Feeding Strategies and Nutrient Management of Grazing Cattle in Uruguay

Animal Nutritio

Providing heat-stress abatement to late-lactation Holstein cows affects hormones, metabolite blood profiles, and hepatic gene expression but not productive responses

Objective: Our objective was to evaluate the effects of providing shade and shade combined with evaporative cooling on production, cow activity, metabolism, and hepatic gene expression of late-lactation Holstein dairy cows under moderate heat-stress conditions. Materials and Methods: Forty-eight multiparous Holstein cows were used in a completely randomized block-design trial and randomly assigned to 1 of 3 treatments: control (CTL), without access to shade; access to artificial shade (SH); and shade combined with evaporative cooling (SHplus). Results were analyzed using a mixed procedure with repeated measures. Results and Discussion: No differences were observed in DMI. Milk yield was not different among treatments, but lactose concentration was greater in SHplus. Treatments CTL and SH had greater BW losses than SHplus. Control cows spent less time grazing. The CTL and SH had higher p.m. rectal temperatures than SHplus, whereas CTL had the highest p.m. respiration rate. Control cows had greater serum insulin levels. Control and SH had greater BHB and urea concentrations and lower glucose concentration compared with SHplus. The hepatic expression of PCK1, PDK4, and HP genes was downregulated in SH and SHplus relative to control. Hepatic expression of NFKB1 was downregulated, whereas SOCS2 was upregulated, for SHplus compared with CTL. Implications and Applications: Despite the absence of treatment effects on productive variables, changes in blood profiles and hepatic expression of target genes were observed among treatments. These results suggest that the provision of shade combined with evaporative cooling was effective in alleviating the negative effects of heat stress.Fil: Martínez, Rocío Soledad. Instituto Nacional de Investigacion Agropecuaria;Fil: Palladino, Rafael Alejandro. Universidad Nacional de Lomas de Zamora; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Unidad Ejecutora de Investigaciones en Producción Animal. Universidad de Buenos Aires. Facultad de Ciencias Veterinarias. Unidad Ejecutora de Investigaciones en Producción Animal; ArgentinaFil: Banchero, Georgget. Instituto Nacional de Investigacion Agropecuaria;Fil: Fernández y Martín, Rafael. Universidad de Buenos Aires. Facultad de Agronomía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Unidad Ejecutora de Investigaciones en Producción Animal. Universidad de Buenos Aires. Facultad de Ciencias Veterinarias. Unidad Ejecutora de Investigaciones en Producción Animal; ArgentinaFil: Nanni, Mariana Sandra. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Agroindustria. Instituto de Tecnología de los Alimentos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Juliano, Nicolas. Universidad de Buenos Aires. Facultad de Agronomía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Iorio, Jesica Daniela. Universidad de Buenos Aires. Facultad de Agronomía; ArgentinaFil: La Manna, Alejandro. Instituto Nacional de Investigacion Agropecuaria

Energy feeding strategies to shorten the postpartum anoestrous in grazing dairy cows

A prolonged postpartum anoestrus (PPA) is related to a low reproductive efficiency in dairy farms, independently of the calving pattern or feeding system. Postpartum luteal activity resumption is coincident with the onset of lactation when the cow is in negative energy balance, which depending on its magnitude could alter the hypothalamus – pituitary – ovary axis of the animal and prolong the PAA. In this article, some results from experiments that manipulated nutrition as a strategy to shorten the PPA, with emphasis in grazing systems, are briefly reviewed. Available information suggests that manipulation of the level and source of dietary energy are promising tools to reduce the length of the PPA in grazing dairy cows and increase the reproductive efficiency in dairy farms

Plant density in red clover (Trifolium pratense L.) pastures as an early predictor of forage production

Red clover (Trifolium pratense L.) is an alternative of great potential productivity for dairy systems, particularly in heavily compacted soils. Plant density (PD) during pasture establishment can be related to forage production and used as an early indicator of pasture quality. However, biomass predictive models for red clover are not readily available. To predict red clover biomass a few weeks after sowing would help farmers to adopt suitable management practices. The aim of this paper has therefore been to model the relationship between red clover biomass and PD at different time points during pasture establishment to identify the best monitoring moment for estimating future herbage productivity. A multi-environment trial, including several seeding rates simulating different levels of establishment within each of the nine environments, was conducted in Uruguay. Seedlings were counted 3, 7 and 12 weeks after sowing (WS). Biomass of first-cut (C1) harvest was linearly related to PD at 7 WS, whereas a second-order polynomial on PD at 7 WS was a significant predictor of accumulated biomass one (Y1) and two (Y2) years after sowing. PD at 3 WS was a strong predictor of biomass only in high-yielding environments. In such environments, more than 64 plants m−2 at 3 WS suggest a high probability of achieving annual yields above 10,000 kg DM ha-1. Therefore, early PD determination (3 or 7 WS) is a good indicator of annual productivity in pure red clover pastures.Fil: Zarza, Rodrigo. Instituto Nacional de Tecnología Agropecuaria; ArgentinaFil: Rebuffo, Mónica. Instituto Nacional de Tecnología Agropecuaria; ArgentinaFil: La Manna, Alejandro. Instituto Nacional de Tecnología Agropecuaria; ArgentinaFil: Balzarini, Monica Graciela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentin

Prediction of the nutritive value of pasture silage by near infrared spectroscopy (NIRS) Predicción del valor nutritivo de ensilaje de pasturas mediante espectrofotometría en el infrarrojo cercano (NIRS)

