The current and future role of near infrared reflectance spectroscopy in animal nutrition: a review

Givens, D.I.; Deaville, E. R.

doi:10.1071/ar98014

Cited by 98 publications

(91 citation statements)

References 53 publications

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“…This is mainly because of the variation in range and quantity of raw materials which may exhibit different spectral characteristics for a compound feed with apparently the same chemical composition (Givens & Deaville, 1999). Aufrère et al (1996) stated that NIRS is not widely used for concentrates and compound feeds as a large number of samples are required for the calibration.…”

Section: Introductionmentioning

confidence: 99%

The use of near infrared spectroscopy (NIRS) to predict the chemical composition of feed samples used in ostrich total mixed rations

Swart¹,

Brand²,

Engelbrecht³

2012

SA J. An. Sci.

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The wet chemical analysis of feed samples is time consuming and expensive. Near infrared spectroscopy (NIRS) was developed as a rapid technique to predict the chemical composition of feeds. The prediction of accuracy of NIRS relies heavily on obtaining a calibration set which represents the variation in the main population, accurate laboratory analyses and the application of the best mathematical procedures. In this study NIRS was used to determine the chemical composition of total mixed rations (TMRs) used in ostrich diets. A sample population of 479 ostrich feed samples was used in the calibration and 94 samples were used in the independent validation of dry matter (DM), ash, crude protein (CP), ether extract (EE), crude fibre (CF), acid detergent fibre (ADF), neutral detergent fibre (NDF), gross energy (GE), calcium (Ca) and phosphorus (P). Coefficient of determination in validation (r 2 v ) and standard error of prediction (SEP) was satisfactory (r 2 v values higher than 0.80). Coefficient of determination and SEP values for CP, EE, CF, ADF, NDF and GE were 0.97% and 0.74%, 0.89% and 0.50%, 0.94% and 1.41%, 0.89% and 2.67%, 0.95% and 2.81% and 0.80% and 0.28 MJ/kg, respectively. Less accurate values (r 2 v below 0.80) were obtained for DM, ash, Ca and P being 0.57% and 0.28%, 0.67% and 1.29%, 0.43% and 0.59% and 0.49% and 0.11%, respectively. The study indicated that NIRS is a suitable tool for a rapid, non-destructive and reliable prediction of the chemical composition of ostrich TMRs.

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Section: Introductionmentioning

confidence: 99%

The use of near infrared spectroscopy (NIRS) to predict the chemical composition of feed samples used in ostrich total mixed rations

Swart¹,

Brand²,

Engelbrecht³

2012

SA J. An. Sci.

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“…Also tests need to be done with multiple samples frequently to profile a complete silo of feed and forage, which could impact operating costs. In the last few years, nondestructive testing methods such as Near Infrared Spectroscopy (NIR) has gained popularity for feed testing due to its rapid and inexpensive characteristics (Fulgueira et al, 2007;Givens & Deaville, 1999;Rasby et al, 2008;Undersander, 2007) …”

Section: Wet Chemistry Testingmentioning

confidence: 99%

“…The chemical composition of feed rations is typically determined by using either wellestablished wet chemistry tests or by Near Infrared Spectroscopy (NIR) (Ball et al, 2001;Cozzolino & Moron, 2004;Givens & Deaville, 1999). Conventional wet chemistry analysis is time-consuming, labor-intensive and expensive (Osborne, Fearn, & Hindle, 1993).…”

Section: Introductionmentioning

confidence: 99%

Does a NIR system provide low-cost alternative to on-farm feed and forage testing? A Techno-economic analysis

Ramaswamy¹,

Rosentrater²,

Mosher³

2016

2016 ASABE International Meeting

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Improperly balanced diet not only impacts the quality of animal products but also the quantity of profits of a livestock operation. Typically, the nutrient and chemical content of feed ingredients and forages are determined using well-established wet chemistry tests. However, these tests can be expensive and timeconsuming. Moreover, the increasing use of distiller's by-products which are known to have large variations in chemical and nutrient content warrants a real-time on-farm feed and forage testing system. Near Infra-Red (NIR) spectroscopy systems have been documented as a quick and effective on-site testing tool across several industries. While NIR systems are being adopted for on-farm feed and forage testing, very little is known about the economic impacts of such an investment for a livestock operator. This study developed a baseline model and an excel based spreadsheet application for performing Return On Investment (ROI) analysis to determine the feasibility of using an on-farm NIR testing system. ROI was calculated based on the nutrient cost saved or spent determined from the difference of estimated nutrient content and actual calculated value. Assumptions were made for the cost of NIR system, calibration and labor expenses. What-if analyses were also performed to determine the impact of variation in nutrient content on the ROI. The finding of this study will help promote low-cost alternatives for on-farm feed and forage testing, thus positively impacting the quality of animal product and minimizing costs.

