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Predicting the grass dry matter intake (GDMI), milk yield (MY) or milk fat and protein yield (milk solids yield (MSY)) of the grazing dairy herd is difficult. Decisions with regard to grazing management are based on guesstimates of the GDMI of the herd, yet GDMI is a critical factor influencing MY and MSY. A data set containing animal, sward, grazing management and concentrate supplementation variables recorded during weeks of GDMI measurement was used to develop multiple regression equations to predict GDMI, MY and MSY. The data set contained data from 245 grazing herds from 10 published studies conducted at Teagasc, Moorepark. A forward stepwise multiple regression technique was used to develop the multiple regression equations for each of the dependent variables (GDMI, MY, MSY) for three periods during the grazing season: spring (SP; 5 March to 30 April), summer (SU; 1 May to 31 July) and autumn (AU; 1 August to 31 October). The equations generated highlighted the importance of different variables associated with GDMI, MY and MSY during the grazing season. Peak MY was associated with an increase in GDMI, MY and MSY during the grazing season with the exception of GDMI in SU when BW accounted for more of the variation. A higher body condition score (BCS) at calving was associated with a lower GDMI in SP and SU and a lower MY and MSY in all periods. A higher BCS was associated with a higher GDMI in SP and SU, a higher MY in SU and AU and a higher MSY in all periods. The pre-grazing herbage mass of the sward (PGHM) above 4 cm was associated with a quadratic effect on GDMI in SP, on MY in SP and SU and on MSY in SU. An increase in daily herbage allowance (DHA) above 4 cm was associated with an increase in GDMI in AU, an increase in MY in SU and AU and MSY in AU. Supplementing grazing dairy cows with concentrate reduced GDMI and increased MY and MSY in all periods. The equations generated can be used by the Irish dairy industry during the grazing season to predict the GDMI, MY and MSY of grazing dairy herds.

International audience; This study evaluated the prediction accuracy of grass dry-matter intake (GDMI) and milk yield predicted by the GrazeIn model using a large database representing 8787 per cow GDMI measurements. In this study, the animal input variables (age, parity, week of lactation, potential peak milk yield, milk fat content, milk protein content, bodyweight, body condition score (BCS), week of conception, BCS at calving and calf birth weight) were investigated. The mean actual GDMI of the database was 159kg DM per cow d(-1) and GrazeIn predicted a mean GDMI for the database of 155kg DM per cow d(-1). The mean bias was -04kg DM per cow d(-1). GrazeIn predicted GDMI for the total database with an RPE of 155% at cow level. The mean actual daily milk yield of the database was 213kg per cow d(-1) and GrazeIn predicted a daily milk yield for the database of 222kg per cow d(-1). The mean bias was +09kg per cow d(-1). GrazeIn predicted milk yield for the total database with an RPE of 167% at cow level. From the evaluation, GrazeIn predicted milk yield of all cows in late lactation with a larger level of error than in early and mid-lactation. This error appears to be due to the persistency of the lactation curve used by the model, which results in a higher predicted milk yield in late lactation compared with the actual milk yield.

International audience; This study evaluated the prediction accuracy of grass dry-matter intake (GDMI) and milk yield predicted by the model GrazeIn using a database representing 522 grazing herds. The GrazeIn input variables under consideration were fill value (FV), grass energy content [Unite Fourragere Lait (UFL)], grass protein value [true protein absorbable in the small intestine when rumen fermen energy is limiting microbial protein synthesis in the rumen (PDIE)], pre-grazing herbage mass (PGHM), daily herbage allowance (DHA) and concentrate supplementation. GrazeIn was evaluated using the relative prediction error (RPE). The mean actual GDMI and milk yields of grazing herds in the database ranged from 99-220kg DM per cowd(-1) and 89-418kg per cowd(-1), respectively. The accuracy of predictions for the total database estimated by RPE was 122 and 128% for GDMI and milk yield, respectively. The mean bias (predicted minus actual) for GDMI was -03kg DM per cowd(-1) and for milk yield was +09kg per cowd(-1). GrazeIn predicted GDMI with a level of error 4% RPE for spring, summer and autumn. GrazeIn predicted milk yield in autumn (RPE=176%) with a larger error in comparison with spring (RPE=104%) and summer (RPE=110%). Future studies should focus on the adaptation of GrazeIn to correct and improve the prediction of milk yield in autumn.

