Faecal near infrared reflectance spectroscopy estimates of diet quality and responses to nitrogen supplements by cattle grazing Bothriochloa pertusa pastures

2008 ◽  
Vol 48 (7) ◽  
pp. 829 ◽  
Author(s):  
D. B. Coates ◽  
R. M. Dixon
Keyword(s):  
Diet Quality ◽  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Dry Season ◽  
Infrared Reflectance ◽  
Wet Season ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Infrared Reflectance Spectroscopy ◽  
Grazing Cattle

A grazing experiment in the seasonally dry tropics of north Queensland examined the diet selected and the growth responses of Bos indicus steers to urea supplement over two dry seasons and one wet season, from August 2001 to January 2003. There were two groups of 10 steers (control and urea-supplemented) and each group comprised two age cohorts, A and B, of five steers each with an age difference of ~1 year. In June 2002, cohort A steers were replaced with steers 2 years younger (cohort C). The steers grazed Bothriochloa pertusa pastures on a low fertility Red Chromosol soil. The groups were switched between two adjoining paddocks at fortnightly intervals when they were weighed and faecal samples were collected for faecal near infrared reflectance spectroscopy (F.NIRS) estimates of diet quality and growth rate. Rainfall and diet quality followed the expected seasonal pattern, but the 2001–02 wet season was very short (November–January) with only 65% of the long-term average rainfall. There was no rain during the 2001 dry season (DS-1) from August to mid November, and no effective rain (17 mm) between February and December 2002. Non-grass (i.e. herbaceous dicot plants) made only a small contribution to the diet, averaging 13%. In DS-1 and in the dry season of 2002 (DS-2) diet crude protein (CP) averaged 2.5% and 2.9%, and DMD/CP (ratio of dry matter digestibility to CP) averaged 18.6 and 17.1, respectively. Liveweight (LW) loss in control steers during DS-1 averaged 32 kg. Urea supplement reduced LW loss by 18 kg (P < 0.001), but most of the benefit was lost during the following growing season. During the extended dry period in 2002, average LW losses of control steers were 85 and 47 kg in the older and younger cohorts, respectively, and supplementation with urea reduced weight losses by 53 and 31 kg, respectively (P < 0.001). F.NIRS predicted the cumulative LW of the unsupplemented steers in cohorts A and B with acceptable accuracy, the difference between the observed and predicted final LW being 6 kg for cohort A after 10 months, 12 kg for cohort B after 17 months, and 27 kg for cohort C after 7 months. The results demonstrated that F.NIRS can be effectively used to monitor dietary CP and DMD levels in grazing cattle, to help develop an understanding of cattle responses to urea supplement relative to the quality of the basal forage diet, and to provide useful decision support information for the nutritional management of grazing cattle.

Diet quality and liveweight gain of steers grazing Leucaena - grass pasture estimated with faecal near infrared reflectance spectroscopy (F.NIRS)

2008 ◽  
Vol 48 (7) ◽  
pp. 835 ◽  
Author(s):  
R. M. Dixon ◽  
D. B. Coates
Keyword(s):  
Diet Quality ◽  
Crude Protein ◽  
Protein Concentration ◽  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Infrared Reflectance Spectroscopy ◽  
Additional Reference

