Equations to predict methane emissions from cows fed at maintenance energy level in pasture-based systems

Ruminant production is a vital part of food industry but it raises environmental concerns, partly due to the associated methane outputs. Efficient methane mitigation and estimation of emissions from ruminants requires accurate prediction tools. Equations recommended by international organizations or scientific studies have been developed with animals fed conserved forages and concentrates and may be used with caution for grazing cattle. The aim of the current study was to develop prediction equations with animals fed fresh grass in order to be more suitable to pasture-based systems and for animals at lower feeding levels. A study with 25 nonpregnant nonlactating cows fed solely fresh-cut grass at maintenance energy level was performed over two consecutive grazing seasons. Grass of broad feeding quality, due to contrasting harvest dates, maturity, fertilisation and grass varieties, from eight swards was offered. Cows were offered the experimental diets for at least 2 weeks before housed in calorimetric chambers over 3 consecutive days with feed intake measurements and total urine and faeces collections performed daily. Methane emissions were measured over the last 2 days. Prediction models were developed from 100 3-day averaged records. Internal validation of these equations, and those recommended in literature, was performed. The existing in greenhouse gas inventories models under-estimated methane emissions from animals fed fresh-cut grass at maintenance while the new models, using the same predictors, improved prediction accuracy. Error in methane outputs prediction was decreased when grass nutrient, metabolisable energy and digestible organic matter concentrations were added as predictors to equations already containing dry matter or energy intakes, possibly because they explain feed digestibility and the type of energy-supplying nutrients more efficiently. Predictions based on readily available farm-level data, such as liveweight and grass nutrient concentrations were also generated and performed satisfactorily. New models may be recommended for predictions of methane emissions from grazing cattle at maintenance or low feeding levels.

Manipulation of milk fatty acid composition in lactating cows: opportunities and challenges

Public health policies recommend a population wide decrease in the consumption of saturated fatty acids (SFA) to lower the incidence of cardiovascular and metabolic diseases. In most developed countries, milk and dairy products are the major source of SFA in the human diet. Altering milk fat composition offers the opportunity to lower the consumption of SFA without requiring a change in eating habits. Supplementing the diet of lactating cows with oilseeds, plant oils and marine lipids can be used to replace the SFA in milk fat with monounsaturated fatty acids (MUFA), and to a lesser extent, polyunsaturated fatty acids (PUFA). Due to ruminal metabolism, the decreases in milk SFA are also accompanied by increases in trans fatty acids (TFA), including conjugated isomers. The potential to lower SFA, enrich cis MUFA and PUFA, and alter the abundance and distribution of individual TFA in milk differs according to oil source, form of lipid supplement and degree of oilseed processing, and the influence of other components in the diet. The present review summarises recent evidence on changes in milk fat composition that can be achieved using dietary lipid supplements and highlights the challenges to commercial production of modified milk and dairy products. A meta-analysis on the effects of oilseeds on milk fatty acid composition is also presented.

Assessment and improvement of biotransfer models to cow’s milk and beef used in exposure assessment tools for organic pollutants

The aim of this study was to assess and improve the accuracy of biotransfer models for the organic pollutants (PCBs, PCDD/Fs, PBDEs, PFCAs, and pesticides) into cow’s milk and beef used in human exposure assessment. Metabolic rate in cattle is known as a key parameter for this biotransfer, however few experimental data and no simulation methods are currently available. In this research, metabolic rate was estimated using existing QSAR biodegradation models of microorganisms (BioWIN) and fish (EPI-HL and IFS-HL). This simulated metabolic rate was then incorporated into the mechanistic cattle biotransfer models (RAIDAR, ACC-HUMAN, OMEGA, and CKow). The goodness of fit tests showed that RAIDAR, ACC-HUMAN, OMEGA model performances were significantly improved using either of the QSARs when comparing the new model outputs to observed data. The CKow model is the only one that separates the processes in the gut and liver. This model showed the lowest residual error of all the models tested when the BioWIN model was used to represent the ruminant metabolic process in the gut and the two fish QSARs were used to represent the metabolic process in the liver. Our testing included EUSES and CalTOX which are KOW-regression models that are widely used in regulatory assessment. New regressions based on the simulated rate of the two metabolic processes are also proposed as an alternative to KOW-regression models for a screening risk assessment. The modified CKow model is more physiologically realistic, but has equivalent usability to existing KOW-regression models for estimating cattle biotransfer of organic pollutants.

