Fecal Near-Infrared Reflectance Spectroscopy Prediction of the Feed Value of Temperate Forages for Ruminants and Some Parameters of the Chemical Composition of Feces: Efficiency of Four Calibration Strategies

The forage feed value determined by organic matter digestibility (OMD) and voluntary intake (VI) is hard and expensive. Thus, several indirect methods such as near infrared reflectance (NIR) spectroscopy have been developed for predicting the feed value of forages. In this study, NIR spectra of 1040 samples of feces from sheep fed fresh temperate forages were used to develop calibration models for the prediction of fecal crude ash (CA), fecal crude protein (CP), fresh forage OMD, and VI. Another 136 samples of feces were used to assess these models. Four calibration strategies were compared: (1) species-specific calibration; (2) family-specific calibration; (3) a global procedure; and (4) a LOCAL approach. The first three strategies were based on classical regression models developed on different sample populations, whereas the LOCAL approach is based on the development models from selected samples spectrally similar to the sample to be predicted. The first two strategies use feces-samples grouping based on the species or the family of the forage ingested. Forage calibration data sets gave value ranges of 79-327 g/kg dry matter (DM) for CA, 65-243 g/kg DM for CP, 0.52-0.85 g/g for OMD, and 34.7-100.5 g DM/kg metabolic body weight (BW^0.75) for VI. The prediction of CA and CP content in feces by species-specific fecal NIR (FNIR) spectroscopy models showed lower standard error of prediction (SEP) (CA 15.03 and CP 7.48 g/kg DM) than family-specific (CA 21.93 and CP 7.69 g/kg DM), global (CA 19.83 and CP 7.98 g/kg DM), or LOCAL (CA 30.85 and CP 8.10 g/kg DM) models. For OMD, the LOCAL procedure led to a lower SEP (0.018 g/g) than the other approaches (0.023, 0.024, and 0.023 g/g for species-specific, family-specific, and global models, respectively). For VI, the LOCAL approach again led to a lower SEP (6.15 g/kg BW^0.75) than the other approaches (7.35, 8.00, and 8.13 g/kg BW^0.75 for the species-specific, family-specific, and global models, respectively). LOCAL approach performed on FNIR spectroscopy samples gives more precise models for predicting OMD and VI than species-specific, family-specific, or global approaches.

Feasibility of a "leader-follower" grazing system instead of specialised paddocks with regard to integrated gastrointestinal control in small ruminant farming

In the humid tropics, small ruminant farmers have to deal with gastrointestinal parasitic nematodes (GIN), among which anthelmintic resistant (AR) populations are rapidly spreading. Although targeted selective treatments (TSTs) are being increasingly used in breeding stock, suppressive drenchings remain the rule in younger animals, for safety and ease of implementation. Until now, the weaned animals are grazed on dedicated plots, making the selection and spread of AR parasites inevitable. Given that GINs disseminate through pastures, we compared the usual grazing system (control) to a "leader-follower" grazing system (LF) for managing the entire GIN population at the farm scale. There were no significant differences between treatments for the dam reproductive parameters and level of GIN infection nor for the pre-weaning death rate of the kids. The 70-day weight of the litter was significantly lower for LF than for control goats (9.71 vs. 11.64 kg, P < 0.05). Although they were more infested with GIN (1860 vs. 966 epg, P < 0.05), the LF weaned animals grew faster (53.4 vs. 40.8 g day(-1), P < 0.05) and their death rate was lower (4.0 vs. 7.7 %, P < 0.05). The overall animal output was estimated to 1010 [911; 1086] vs. 966 [885; 1046] kg LW ha(-1) year(-1), for LF and control grazing systems, respectively. Additionally, the LF grazing system would make the stocking rate easier to manage. Therefore, it is to be recommended as a complement of TSTs in sustainable small ruminant farming.

