents was similar to that reported by other workers. Digestible energy content, dry matter digestibility, voluntary intake and digestible energy intake of hays by cattle were predicted with standard errors of prediction of 0.59 MJ kg, 2.4%, 7.6 g DM kg−0.75, and 79 kJ kg−0.75, respectively. Corresponding values for sheep were 0.96, 4.4, 6.3 and 128. The quantitative importance of variability in animal data in the calibration of the NIR procedure was discussed. This variability accounted for about one-half of the variability of NIR prediction of voluntary DM and digestible energy intake of cattle. This proportion was reduced to approximately one-quarter and one-sixth for digestibility of dry matter and digestible energy content of feed, respectively. Key words: Cattle, sheep, forages, near infrared reflectance spectroscopy, nutritive value

Prediction of Dry Matter and Crude Protein Content in Fresh Grass Silage by Near Infrared Spectroscopy

2005 ◽  
Vol 1 (1) ◽  
pp. 57-75 ◽  
Author(s):  
Marina Vranić ◽  
Mladen Knežević ◽  
Zsolt Seregély ◽  
Krešimir Bošnjak ◽  
Josip Leto ◽  
...  
Keyword(s):  
Protein Content ◽  
Crude Protein ◽  
Dry Matter ◽  
Near Infrared ◽  
Chemical Constituents ◽  
Nir Spectroscopy ◽  
Meat Production ◽  
Crude Protein Content ◽  
Near Infrared Reflectance ◽  
Grass Silage

Intensive livestock feeding requires constant monitoring of diet composition to ensure a consistent level of milk or meat production. A rapid analysis of fresh grass silage samples for dry matter (DM) and crude protein (CP) content would provide basic, rapid information what would permit decision to be made regarding the need to supplement the diet. The aim of the present study was to determine dry matter (DM) and crude protein (CP) content in fresh grass silage samples by NIR spectroscopy. Crude protein content can be expressed as g per kg dry matter (g kg-1 DM) or as per cent of fresh weight (% FW). Near-infrared reflectance spectra were recorded for 103 fresh grass silage samples. Laboratory analysis of DM and CP were determined for these samples. MLR, PCR and PLS techniques were used for data modelling to determine the optimum models for predicting each of the chemical constituents. It was concluded that the PLS method was superior to the PCR and MLR methods for DM and CP prediction in fresh grass silage samples, while MLR showed a promising possibility to determine the CP content using only two spectral values measured at two “characteristic”wavelengths.

scholarly journals Predicting quality, texture and chemical content of yam (Dioscorea alata L.) tubers using near infrared spectroscopy

2021 ◽  
pp. 096703352110075
Author(s):  
Adou Emmanuel Ehounou ◽  
Denis Cornet ◽  
Lucienne Desfontaines ◽  
Carine Marie-Magdeleine ◽  
Erick Maledon ◽  
...  
Keyword(s):  
High Throughput ◽  
Dry Matter ◽  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Infrared Reflectance ◽  
Quality Traits ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Infrared Reflectance Spectroscopy ◽  
Texture Attributes

Despite the importance of yam ( Dioscorea spp.) tuber quality traits, and more precisely texture attributes, high-throughput screening methods for varietal selection are still lacking. This study sets out to define the profile of good quality pounded yam and provide screening tools based on predictive models using near infrared reflectance spectroscopy. Seventy-four out of 216 studied samples proved to be moldable, i.e. suitable for pounded yam. While samples with low dry matter (<25%), high sugar (>4%) and high protein (>6%) contents, low hardness (<5 N), high springiness (>0.5) and high cohesiveness (>0.5) grouped mostly non-moldable genotypes, the opposite was not true. This outline definition of a desirable chemotype may allow breeders to choose screening thresholds to support their choice. Moreover, traditional near infrared reflectance spectroscopy quantitative prediction models provided good prediction for chemical aspects (R2 > 0.85 for dry matter, starch, protein and sugar content), but not for texture attributes (R2 < 0.58). Conversely, convolutional neural network classification models enabled good qualitative prediction for all texture parameters but hardness (i.e. an accuracy of 80, 95, 100 and 55%, respectively, for moldability, cohesiveness, springiness and hardness). This study demonstrated the usefulness of near infrared reflectance spectroscopy as a high-throughput way of phenotyping pounded yam quality. Altogether, these results allow for an efficient screening toolbox for quality traits in yams.

Prediction of crude protein content in field peas using near infrared reflectance spectroscopy

2006 ◽  
Vol 86 (1) ◽  
pp. 157-159 ◽  
Author(s):  
G. C. Arganosa ◽  
T. D. Warkentin ◽  
V. J. Racz ◽  
S. Blade ◽  
C. Phillips ◽  
...  
Keyword(s):  
Crude Protein ◽  
Near Infrared ◽  
Spectroscopic Method ◽  
Correlation Coefficients ◽  
Reflectance Spectroscopy ◽  
Field Pea ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Infrared Reflectance Spectroscopy

A rapid, near-infrared spectroscopic method to predict the crude protein contents of 72 field pea lines grown in Saskatchewan, both whole seeds and ground samples, was established. Correlation coefficients between the laboratory and predicted values were 0.938 and 0.952 for whole seed and ground seed, respectively. Both methods developed are adequate to support our field pea breeding programme. Key words: Field pea, near-infrared reflectance spectroscopy, crude protein

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