The aim of this study was to investigate the use of near infrared reflectance (NIRS) spectroscopy to predict the nutritive value of silages from pastures and to assess the effect of silage structure type (e.g. bunker and bag silos) on the NIRS predictions. Samples (n = 120) were sourced from commercial farms and analyzed in a NIRS monochromator instrument (NIR Systems, Silver Spring, Maryland, USA) using wavelengths between 400 and 2500 nm in reflectance. Calibration models were developed between chemical and NIRS spectral data using partial least squares (PLS) regression. The coefficients of determination in calibration (R2) and the standard error in cross validation (SECV) were 0.73 (SECV: 1.2%), 0.81 (SECV: 2.0%), 0.75 (SECV: 6.6%), 0.80 (SECV: 6.7%), 0.80 (SECV: 4.0%), 0.60 (SECV: 3.6%) and 0.70 (SECV: 0.34) for ash, crude protein (CP), neutral detergent fiber (NDF), dry matter (DM), acid detergent fiber (ADF), in vitro dry matter digestibility (IVDMD) and pH, respectively. The results showed the potential of NIRS to analyze DM, ADF and CP in silage samples from pastures

Usefulness of near infrared reflectance (NIR) spectroscopy and chemometrics to discriminate between fishmeal, meat meal and soya meal samples

Near infrared reflectance (NIR) spectroscopy was used in combination with chemometrics to discriminate between fishmeal, meat meal and soya meal samples. Samples were obtained from commercial feed miles and scanned in the NIR region (1100 - 2500 nm) in a monochromatic instrument in reflectance mode. Principal component analysis (PCA) and linear discriminant analysis were used to classify samples based on their NIR spectra. Full cross-validation was used in the development of classification models. Partial least squares-discriminant analysis (PLS-DA) correctly classified 85.7% of the fishmeal samples and 100% of the meat meal and soya meal samples. These results demonstrate the usefulness of NIR spectra combined with chemometrics as an objective and rapid method to classify fishmeal, meat meal and soya meal samples. NIR spectroscopic methods can be easily implemented in food miles and may be most useful for initial screening at early stages in the food production chain, enabling more costly methods to be used selectively for suspected specimens.El objetivo de este trabajo fue investigar el uso de la espectrofotometría de reflectancia en el infrarrojo cercano (NIR) en combinación con la quimiometría para discriminar muestras de harinas de pescado, carne y soja. Muestras provenientes de molinos racioneros comerciales fueron leídas en un equipo monocromador NIRS (NIRSy stems, Silver Spring, USA) en el rango de longitudes de onda de 400 a 2500 nm, en reflectancia. Análisis de componentes principales (APC) y de discriminantes utilizando la técnica de los cuadrados mínimos parciales (PLS-DA) fueron usados para clasificar las muestras de acuerdo a su origen. El método de la validación cruzada fue utilizado para validar los modelos. El 85,7% de las muestras de harina de pescado y el 100 % de las muestras de carne y soja fueron correctamente clasificados usando el método PLS-DA. Los resultados obtenidos en este estudio demuestran el potencial uso de la reflectancia en el infrarrojo cercano combinada con la quimiometría como un método rápido y de bajo costo para clasificar muestras de harina de pescado, carne y soja

Predicción del valor nutritivo de ensilaje de pasturas mediante espectrofotometría en el infrarrojo cercano (NIRS)

The aim of this study was to investigate the use of near infrared reflectance (NIRS) spectroscopy to predict the nutritive value of silages from pastures and to assess the effect of silage structure type (e.g. bunker and bag silos) on the NIRS predictions. Samples (n = 120) were sourced from commercial farms and analyzed in a NIRS monochromator instrument (NIR Systems, Silver Spring, Maryland, USA) using wavelengths between 400 and 2500 nm in reflectance. Calibration models were developed between chemical and NIRS spectral data using partial least squares (PLS) regression. The coefficients of determination in calibration (R2) and the standard error in cross validation (SECV) were 0.73 (SECV: 1.2%), 0.81 (SECV: 2.0%), 0.75 (SECV: 6.6%), 0.80 (SECV: 6.7%), 0.80 (SECV: 4.0%), 0.60 (SECV: 3.6%) and 0.70 (SECV: 0.34) for ash, crude protein (CP), neutral detergent fiber (NDF), dry matter (DM), acid detergent fiber (ADF), in vitro dry matter digestibility (IVDMD) and pH, respectively. The results showed the potential of NIRS to analyze DM, ADF and CP in silage samples from pastures.El objetivo de este trabajo fue investigar el uso de la espectrofotometría de reflectancia en el infrarrojo cercano (NIRS) para predecir el valor nutritivo en ensilaje de pasturas y evaluar el tipo de estructura de silo (silo bolsa y trinchera) en las predicciones NIRS. Muestras (n = 120) provenientes de granjas comerciales fueron leídas en un equipo monocromador NIRS (NIR Systems, Silver Spring, Maryland, USA) en el rango de longitudes de onda de 400 a 2500 nm, en reflectancia. Modelos de calibración entre los datos químicos y los espectros NIRS fueron desarrollados usando el método de los cuadrados mínimos parciales. Los coeficientes de determinación en calibración (R2) y el error estándar de la validación cruzada (SEVC) fueron 0,73 (SECV: 1,2%), 0,81 (SECV: 2,0%), 0,75 (SECV: 6,6%), 0,80 (SECV: 6,7%), 0,80 (SECV: 4,0%), 0,60 (SECV: 3,6%) and 0,70 (SECV: 0,34) para cenizas, proteína cruda (PC), fibra detergente neutro (FDN), materia seca (MS), fibra detergente ácido (FDA), digestibilidad in vitro de la materia seca (DIVMS) y pH, respectivamente. Los resultados demuestran el potencial de la técnica NIRS para el análisis de rutina en ensilaje de pasturas para MS, FDA, y PC