Understanding rumen microbial ecology is essential for the development of feed systems designed to improve livestock productivity, health and for methane mitigation strategies from cattle. Although rumen microbial communities have been studied previously, few studies have applied next-generation sequencing technologies to that ecosystem. The aim of this study was to characterize changes in microbial community structure arising from feeding dairy cows two widely used diets: pasture and total mixed ration (TMR). Bacterial, archaeal and protozoal communities were characterized by terminal restriction fragment length polymorphism of the amplified SSU rRNA gene and statistical analysis showed that bacterial and archaeal communities were significantly affected by diet, whereas no effect was observed for the protozoal community. Deep amplicon sequencing of the 16S rRNA gene revealed significant differences in the bacterial communities between the diets and between rumen solid and liquid content. At the family level, some important groups of rumen bacteria were clearly associated with specific diets, including the higher abundance of the Fibrobacteraceae in TMR solid samples and members of the propionate-producing Veillonelaceae in pasture samples. This study will be relevant to the study of rumen microbial ecology and livestock feed management.

In 2006, after 44 years of eradication of malaria, Jamaica had an outbreak of Plasmodium falciparum: 406 confirmed cases between September 2006 and December 2009 with a peak of the epidemic in December 2006. In response to the outbreak, the Ministry of Health launched an emergency response through early detection and prompt treatment of cases, vector control, public education and intersectoral collaboration. Ninety percent (361) of cases were residents of Kingston, and 63.6% were identified through house to house surveillance visits. For 56% of the confirmed cases, treatment with chloroquine was initiated within a week of onset of symptoms. Only one (0.3%) of 358 cases who had a post-treatment smear on day 7 had a persistent asexual parasitaemia, while none of the 149 persons who had a follow-up smear on day 28 was positive. The outbreak highlighted the need for increased institutional capacity for surveillance, confirmation and treatment of malaria as well as effective prevention and control of outbreaks which can occur after elimination. Jamaica appears to have successfully eliminated malaria after its reintroduction.

The objective of the present study was to compare the enteric methane (CH4) emissions and milk production of spring-calving Holstein-Friesian cows offered either a grazed perennial ryegrass diet or a total mixed ration (TMR) diet for 10 wk in early lactation. Forty-eight spring-calving Holstein-Friesian dairy cows were randomly assigned to 1 of 2 nutritional treatments for 10 wk: 1) grass or 2) TMR. The grass group received an allocation of 17 kg of dry matter (DM) of grass per cow per day with a pre-grazing herbage mass of 1,492 kg of DM/ha. The TMR offered per cow per day was composed of maize silage (7.5 kg of DM), concentrate blend (8.6 kg of DM), grass silage (3.5 kg of DM), molasses (0.7 kg of DM), and straw (0.5 kg of DM). Daily CH4 emissions were determined via the emissions from ruminants using a calibrated tracer technique for 5 consecutive days during wk 4 and 10 of the study. Simultaneously, herbage dry matter intake (DMI) for the grass group was estimated using the n-alkane technique, whereas DMI for the TMR group was recorded using the Griffith Elder feeding system. Cows offered TMR had higher milk yield (29.5 vs. 21.1 kg/d), solids-corrected milk yield (27.7 vs. 20.1 kg/d), fat and protein (FP) yield (2.09 vs. 1.54 kg/d), bodyweight change (0.54 kg of gain/d vs. 0.37 kg of loss/d), and body condition score change (0.36 unit gain vs. 0.33 unit loss) than did the grass group over the course of the 10-wk study. Methane emissions were higher for the TMR group than the grass group (397 vs. 251 g/cow per day). The TMR group also emitted more CH4 per kg of FP (200 vs. 174 g/kg of FP) than did the grass group. They also emitted more CH4 per kg of DMI (20.28 vs. 18.06 g/kg of DMI) than did the grass group. In this study, spring-calving cows, consuming a high quality perennial ryegrass diet in the spring, produced less enteric CH4 emissions per cow, per unit of intake, and per unit of FP than did cows offered a standard TMR diet.

