Evaluation of acid detergent insoluble protein as an estimator of rumen non-degradable protein in tropical grass forages

Clipes, Renata Cogo; Detmann, Edênio; Silva, J.F.C.; Vieira, Ricardo Augusto Mendonça; Nunes, L.B.M.; Lista, Fábio Nunes; Ponciano, Niraldo José

doi:10.1590/s0102-09352006000400041

Cited by 12 publications

(5 citation statements)

References 2 publications

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“…Based on the results, it can be inferred that the DM content of forages at baling time was appropriate and did not cause increase in temperature during storage, because according to Van Soest (1994), increase in ADIP levels occur when moisture is high and temperature reaches values above 55 °C. The estimate of this fraction becomes relevant due to its potential use as a predictor or estimator of protein, since ADIP is not available to rumen microorganisms or intestinal digestibility (Clipes et al, 2006). Aguiar et al (2006) studied tropical grass hays and found NDIP values ranging from 45.45 to 54.66%, while Gobbi et al (2005) studied Brachiaria decumbens Stapf.…”

Section: Resultsmentioning

confidence: 99%

Use of a conditioning unit at the haymaking of Tifton 85 overseeded with Avena sativa or Lolium multiflorum

et al. 2012

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-White oat and ryegrass were overseeded on Tifton 85 pastures for evaluation of dry matter yield (DMY), leaf:stem ratio (L:S), dehydration curves and nutritional value of forages. Dry matter intake and L:S ratio were analyzed using a completely randomized blocks design with five forage growth conditions (single Tifton 85 and intercropped with white oat or ryegrass, and white oat or ryegrass intercropped with Tifton 85), whereas for drying curves, ten dehydration times were tested (0, 4, 8, 24, 28, 32, 48, 52, 56 and 71 hours after harvest) by a 5 × 10 split-plot arrangement (growth conditions of forages as main plot and dehydration times as sub-plots). The nutritive value data were analyzed in a 3 × 3 split-plot trial with single Tifton 85, Tifton 85 -Oat and Tifton 85-Ryegrass as main plots and the three sampling times (before harvesting, at baling and 100 days after storage) as sub-plots. Oat and ryegrass showed higher L:S ratio, while the intercrops of Tifton 85 -Oat and Tifton 85 -Ryegrass presented lower DMY, but higher crude protein concentration and in vitro DM digestibility than single Tifton. Neutral and acid detergent fiber concentrations were higher for single Tifton 85. Ryegrass and white oat, overseeded on Tifton 85 pasture, improved the nutritional value of the hay produced; however, in a 100-day storage period, there was a reduction in in vitro dry matter digestibility and crude protein concentrations.

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Section: Resultsmentioning

confidence: 99%

Use of a conditioning unit at the haymaking of Tifton 85 overseeded with Avena sativa or Lolium multiflorum

et al. 2012

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“…Acid detergent fibre (ADF) and lignin (ADL) models have to be rejected because validation with 2013 data clearly fails (NRMSE = 0.4, NMAE = 0.4 for ADF; NRMSE = 0.5, NMAE = 0.4 for ADL). There is a possible reason for these difference within both fibre and digestibility (predictability of dNDF24 and NDF but not of dNDF240, ADF and ADL) considering the nature of these variables: cellulose and lignin are the vegetal component which less manifest themselves into visible effects (like greenness), and NDF digestibility at 240 hours is linked to their relative content more than in the case of NDF digestibility at 24 hours [Clipes et al, 2006;Casali et al, 2008].…”

Section: Fibrementioning

confidence: 99%

MODIS time series contribution for the estimation of nutritional properties of alpine grassland

Ranghetti

Bassano

Bogliani

et al. 2016

European Journal of Remote Sensing

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Despite the Normalised Difference Vegetation Index (NDVI) has been used to make predictions on forage quality, its relationship with bromatological field data has not been widely tested. This relationship was investigated in alpine grasslands of the Gran Paradiso National Park (Italian Alps). Predictive models were built using remotely sensed derived variables (NDVI and phenological information computed from MODIS) in combination with geo-morphometric data as predictors of measured biomass, crude protein, fibre and fibre digestibility, obtained from 142 grass samples collected within 19 experimental plots every two weeks during the whole 2012 growing season. The models were both crossvalidated and validated on an independent dataset (112 samples collected during 2013). A good predictability ability was found for the estimation of most of the bromatological measures, with a considerable relative importance of remotely sensed derived predictors; instead, a direct use of NDVI values as a proxy of bromatological variables appeared not to be supported.

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“…w ADICP in Eq. 15b is the mass fraction of acid detergent insoluble crude protein (ADICP) in feed dry matter, which is estimated from w NDICP using a relationship from Clipes et al (2006):…”

Section: Digestible Nutrientsmentioning

confidence: 99%

Modeling the role of livestock grazing in C and N cycling in grasslands with LPJmL5.0-grazing

Heinke

Rolinski

Müller

2022

Preprint

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Abstract. Grazing livestock alter the fluxes of carbon (C) and nitrogen (N) in grasslands. We implement a livestock module representing grazing dairy cows into LPJmL5.0-tillage, a global vegetation and crop model with explicit representation of managed grasslands and pastures, forming LPJmL5.0-grazing. The new module explicitly accounts for feed quality on dry matter intake and feed digestibility using relationships derived from compositional analyses for different forages. Partitioning of N into milk, feces, and urine are simulated by the new livestock module shows very good agreement with observation-based relationships reported in the literature. Modeled C and N dynamics depend on feed quality (C:N ratios in grazed biomass), feed quantity, livestock densities, manure or fertilizer inputs, soil, atmospheric CO2 concentrations, and climate conditions. Due to the many interacting relationships, C sequestration or emission rates as well as N losses and N use efficiency (NUE) show substantial variation in space and across livestock densities. The improved LPJmL5.0-grazing model can now assess the effects of management and climate change on grazing dairy productivity, C dynamics and N losses. Optimal stocking densities can be derived per location for different optimization targets, such as maximization of milk production, lowest emission intensity, best NUE, or highest C sequestration.

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Evaluation of acid detergent insoluble protein as an estimator of rumen non-degradable protein in tropical grass forages

Cited by 12 publications

References 2 publications

Use of a conditioning unit at the haymaking of Tifton 85 overseeded with Avena sativa or Lolium multiflorum

Use of a conditioning unit at the haymaking of Tifton 85 overseeded with Avena sativa or Lolium multiflorum

MODIS time series contribution for the estimation of nutritional properties of alpine grassland

Modeling the role of livestock grazing in C and N cycling in grasslands with LPJmL5.0-grazing

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