Alternative body sites for heat stress measurement in milking cows under tropical conditions and their relationship to the thermal discomfort of the animals

This study was conducted to determine the relationship among temperatures measured at different anatomical sites of the animal body and their daily pattern as indicative of the thermal stress in lactating dairy cows under tropical conditions. Environmental dry bulb (DBT) and black globe (BGT) temperatures and relative humidity (RH) were recorded. Rectal temperature (RT), respiratory frequency (RF), body surface (BST), internal base of tail (TT), vulva (VT) and auricular temperatures (AT) were collected, from 37 Black and White Holstein cows at 0700, 1300 and 1800 hours. RT showed a moderately and positive correlations with all body temperatures, ranging from 0.59 with TT to 0.64 with BST. Correlations among AT, VT and TT with RF were very similar (from 0.63 to 0.64) and were greater than those observed for RF with RT (0.55) or with BST (0.54). RF and RT were positively correlated to TT (0.63 and 0.59, respectively), AT (r = 0.63 for both) and VT (r = 0.64 and 0.63, respectively). Positive and very high correlations were observed among AT, VT and TT (from 0.94 to 0.97) indicating good association of temperatures measured in these anatomical sites. Correlations of BST with AT and VT were positive and very similar (0.71 and 0.72, respectively) and lower with TT (0.66). The AT, TT, VT and BST presented similar patterns and follow the variations of DBT through the day. Temperatures measured at different anatomical sites of the animal body have the potential to be used as indicative of the thermal stress in lactating dairy cows.

Hormone release and behavior during suckling and milking in Gir, Gir x Holstein, and Holstein cows

There are several different milking management systems in Latin America, because Gir cattle are reputed to be easily stressed and not well adapted to machine-milking. This paper, therefore, provides an overview of hormone release and behavior during suckling and milking in Gir cows and their crossbred offspring. Several experiments were performed to study oxytocin release during exclusive suckling or exclusive hand- and machine-milking, oxytocin, and prolactin release during a mixed suckling-milking system and oxytocin release after weaning. Cortisol concentrations and behavior were also examined. Concentration of oxytocin, released during suckling, and both types of milking were high, but the maximum concentration measured during suckling was significantly greater than that observed during exclusive milking. In the mixed suckling-milking system, the greatest oxytocin and prolactin releases were measured during suckling. Cortisol concentrations measured before, during, and after milking demonstrated that Gir x Holstein and Holstein cows were not stressed. On the other hand, although Gir had greater concentrations of cortisol, the percentage of residual milk for Gir cows was less than for dairy cows exposed to different stressful situations. In general, Gir cows and their crossbred offspring adapted to machine-milking, although these breeds can react negatively to milkers. Gir, Gir x Holstein, and Holstein cows all had similar cortisol levels during and after milking.

Evaluation of the pH and electrical conductivity in milk from jersey cows during the first month of lactation

In order to assess the influence of the colostrum period on pH and, electrical conductivity, we collected 418 milk samples from 127 Jersey cows. The samples were collected from healthy udders that did not present any bacterial growth in the microbiological examination. They were divided into eight groups as follows < 1/2 day; 1/2 and 1 degrees day; 2 degrees day; 3 degrees day; 4 degrees and 5 degrees day; 6 degrees and 7 degrees day; 8 degrees to 15 degrees day; 16 degrees to 30 degrees days of lactation. The samples were collected before milking and the following analyses were conducted: pH, electrical conductivity. In the first 24 hours of lactation, there was an reduction in electrical conductivity value, associated with an increase in pH value. We observed that transition of secretion from colostrum to milk, occurs during the first week of lactation; from 6(rd) day of lactation for pH value and 3(th) day for electrical conductivity value. We recommend the use the following figures as normal ranges for the first 24 hours of lactation (colostrum period): pH <= 6,51 and electrical conductivity <= 6,33 mS/cm; while for the interval between 2(nd) and 7(th) days of lactation (transition from colostrum to milk) we suggest the use of the values as normal ranges: pH <= 6,66 and electrical conductivity <= 5,93 mS/cm.