Genetic parameters and evaluations from single- and multiple-trait analysis of dairy cow fertility and milk production

Genetic parameters and breeding values for dairy cow fertility were estimated from 62 443 lactation records. Two-trait analysis of fertility and milk yield was investigated as a method to estimate fertility breeding values when culling or selection based on milk yield in early lactation determines presence or absence of fertility observations in later lactations. Fertility traits were calving interval, intervals from calving to first service, calving to conception and first to last service, conception success to first service and number of services per conception. Milk production traits were 305-day milk, fat and protein yield. For fertility traits, range of estimates of heritability (h(2)) was 0.012 to 0.028 and of permanent environmental variance (c(2)) was 0.016 to 0.032. Genetic correlations (r(g)) among fertility traits were generally high ( > 0.70). Genetic correlations of fertility with milk production traits were unfavourable (range -0.11 to 0.46). Single and two-trait analyses of fertility were compared using the same data set. The estimates of h(2) and c(2) were similar for two types of analyses. However, there were differences between estimated breeding values and rankings for the same trait from single versus multi-trait analyses. The range for rank correlation was 0.69-0.83 for all animals in the pedigree and 0.89-0.96 for sires with more than 25 daughters. As single-trait method is biased due to selection on milk yield, a multi-trait evaluation of fertility with milk yield is recommended. (C) 2002 Elsevier Science B.V. All rights reserved.

Farm-level performance of genetically modified cotton - A frontier analysis of cotton production in Maharashtra

In this paper, the yield increases resulting from the cultivation of Bt cotton in Maharashtra, India, are analysed. The study relies on commercial farm, rather than trial, data and is among the first of its kind to be based on real farm and market conditions. Findings show that since its commercial release in 2002, Bt cotton has had a significant positive impact on yields and on the economic performance of cotton growers in Maharashtra. This difference remains even after controlling for different soil and insecticide inputs in the production of Bt cotton. There is also significant spatial and temporal variation in this 'benefit', and much depends upon where production is taking place and on the season.

Alternatives to linear analysis of energy balance data from lactating dairy cows

The current energy requirements system used in the United Kingdom for lactating dairy cows utilizes key parameters such as metabolizable energy intake (MEI) at maintenance (MEm), the efficiency of utilization of MEI for 1) maintenance, 2) milk production (k(l)), 3) growth (k(g)), and the efficiency of utilization of body stores for milk production (k(t)). Traditionally, these have been determined using linear regression methods to analyze energy balance data from calorimetry experiments. Many studies have highlighted a number of concerns over current energy feeding systems particularly in relation to these key parameters, and the linear models used for analyzing. Therefore, a database containing 652 dairy cow observations was assembled from calorimetry studies in the United Kingdom. Five functions for analyzing energy balance data were considered: straight line, two diminishing returns functions, (the Mitscherlich and the rectangular hyperbola), and two sigmoidal functions (the logistic and the Gompertz). Meta-analysis of the data was conducted to estimate k(g) and k(t). Values of 0.83 to 0.86 and 0.66 to 0.69 were obtained for k(g) and k(t) using all the functions (with standard errors of 0.028 and 0.027), respectively, which were considerably different from previous reports of 0.60 to 0.75 for k(g) and 0.82 to 0.84 for k(t). Using the estimated values of k(g) and k(t), the data were corrected to allow for body tissue changes. Based on the definition of k(l) as the derivative of the ratio of milk energy derived from MEI to MEI directed towards milk production, MEm and k(l) were determined. Meta-analysis of the pooled data showed that the average k(l) ranged from 0.50 to 0.58 and MEm ranged between 0.34 and 0.64 MJ/kg of BW0.75 per day. Although the constrained Mitscherlich fitted the data as good as the straight line, more observations at high energy intakes (above 2.4 MJ/kg of BW0.75 per day) are required to determine conclusively whether milk energy is related to MEI linearly or not.

Environmental impact of genetically modified cotton in South Africa

This paper presents the results of a large-scale study designed to monitor the impact arising from the introduction of insect-resistant Bt cotton in the Makhathini Flats, Republic of South Africa. Bt cotton provides a degree of resistance to cotton bollworm complex (Lepidoptera). Data were collected on the use of insecticides (type and quantity) as well as the farm-level economics of production from over 2200 farmers in three growing seasons (1998/1999, 1999/2000 and 2000/2001). and the results are discussed within the context of environmental impact brought about by insecticide. Over the three seasons of the study it was clear that Bt cotton provided benefits in terms of higher yield and gross margin relative to farmers growing conventional (non-Bt) cotton, and the benefits were particularly apparent for the smallest producers. Bt growers also used significantly less insecticide than growers of non-Bt cotton. Once quantities of insecticide applied to Bt and non-Bt cotton were converted into a Biocide Index and an Environmental Impact Quotient (EIQ) in order to allow for differences in terms of toxicity and persistence in the environment, it was apparent that the growing of Bt had a less negative impact on the environment. While this points to beneficial impacts on agricultural sustainability there are wider concerns regarding the vulnerability of resource-poor farmers in an area with limited (as yet) marketing options for their product and options for livelihood diversification both within and outside agriculture. Cotton producers in Makhathini are vulnerable as they rely on just One company for inputs (including, credit) and for their market. While Bt cotton provides benefits it does not in itself address some of the structural limitations that farmers face. (c) 2006 Elsevier B.V. All rights reserved.

