Development and evaluation of a model to predict sheep nutrient requirements and feed utilisation

A new feeding system for sheep, called MIPAF, was developed by integrating previously published equations with new ones to predict energy and protein requirements as well as feed utilization of sheep. Special emphasis was given to dairy sheep, whose specific needs are not considered by most sheep feeding systems, and to some of the environmental factors that affect requirements. Original equations were added to predict fluxes in body energy reserves from body weight (BW) and body condition score. The prediction of supply of nutrients was based on the discount system of Van Soest. Thus, the MIPAF system predicts feed value as a function of the specific feeding level of the sheep that receive the ration. The ability of the MIPAF model to predict BW variations was evaluated using data from six studies with adult sheep (13 treatments with lactating ewes and 15 with dry ewes or wethers). The model predicted the variations of BW in sheep with no bias, but with high rooted mean squared prediction error (RMSPE) (mean bias = -0.1 g/d; P > 0.1; RMSPE = 44.9 g/d; n = 28). Three extreme outliers were discarded because the treatment diets, made only of wheat straw and supplied to mature wethers, had very low CP concentrations (less than 3.25%, DM basis). After the outliers were removed, the prediction error improved but the mean bias became significantly different from zero (mean bias = -12.3 g/d; P < 0.05; RMSPE = 29.6 g/d; n = 25). Prediction accuracy was different between lactating and non lactating sheep. Variations of BW in lactating ewes were predicted with high accuracy (mean bias = 6.8 g/d; P > 0.1; RMSPE = 18.7 g/d; n = 13), while for dry ewes the model was less accurate, under predicting the variations in BW (mean bias = -33.0 g/d, P < 0.001; RMSPE = 38.1 g/d; n = 12). The evaluations included published experiments with sheep of diverse body sizes and physiological stages fed diverse diets at various levels of nutrition. This suggests that the MIPAF model can be used to evaluate diets and animal performance in a variety of production settings with good accuracy

A multivariate and stochastic approach to identify key variables to rank dairy farms on profitability

The economic efficiency of dairy farms is the main goal of farmers. The objective of this work was to use routinely available information at the dairy farm level to develop an index of profitability to rank dairy farms and to assist the decision-making process of farmers to increase the economic efficiency of the entire system. A stochastic modeling approach was used to study the relationships between inputs and profitability (i.e., income over feed cost; IOFC) of dairy cattle farms. The IOFC was calculated as: milk revenue + value of male calves + culling revenue - herd feed costs. Two databases were created. The first one was a development database, which was created from technical and economic variables collected in 135 dairy farms. The second one was a synthetic database (sDB) created from 5,000 synthetic dairy farms using the Monte Carlo technique and based on the characteristics of the development database data. The sDB was used to develop a ranking index as follows: (1) principal component analysis (PCA), excluding IOFC, was used to identify principal components (sPC); and (2) coefficient estimates of a multiple regression of the IOFC on the sPC were obtained. Then, the eigenvectors of the sPC were used to compute the principal component values for the original 135 dairy farms that were used with the multiple regression coefficient estimates to predict IOFC (dRI; ranking index from development database). The dRI was used to rank the original 135 dairy farms. The PCA explained 77.6% of the sDB variability and 4 sPC were selected. The sPC were associated with herd profile, milk quality and payment, poor management, and reproduction based on the significant variables of the sPC. The mean IOFC in the sDB was 0.1377 ± 0.0162 euros per liter of milk (€/L). The dRI explained 81% of the variability of the IOFC calculated for the 135 original farms. When the number of farms below and above 1 standard deviation (SD) of the dRI were calculated, we found that 21 farms had dRI-1 SD, 32 farms were between -1 SD and 0, 67 farms were between 0 and +1 SD, and 15 farms had dRI+1 SD. The top 10% of the farms had a dRI greater than 0.170 €/L, whereas the bottom 10% farms had a dRI lower than 0.116 €/L. This stochastic approach allowed us to understand the relationships among the inputs of the studied dairy farms and to develop a ranking index for comparison purposes. The developed methodology may be improved by using more inputs at the dairy farm level and considering the actual cost to measure profitability

Short communication: In vitro rumen gas production and starch degradation of starch-based feeds depend on mean particle size