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“…Some studies (Eckman et al, 1983;Park et al, 1997;Steen et al, 1998;Ward et al, 1982) concluded that NIRS could be used to measure diet digestibility, voluntary DM intake and production responses in ruminants fed forage-based diets as accurately as can be done with conventional laboratory analyses. Many research groups and studies have successfully developed calibrations to measure a wide range of forage quality attributes (Ramana Sharma et al, 2010;Smith and Flinn, 1991;Stimson et al, 1991), animal response (Abrams et al, 1987) and voluntary intake (Agnew et al, 2004;Deaville and Flinn, 2000;Givens and Deaville, 1999;.…”

Section: Introductionmentioning

confidence: 99%

“…NIRS for analysis including of feedstuffs (Givens and Deaville, 1999;Williams and Norris, 2001;Williams, 1975) is based on the measurement of the absorption of light in the near infrared range (700-3000 nanometres (nm) region) which is closely related to important chemical bonds (OH, NH and CH) (Deaville and Flinn, 2000;Dixon and Coates, 2010).…”

Section: Introductionmentioning

confidence: 99%

Options for improving the yield and nutritive value of maize and grain legume residues for ruminants in East African farming systems

Dejene¹

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The role and importance of livestock in smallholder crop-livestock systems and the importance of crop residues (CR) as ruminant feedstuffs in such systems are well established. The effects of genotype (G), environment (E) and crop management (M) factors on yields of grain and CR and the nutritive value of the CR of maize (Zea mays) and common bean (Phaseolus vulgaris) were investigated in an East African context. Genotype effects were examined in early and medium maturing (EM and MM, respectively) maize hybrids and popular varieties of common bean. Environment was examined at three sites for maize in the 2013 and 2014 cropping seasons and at four sites for common bean in 2013. Management effects examined were plant density (D) (5 and 7 plants/m 2 ), height of cutting at harvest in maize, and harvest at early and final seed maturity in common bean. Quality attributes (nitrogen (N), neutral detergent fibre (NDF) and acid detergent fibre (ADF) contents and dry matter digestibility (DMD)) were analysed using near infrared spectroscopy (NIRS) and calibrations expanded and validated with reference samples of CR representing the experimental sample set.There was substantial variation (P<0.05 to P<0.0001) among maize genotypes in yields of grain and stover and quality of stover as a feedstuff. Dual purpose genotypes were identified but G x E interactions for some yield and quality attributes showed that the variation among genotypes can depend on environment. In general the higher D increased yields of grain by 9-15% and stover by 21-31%, but had only minor effects on stover quality attributes. Year (Y) x density (D), G x E and G x D interactions were observed for some of the yield and stover attributes.High cutting height of maize (two internodes below the lowest ear) allowed harvest of most of the stover (on average 63-72% in EM and MM genotypes, respectively) as feedstuff while leaving stubble in the field available for other uses. This is established practice by farmers in some regions. The amount and quality as a feedstuff of the upper and lower stover components varied (P<0.01) among genotypes. N and DMD were 0.05-0.09% and 1.7-3.6%, respectively higher (P<0.0001) in the upper fraction of the stover than in whole stover. Thus evaluation and estimation of the amount and quality of maize stover available as a feedstuff should consider harvest at high cutting height to increase quality. G x E interactions were observed in yield and in some stover attributes in the upper and lower fractions, but these were not consistent.ii Common bean varieties varied (P<0.05 to P<0.0001) in yields of seed and haulm and in the nutritive value of haulm fractions (leaf, stem and pod wall) when harvested at seed maturity. There was extensive leaf loss at seed maturity which decreased haulm quality.Seed and haulm yields were correlated (r=0.87). Seed yield was generally not related to haulm quality as N% or DMD%. The variation in yield and haulm feedstuff quality was also examined in common bean varieties harvested at early se...

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The current and future role of near infrared reflectance spectroscopy in animal nutrition: a review

Cited by 98 publications

References 53 publications

The use of near infrared spectroscopy (NIRS) to predict the chemical composition of feed samples used in ostrich total mixed rations

The use of near infrared spectroscopy (NIRS) to predict the chemical composition of feed samples used in ostrich total mixed rations

Does a NIR system provide low-cost alternative to on-farm feed and forage testing? A Techno-economic analysis

Options for improving the yield and nutritive value of maize and grain legume residues for ruminants in East African farming systems

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