Estimation of milk production from smallholder dairy cattle in the coastal lowlands of Kenya

A study was carried out on 92 smallholder farms in Kwale district in Coast Province of Kenya to estimate the milk yield. The effect of concentrate feed supplementation on milk yield was also evaluated. Data were collected during a one-year observational longitudinal study. Analysis was done for 371 observations following 63 calving events. The mean annual milk offtake was estimated at 2021 kg/cow. Forty-nine (77.8%) of the lactating cows were supplemented with concentrate feeds at varying rates of 0.5-3.0 kg/cow per day. Supplementary feeding of lactating cows led to a significantly higher mean daily milk yield compared to non-supplemented cows throughout the year (p<0.05). The mean annual milk offtake from supplemented cows (2195 kg/cow) was 18.6% more than offtake from non-supplemented cows, a difference that was statistically significant (p<0.05). Therefore, supplementary feeding of commercial feed concentrates was a rational management practice. It was also concluded that milk production from smallholder dairy cows in the coastal lowlands of Kenya was comparable to that from similar production systems but lower than national targets.

Effect of corn silage from an herbicide-tolerant genetically modified variety on milk production and absence of transgenic DNA in milk

Data from 60 multiparous Holstein cows were used in a 12-wk continuous design feeding trial. Cows were allocated to 1 of 4 experimental treatments (T1 to T4). In T1 and T2, the total mixed ration (TMR) contained either corn silage from the genetically modified (GM) variety Chardon Liberty Link, which is tolerant to the herbicide glufosinate ammonium, or its near isogenic nonGM counterpart, whereas the TMR used in T3 and T4 contained corn silage from the commercially available nonGM varieties Fabius and Antares, respectively. The objectives of the study were to determine if the inserted gene produced a marked effect on chemical composition, nutritive value, feed intake, and milk production, and to determine if transgenic DNA and the protein expressed by the inserted gene could be detected in bovine milk. The nutritive value, fermentation characteristics, mineral content, and amino acid composition of all 4 silages were similar. There were no significant treatment effects on milk yield, milk composition, and yield of milk constituents, and the dry matter (DM) intake of the GM variety was not significantly different from the 2 commercial varieties. However, although the DM intake noted for the nonGM near-isogenic variety was similar to the commercial varieties, it was significantly lower when compared with the GM variety. Polymerase chain reaction analyses of milk samples collected at wk 1, 6, and 12 of the study showed that none of the 90 milk samples tested positive, above a detection limit of 2.5 ng of total genomic DNA/mL of milk, for either tDNA (event T25) or the single-copy endogenous Zea mays gene, alcohol dehydrogenase. Using ELISA assays, the protein expressed by the T25 gene was not detected in milk.

Production and metabolic effects of site of starch digestion in lactating dairy cattle

Milk solids yield in modern dairy cows has increased linearly over the last 50 years, stressing the need for maximal dietary energy intake to allow genetic potential for milk energy yield to be realized with minimal negative effects on health and reproduction. Feeding supplemental starch is a common approach for increasing the energy density of the ration and supplying carbon for meeting the substantial glucose requirement of the higher yielding cow. In this regard, it is a long held belief that feeding starch in forms that increase digestion in the small intestine and glucose absorption will benefit the cow in terms of energetic efficiency and production response, but data supporting this dogma are equivocal. This review will consider the impact of supplemental starch and site of starch digestion on metabolic and production responses of lactating dairy cows, including effects on feed intake, milk yield and composition, nutrient partitioning, the capacity of the small intestine for starch digestion, and nutrient absorption and metabolism by the splanchnic tissues (the portal-drained viscera and liver). Whilst there appears to be considerable capacity for starch digestion and glucose absorption in the lactating dairy cow, numerous strategic studies implementing postruminal starch or glucose infusions have observed increases in milk yield, but decreased milk fat concentration such that there is little effect on milk energy yield, even in early lactation. Measurements of energy balance confirm that the majority of the supplemental energy arising from postruminal starch digestion is used with high efficiency to support body adipose and protein retention, even in early lactation. These responses may be mediated by changes in insulin status, and be beneficial to the cow in terms of reproductive success and well-being. However, shifting starch digestion from the rumen impacts the nitrogen economy of the cow as well by shifting the microbial protein gained from starch digestion from potentially absorbable protein to endogenous faecal loss.