International audience; Increasing milk production from pasture while increasing grass dry matter intake (GDMI) and lowering methane (CH4) emissions are key objectives of low-cost dairy production systems. It was hypothesized that offering swards of low herbage mass with increased digestibility leads to increased milk output. A grazing experiment was undertaken to investigate the effects of varying levels of HM on CH4 emissions, GDMI and milk production of grazing dairy cows during the mid-season grazing period (June to July). Prior to the experiment, 46 Holstein-Friesian dairy cows (46 d in milk) were randomly assigned to 1 of 2 treatments (n=23) in a randomized block design. The 2 treatments consisted of 2 target pregrazing HM: 1,000kg of dry matter (DM)/ha (low herbage mass, LHM) or 2,200kg of DM/ha (high herbage mass, HHM). The experimental period lasted 2 mo from June 1 until July 31. Within the experimental period, there were 2 measurement periods, measurement 1 (M1) and measurement 2 (M2), where CH4 emissions, GDMI, and milk production were measured. Mean herbage mass throughout the measurement periods was 1,075kg of DM/ha and 1,993kg of DM/ha for the LHM and HHM treatments, respectively. Grass quality in terms of organic matter digestibility was significantly higher for the LHM treatment in M2 (+12g/kg of DM). In M1, the effect of herbage mass on grass quality was approaching significance in favor of the LHM treatment. Herbage mass did not significantly affect milk production during the measurement periods. Cows grazing the LHM swards had increased GDMI in M1 (+1.5kg of DM) compared with cows grazing the HHM swards; no difference in GDMI was observed in M2. Grazing HHM swards increased CH4 production per cow per day (+42g), per kilogram of milk yield (+3.5g/kg of milk), per kilogram of milk solids (+47g/kg of milk solids), and per kilogram of GDMI (+3.1g/kg of GDMI) in M2. Cows grazing the HHM swards lost a greater proportion of their gross energy intake as CH4 during both measurement periods (+0.9% and +1% for M1 and M2, respectively). It was concluded that grazing LHM swards would increase grass quality with a concurrent reduction in CH4 emissions.

Mitigating the proportion of energy intake lost as methane could improve the sustainability and profitability of dairy production. As widespread measurement of methane emissions is precluded by current in vivo methods, the development of an easily measured proxy is desirable. An equation has been developed to predict methane from the mid-infrared (MIR) spectra of milk within routine milk-recording programs. The main goals of this study were to improve the prediction equation for methane emissions from milk MIR spectra and to illustrate its already available usefulness as a high throughput phenotypic screening tool. A total of 532 methane measurements considered as reference data (430 ± 129 g of methane/day) linked with milk MIR spectra were obtained from 165 cows using the SF6 technique. A first derivative was applied to the MIR spectra. Constant (P0), linear (P1) and quadratic (P2) modified Legendre polynomials were computed from each cows stage of lactation (days in milk), at the day of SF6 methane measurement. The calibration model was developed using a modified partial least-squares regression on first derivative MIR data points × P0, first derivative MIR data points × P1, and first derivative MIR data points × P2 as variables. The MIR-predicted methane emissions (g/day) showed a calibration coefficient of determination of 0.74, a cross-validation coefficient of determination of 0.70 and a standard error of calibration of 66 g/day. When applied to milk MIR spectra recorded in the Walloon Region of Belgium (≈2 000 000 records), this equation was useful to study lactational, annual, seasonal, and regional methane emissions. We conclude that milk MIR spectra has potential to be used to conduct high throughput screening of lactating dairy cattle for methane emissions. The data generated enable monitoring of methane emissions and production characteristics across and within herds. Milk MIR spectra could now be used for widespread screening of dairy herds in order to develop management and genetic selection tools to reduce methane emissions.

We surveyed the prevalence of obesity in the general population in Jamaica, and examined the relationship between it and lifestyle. The survey population consisted of 1,935 inhabitants in Jamaica, whose body weight, height, marital status, educational history, employment status and other obesity-associated lifestyle factors were surveyed. Six major findings emerged. The first finding is that the proportion of obesity in women was very high, and there was a big gender difference. Secondly, a lower prevalence towards obesity was associated with cohabitation of the subjects in both genders, and higher educational levels in female subjects. Thirdly, the proportion of the subjects who considered their weight to be quite acceptable was higher in the obese/overweight groups in both genders. Fourthly, exercise frequency showed a negative correlation with the body mass index (BMI) in men, and the frequency of exercising was apparently lower in women than in men. Fifthly, as for dietary factors, in both genders vegetables showed a negative correlation with the BMI. Sixthly, non-smokers were also associated with a lower obesity prevalence in men. In conclusions, these findings suggest that social and lifestyle factors such as the educational level, marital status and dietary habits of the general population influence Jamaican obesity.