Our objective was to model the effect of mean particle size (mPS) on in vitro rumen starch degradation (IVSD) and the kinetics of gas production for different starch-based feeds. For each feed, 2 batches of the same grains were separately processed through 2 different mills (cutter or rotor speed mills), with or without different screens to achieve a wide range of mPS (0.32 to 3.31 mm for corn meals; 0.19 to 2.81 mm for barley meals; 0.16 to 2.13 mm for wheat meals; 0.28 to 2.32 mm for oat meals; 0.21 to 2.36 mm for rye meals; 0.40 to 1.79 for sorghum meals; 0.26 to 4.71 mm for pea meals; and 0.25 to 4.53 mm for faba meals). The IVSD data and gas production kinetics, obtained by fitting to a single-pool exponential model, were analyzed using a completely randomized design, in which the main tested effect was mPS (n = 6 for all tested meals, except n = 7 for corn meals and n = 5 for sorghum meals). Rumen inocula were collected from 2 fistulated Holstein dairy cows that were fed a total mixed ration consisting of 16.2% crude protein, 28.5% starch, and 35.0% neutral detergent fiber on a dry matter basis. The IVSD, evaluated after 7 h of rumen incubation, decreased linearly with increasing mPS for corn, barley, wheat, rye, pea, and faba meals, and decreased quadratically with increasing mPS for the other meals. The y-axis intercept for 7-h IVSD was below 90% starch for corn, barley, and rye feeds and greater than 90% for the other tested feeds. The mPS adjustment factors for the rate of rumen starch degradation varied widely among the different tested feeds. We found a linear decrease in starch degradation with increasing mPS for barley, wheat, rye, and pea meals, whereas we noted a quadratic decrease in starch degradation for the other tested meals. Further, we observed a linear decrease in the rate of gas production with increasing mPS in each tested feed, except for pea meal, which had a quadratic relationship. For each 1 mm increase in mPS, the gas production was adjusted by -0.009 h-1 for corn, -0.011 h-1 for barley, -0.008 h-1 for wheat, and -0.006 h-1 for faba, whereas numerically greater adjustments were needed for oat (-0.022 h-1), rye (-0.017 h-1), and sorghum (-0.014 h-1). These mPS adjustment factors could be used to modify the starch-based feed energy values as a function of mean particle size, although in vivo validation is required

Analyzing Food Supply and Distribution Systems using complex systems methodologies

This paper discusses how a complex-systems perspective can shed light on the analysis of complex food-systems meeting urban food needs. The common features between complex systems and Food Supply and Distribution Systems (FSDS) are explored. A brief review of the major approaches - agent-based models (ABM), social network analysis (SNA), and system dynamics (SD) - is developed in order to make an assessment on the analysis performance of different complex system methodologies while dealing with FSDS. After sifting out the most suitable methodology for the study of FSDS, a system archetype analysis of the FSDS dynamics is elicited from the methodological guide of FAO, the United Nations Food and Agriculture Organization. To finalize, three basic points for the analysis of FSDS obtained from the current research are explained. This content is part of the content leading the SD updates to FAO’s FSDS methodological guide

The Small Ruminant Nutrition System: development and evaluation of a goat submodel

The Small Ruminant Nutrition System (SRNS) is a computer model based on the structure of the Cornell Net Carbohydrate and Protein System for Sheep.A version of the SRNS for goats is under development and evaluation. In the SRNS for goats, energy and protein requirements are predicted based on the equations developed for the SRNS for sheep, modified to account for specific requirements of goats. Feed biological values are predicted based on carbohydrate and protein fractions and their ruminal degradation rates, on forage, concentrate and liquid passage rates, on microbial growth, and on physically effective fiber. The evaluation of the SRNS for goats based on literature data showed that the SRNS accurately predicted the ADG of kids (RMSEP = 32.5 g/d; r2 = 0.85; CCC = 0.91), and the daily MEI (RMSEP = 0.24 Mcal/d g/d; r2 = 0.99; CCC = 0.99) and the energy balance (RMSEP = 0.20 Mcal/d g/d; r2 = 0.87; CCC = 0.90) of goats

A Preliminary Study on a New Approach to Estimate Water Resource Allocation: The Net Water Footprint Applied to Animal Products☆

AbstractWe propose the Net Waterfootprint (WFPnet) method to estimate the water footprint (WFP) of food products, in alternative to the current WFP method, based on absolute values. We compared the WFP and WFPnet methods for cattle milk and meat production in different feed efficiency (high and low) and crop water use efficiency (WUE; high, medium and low) scenarios under Mediterranean conditions. The WFP values were, on average, much higher than the WFPnet values for both meat and milk. The WFPnet method appears to be able to properly quantify the water consumption needed for animal food production

Using system thinking to study sustainability of Colombian dairy system

Colombia raises 1.73% of global livestock inventory. Key challenges of the sector are to increase the animal production in order to nutritionally sustain the growing population, to ensure a rational use of natural resources for agricultural purposes, either combining criteria of economic sustainability and social equity. Agriculture can be considered as networking factor for productive, environmental and social components. In Colombia development of rural areas comprised complex dynamics affected by low technological farming systems and conflicts over land use and ownership. Free trade and climate change also act on the system as exogenous variables. The use of modeling tools and methodologies, such as system thinking and system dynamics, could help to manage rural development policies taking into account different components and to analyze their interconnections within the system. This comprehensive approach can also be useful to stimulate a multidisciplinary focus on future trends of development. The aim of this work was to qualitatively explain the main loops limiting and enhancing the development of the rural areas oriented to milk production in Colombia, using causal maps and conceptual diagrams. Three main components and their relationships were analyzed: Production and Economics, Environment and Social. Strategies of future development of rural areas suitable for milk production were suggested. Dairy farm management and rational land use supported by technical assistance were proposed alternatively to extensive-extractive livestock system to reach economic, social and environmental benefits

A conceptual model to describe heat stress in dairy cows from actual to questionable loops