Three drafts of Bos indicus cross steers (initially 178–216 kg) grazed Leucaena–grass pasture [Leucaena leucocephala subspecies glabrata cv. Cunningham with green panic (Panicum maximum cv. trichoglume)] from late winter through to autumn during three consecutive years in the Burnett region of south-east Queensland. Measured daily weight gain (DWGActual) of the steers was generally 0.7–1.1 kg/day during the summer months. Estimated intakes of metabolisable energy and dry matter (DM) were calculated from feeding standards as the intakes required by the steers to grow at the DWGActual. Diet attributes were predicted from near infrared reflectance spectroscopy spectra of faeces (F.NIRS) using established calibration equations appropriate for northern Australian forages. Inclusion of some additional reference samples from cattle consuming Leucaena diets into F.NIRS calibrations based on grass and herbaceous legume–grass pastures improved prediction of the proportion of Leucaena in the diet. Mahalanobis distance values supported the hypothesis that the F.NIRS predictions of diet crude protein concentration and DM digestibility (DMD) were acceptable. F.NIRS indicated that the percentage of Leucaena in the diet varied widely (10–99%). Diet crude protein concentration and DMD were usually high, averaging 12.4 and 62%, respectively, and were related asymptotically to the percentage of Leucaena in the diet (R2 = 0.48 and 0.33, respectively). F.NIRS calibrations for DWG were not satisfactory to predict this variable from an individual faecal sample since the s.e. of prediction were 0.33–0.40 kg/day. Cumulative steer liveweight (LW) predicted from F.NIRS DWG calibrations, which had been previously developed with tropical grass and grass–herbaceous legume pastures, greatly overestimated the measured steer LW; therefore, these calibrations were not useful. Cumulative steer LW predicted from a modified F.NIRS DWG calibration, which included data from the present study, was strongly correlated (R2 = 0.95) with steer LW but overestimated LW by 19–31 kg after 8 months. Additional reference data are needed to develop robust F.NIRS calibrations to encompass the diversity of Leucaena pastures of northern Australia. In conclusion, the experiment demonstrated that F.NIRS could improve understanding of diet quality and nutrient intake of cattle grazing Leucaena–grass pasture, and the relationships between nutrient supply and cattle growth.

Faecal near infrared reflectance spectroscopy (F.NIRS) measurements of non-grass proportions in the diet of cattle grazing tropical rangelands

2007 ◽  
Vol 29 (1) ◽  
pp. 51 ◽  
Author(s):  
D. B. Coates ◽  
R. M. Dixon
Keyword(s):  
Crude Protein ◽  
Near Infrared ◽  
Cattle Grazing ◽  
Reflectance Spectroscopy ◽  
Dry Season ◽  
Infrared Reflectance ◽  
Limited Information ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Infrared Reflectance Spectroscopy

Frequent faecal near infrared reflectance spectroscopy (F.NIRS) analyses of faeces from cattle grazing a range of tropical pastures were used to measure the non-grass component, and other aspects, of their diets. Seasonal profiles of non-grass and crude protein in the diet are presented for nine sites from the speargrass, Aristida–Bothriochloa, and Mitchell grass dominated pasture regions, and for three shrubland sites where browse was plentiful. In grass-dominated native pastures of the speargrass and Aristida–Bothriochloa pasture regions of Queensland where little browse was available, non-grass was usually only 5–15% of the diet. Diet non-grass was even lower for a buffel grass pasture. In uncleared eucalypt woodland in the speargrass region, browse may have contributed up to 20% of the diet in the late dry season when grasses were senesced. In regions with abundant browse (e.g. mulga lands and desert upland systems) cattle preferentially selected actively growing grasses and forbs when they were available. With diminishing availability or declining quality of the forbs and grass due to grazing selection and dry conditions, browse increasingly contributed to intake. In Mitchell grass dominated pastures forbs often comprised more than 50% of the diet, and there appeared to be strong selection for forbs during the dry season. Where browse was available in association with Mitchell grass dominated pastures, it appeared to contribute to intake only in the late dry season. Dry season sampling in monsoonal tallgrass and Mitchell grass dominated pastures indicated dietary crude protein to be linearly correlated with diet non-grass, demonstrating the importance of non-grass in the prevention or alleviation of dry season protein deficiency in cattle. Changes in diet selected by cattle in relation to season and rainfall were generally in accord with the previous limited information, largely with sheep, in comparable vegetation systems. The results demonstrate the value of F.NIRS technology to assist understanding of diet selection by grazing cattle in northern Australia.

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.

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