Aim: This study was designed to investigate the point prevalence and pattern of obesity in the Jamaican adult population. Methods: A two-stage-stratified random sampling design was used, and individuals aged 15 years and over were interviewed. In addition, anthropometric measurements were performed. The data were analysed using the SPSS statistical software version 8. Non-response was documented and factored into the final analysis of the survey data. Results: A total of 2105 individuals responded to the all island survey, with 69% being females. Truncal obesity and gynoid obesity showed similar prevalence data. Both were affected by increasing age, being female, level of education attained and smoking status. Conclusions: Jamaica has a point prevalence of obesity, truncal 36.2% and gynoid 34.1%, in the 15 and over age group.

OBJECTIVE This study was designed to investigate the point prevalence of diabetes in Jamaica. RESEARCH DESIGN AND METHODS A two-stage stratified random sampling design was used, and individuals aged 15 years and over were interviewed. Nonresponse was documented and factored into the final analysis of the survey data. The overall response rate obtained was 57.9%. All subjects with fasting blood glucose (FBG) > 6.1 mmol/1 (110 mg/dl) were brought back for an abbreviated glucose tolerance test. The data was analyzed using Epi 5, an advanced statistical program designed specifically for use with epidemiological data. RESULTS The 2,109 subjects who participated were the basis for estimates of diabetes and IGT prevalence. Among those with previously diagnosed diabetes, diet therapy alone, oral hypoglycemic agents plus diet therapy, insulin therapy, and lack of treatment were reported. CONCLUSIONS By the World Health Organization (WHO) criteria, Jamaica has a point prevalence of diabetes of 17.9% in the 15-and-over age-group.

Trevor S Ferguson1, Novie OM Younger1, Nadia D Morgan2, Marshall K Tulloch-Reid1, Shelly R McFarlane1, Damian K Francis1, Andriene Grant3, Eva Lewis-Fuller3, Rainford J Wilks11Epidemiology Research Unit, Tropical Medicine Research Institute, The University of the West Indies, Mona, Kingston, Jamaica; 2Department of Internal Medicine, SUNY Downstate Medical Center, Brooklyn, New York, NY, USA; 3Ministry of Health, Kingston, JamaicaPurpose: Although heart attacks and strokes are among the three leading causes of death in Jamaica, their prevalence among Jamaican adults is not known. This study aims to estimate the prevalence of these conditions and their association with known cardiovascular disease (CVD) risk factors, including age, hypertension, diabetes, overweight/obesity, and hypercholesterolemia.Participants and methods: A national survey of 2848 Jamaicans aged 15–74 years was performed between 2007 and 2008. An interviewer-administered questionnaire was used to collect data on demographic characteristics, educational achievement, medication history, and social habits, including smoking and alcohol use. Participants were specifically asked whether they had been diagnosed with a heart attack or stroke. Blood pressure, anthropometry, fasting glucose, and total cholesterol were measured by the trained interviewers. Heart attack and stoke prevalence estimates were adjusted for the complex survey design and the age and sex distribution of the Jamaican population.Results: The estimated prevalence of heart attacks was 0.7% (95% confidence interval [CI] 0.4%–1.2%) (0.9% for men; 0.4% for women) and of strokes was 1.4% (CI 1.0%–1.9%) (1.2% for men; 1.5% for women) with no significant sex differences. The prevalence of reported heart attacks increased with age and was more common in those with hypercholesterolemia. The prevalence of strokes was highest among people aged 55–74 years; those with primary education only; those with hypertension, diabetes, or hypercholesterolemia; former smokers; and former drinkers. In multivariable logistic regression models adjusted for age, sex, and body mass index (BMI), reported heart attacks were higher in men, older participants, and those with secondary education and lower in current drinkers. In similar models, strokes were positively associated with diabetes, hypercholesterolemia, and past alcohol use, after adjusting for age, sex, and BMI.Conclusion: The overall prevalence of self-reported heart attacks and strokes is low in Jamaica but higher among people with CVD risk factors.Keywords: heart attack, stroke, Jamaica, cardiovascular disease