Prediction of diet quality for sheep from faecal characteristics: comparison of near-infrared spectroscopy and conventional chemistry predictive models

This study evaluated the ability of equations developed from the analysis of faecal material by conventional chemistry (F.CHEM), and by near-infrared spectroscopy (F.NIRS), to predict intake and digestibility of forages fed with or without supplements. In vivo datasets were obtained using 30 sheep and 25 diets to provide 124 diet–faecal pairs, with each sheep fed four or five of the diets. The diets were five forages fed alone or with urea, molasses, cottonseed meal or sorghum grain supplements. Ninety-nine diet–faecal pairs were selected at random, but ensuring that all diets were represented and both the F.CHEM and F.NIRS prediction equations were developed from this dataset. The remaining 25 diet–faecal pairs were used as a validation dataset. Regressions for F.CHEM were developed by stepwise regression, and F.NIRS prediction equations were developed by partial least-squares regression. Prediction equations based solely on faecal analyte concentrations (F.CHEMc) had poor predictive ability, and models incorporating faecal constituent excretion rates (F.CHEMe) were the best at predicting feed constituent intakes. These models had slightly lower standard errors of prediction (SEP) for organic matter (OM) intake and digestible OM intake compared with the F.NIRS models that did not include faecal excretion rates. However, F.NIRS models had lower SEP for protein intake and OM digestibility. Good agreement between the F.CHEMe and F.NIRS methods was evident (according to the 95% limits-of-agreement test), and both predicted the reference values precisely and with small bias. Equations derived from a dataset that included representatives of all diets used in the experiment gave much better prediction of diet characteristics than those developed from a dataset constructed entirely at random. Equations for F.NIRS developed in this way successfully predicted the characteristics of diets that included forages fed alone and with the type of supplements used in tropical Australia.

Nutritional and ecological evaluation of dairy farming systems based on concentrate feeding regimes in semi-arid environments of Jordan

The objective of this study was to evaluate the nutritional and ecological aspects of feeding systems practiced under semi-arid environments in Jordan. Nine dairy farms representing the different dairy farming systems were selected for this study. Feed samples (n = 58), fecal samples (n = 108), and milk samples (n = 78) were collected from the farms and analysed for chemical composition. Feed samples were also analysed for metabolisable energy (ME) contents and in vitro organic matter digestibility according to Hohenheim-Feed-Test. Furthermore, fecal nitrogen concentration was determined to estimate in vivo organic matter digestibility. ME and nutrient intakes were calculated based on the farmer's estimate of dry matter intake and the analysed composition of the feed ingredients. ME and nutrient intakes were compared to recommended standard values for adequate supply of ME, utilizable crude protein, rumen undegradable crude protein (RUCP), phosphorus (P), and calcium (Ca). Technology Impact Policy Impact Calculation model complemented with a partial life cycle assessment model was used to estimate greenhouse gas emissions of milk production at farm gate. The model predicts CH4, N2O and CO2 gases emitted either directly or indirectly. Average daily energy corrected milk yield (ECM) was 19 kg and ranged between 11 and 27 kg. The mean of ME intake of all farms was 184 MJ/d with a range between 115 and 225 MJ/d. Intake of RUCP was lower than the standard requirements in six farms ranging between 19 and 137 g/d, was higher (32 and 93 g/d) in two farms, and matched the requirements in one farm. P intake was higher than the requirements in all farms (mean oversupply = 19 g/d) and ranged between 3 and 30 g/d. Ca intake was significantly below the requirements in small scale farms. Milk nitrogen efficiency N-eff (milk N/intake N) varied between 19% and 28% and was mainly driven by the level of milk yield. Total CO2 equivalent (CO2 equ) emission ranged between 0.90 and 1.88 kg CO2/kg ECM milk, where the enteric and manure CH4 contributed to 52% of the total CO2 equ emissions, followed by the indirect emissions of N2O and the direct emissions of CO2 gases which comprises 17% and 15%, respectively, from total CO2 equ emissions. Emissions per kg of milk were significantly driven by the level of milk production (r (2) = 0.93) and of eDMI (r (2) = 0.88), while the total emissions were not influenced by diet composition. A difference of 16 kg ECM/d in milk yield, 9% in N-eff and of 0.9 kg CO2 equ/kg in ECM milk observed between low and high yielding animals. To improve the nutritional status of the animals, protein requirements have to be met. Furthermore, low price by-products with a low carbon credit should be included in the diets to replace the high proportion of imported concentrate feeds and consequently improve the economic situation of dairy farms and mitigate CO2 equ emissions.