Thermal environment is recognized to be one the most important ecological factor to determine domestic animal growth, development and productivity for direct and indirect effects on its physiology and behavior. Despite having specific and individual adaptation, is very common, within seasonal or diurnal temperature variations, animals deal with situations outside their thermal comfort zone. Due to heat stress, dairy cows reduce milk production and fertility, and therefore, had achieved an increasing in metabolic disorders incidence, causing low revenues to farm in short and medium periods. Climate change is perhaps one of the most important factors on animal responses. This study aimed to describe and understand the interactions of variables associated with heat stress in dairy cattle. System thinking approach to this specific physiological mechanism might help to better focus managerial aspects related to grazing conditions and animal needs. A causal loop diagram annotation used to connect biological variables included in system boundaries. Causal connections were validated with literature citations on the heat stress influence. The most important feedback loops highlighted underline dominant structure and expected patterns. Four balancing loops involved in physiological mechanisms used by animals in order to reduce metabolic heat production and to regulate homeostasis of the internal temperature, were found.Se reconoce que el ambiente térmico es uno de los factores ecológicos más importantes para determinar el crecimiento, el desarrollo y la productividad de animales domésticos con efectos directos e indirectos sobre su fisiología y comportamiento. A pesar de tener una adaptación específica e individual, es muy común que, dentro de las variaciones de temperatura estacionales o diurnas, los animales se enfrenten a situaciones fuera de su zona de confort térmico. Debido al estrés calórico, las vacas lecheras reducen su producción y fertilidad, y por lo tanto, llevan a cabo un aumento en la incidencia de trastornos metabólicos, causando bajos causando bajos ingresos para la finca en corto y mediano plazo. El cambio climático es quizás uno de los factores más importantes en las respuestas de los animales. Este estudio tuvo como objetivo describir y comprender las interacciones de las variables asociadas con el estrés por calor en el ganado lechero. El enfoque del sistema aplicado a este mecanismo fisiológico específico ayuda aliviar el estrés calórico en vacas lecheras cuando se relacionan los aspectos de pastoreo y las necesidades del animal. Se usó una anotación de diagrama de bucle causal para conectar las variables biológicas incluidas en los límites del sistema. Las conexiones causales se validaron con algunas citas bibliográficas sobre la influencia del estrés calórico. Las interconexiones de retroalimentación más importantes resaltadas, subrayan la estructura dominante y los patrones esperados. Se encontraron cuatro bucles balance implicados en los mecanismos fisiológicos utilizados por los animales para reducir la producción de calor metabólico y para regular la homeostasis de la temperatura interna

Models for estimating feed intake in small ruminants

This review deals with the most relevant limits and developments of the modeling of intake of sheep and goats reared intensively and extensively. Because small ruminants are normally fed ad libitum, voluntary feed intake is crucial in feeding tactics and strategies aimed at optimal animal production. The effects of genetic, neuroendocrine, hormonal, feed and environmental factors on voluntary feed intake were discussed. Then, several mathematical models to estimate dry matter intake (DMI) were examined, with emphasis on empirical models for sheep and goats in intensive farm systems or in extensive areas under pasture or rangeland conditions. A sensitivity analysis of four models of prediction of DMI in housed lactating dairy sheep and meat sheep breeds was also presented. This work evidenced a large variability in the approaches used and in the variables considered for housed sheep and goats. Regarding the estimation of feed intake for grazing sheep and browsing goats, the accuracy of estimates based on empirical models developed so far is very low when applied out of the boundaries of the studied system. Feeding experiments indoors and outdoors remain fundamental for a better modeling and understanding of the interactions between feeds and small ruminants. However, there is a need for biological and theoretical frameworks in which these experiments should be carried out, so that appropriate empirical or mechanistic equations to predict DMI could be developed

Seasonal variation in the fatty acid profile in meat of Sarda suckling lambs

This study evaluated temporal changes in fatty acid (FA) composition of meat from Sarda suckling lambs reared in Sardinia, with emphasis on polyunsaturated fatty acids (PUFA) and conjugated linoleic acid (CLA). From December to April, 25 lambs were randomly chosen in a slaughter house and slaughtered at about 30 days of age (5 lambs/rearing month). From each carcass, the Femoral biceps muscle was used to determine the chemical and FA composition. Intramuscular lipid content ranged from 1.72% to 2.34% and protein content from 19.2% to 20.2%. Concentrations of several FA and FA groups were significantly influenced by rearing month. The greatest variation between months was observed for monounsaturated FA (MUFA), which ranged from 35.3% to 43.5%, and total PUFA, which varied from 18% to 26% of total FA. The content of FA of interest, especially α-linolenic (18:3 n-3) acid, CLA and long chain PUFA n-3, i.e. EPA (20:5 n-3), DPA (22:5 n-3) and DHA (22:6 n-3), did not vary among months. Lamb meat analysed in the study evidenced a constant amount of FA of nutritional interest, especially of the omega-3 family and CLA, in all months.Highlights Composition and fatty acid profile of meat from Sarda suckling lambs were evaluated during different months of production. Suckling lamb meat evidenced a low fat content and a constant amount of PUFA n-3 in all slaughter months. PUFA n-3 and CLA did not vary with slaughter months in suckling lambs