Mixed Logit Model Performance and Distributional Assumptions: Preferences and GM foods

Using mixed logit models to analyse choice data is common but requires ex ante specification of the functional forms of preference distributions. We make the case for greater use of bounded functional forms and propose the use of the Marginal Likelihood, calculated using Bayesian techniques, as a single measure of model performance across non nested mixed logit specifications. Using this measure leads to very different rankings of model specifications compared to alternative rule of thumb measures. The approach is illustrated using data from a choice experiment regarding GM food types which provides insights regarding the recent WTO dispute between the EU and the US, Canada and Argentina and whether labelling and trade regimes should be based on the production process or product composition.

Inter-laboratory variation of in vitro cumulative gas production profiles of feeds using manual and automated methods

A study was conducted to estimate variation among laboratories and between manual and automated techniques of measuring pressure on the resulting gas production profiles (GPP). Eight feeds (molassed sugarbeet feed, grass silage, maize silage, soyabean hulls, maize gluten feed, whole crop wheat silage, wheat, glucose) were milled to pass a I mm screen and sent to three laboratories (ADAS Nutritional Sciences Research Unit, UK; Institute of Grassland and Environmental Research (IGER), UK; Wageningen University, The Netherlands). Each laboratory measured GPP over 144 h using standardised procedures with manual pressure transducers (MPT) and automated pressure systems (APS). The APS at ADAS used a pressure transducer and bottles in a shaking water bath, while the APS at Wageningen and IGER used a pressure sensor and bottles held in a stationary rack. Apparent dry matter degradability (ADDM) was estimated at the end of the incubation. GPP were fitted to a modified Michaelis-Menten model assuming a single phase of gas production, and GPP were described in terms of the asymptotic volume of gas produced (A), the time to half A (B), the time of maximum gas production rate (t(RM) (gas)) and maximum gas production rate (R-M (gas)). There were effects (P<0.001) of substrate on all parameters. However, MPT produced more (P<0.001) gas, but with longer (P<0.001) B and t(RM gas) (P<0.05) and lower (P<0.001) R-M gas compared to APS. There was no difference between apparatus in ADDM estimates. Interactions occurred between substrate and apparatus, substrate and laboratory, and laboratory and apparatus. However, when mean values for MPT were regressed from the individual laboratories, relationships were good (i.e., adjusted R-2 = 0.827 or higher). Good relationships were also observed with APS, although they were weaker than for MPT (i.e., adjusted R-2 = 0.723 or higher). The relationships between mean MPT and mean APS data were also good (i.e., adjusted R 2 = 0. 844 or higher). Data suggest that, although laboratory and method of measuring pressure are sources of variation in GPP estimation, it should be possible using appropriate mathematical models to standardise data among laboratories so that data from one laboratory could be extrapolated to others. This would allow development of a database of GPP data from many diverse feeds. (c) 2005 Published by Elsevier B.V.

Production risk, pesticide use and GM crop technology in South Africa

Technology involving genetic modification of crops has the potential to make a contribution to rural poverty reduction in many developing countries. Thus far, pesticide-producing Bacillus thuringensis (Bt) varieties of cotton have been the main GM crops under cultivation in developing nations. Several studies have evaluated the farm-level performance of Bt varieties in comparison to conventional ones by estimating production technology, and have mostly found Bt technology to be very successful in raising output and/or reducing pesticide input. However, the production risk properties of this technology have not been studied, although they are likely to be important to risk-averse smallholders. This study investigates the output risk aspects of Bt technology by estimating two 'flexible risk' production function models allowing technology to independently affect the mean and higher moments of output. The first is the popular Just-Pope model and the second is a more general 'damage control' flexible risk model. The models are applied to cross-sectional data on South African smallholders, some of whom used Bt varieties. The results show no evidence that a 'risk-reduction' claim can be made for Bt technology. Indeed, there is some evidence to support the notion that the technology increases output risk, implying that simple (expected) profit computations used in past evaluations may overstate true benefits.

Tropospheric ozone and winter wheat production in England and Wales: A note

Tropospheric ozone is an air pollutant thought to reduce crop yields across Europe. Much experimental scientific work has been completed or is currently underway to quantify yield effects at ambient ozone levels. In this research, we seek to directly evaluate whether such effects are observed at the farm level. This is done by intersecting a farm level panel dataset for winter wheat farms in England & Wales with information on ambient ozone, and estimating a production function with ozone as a fixed input. Panel data methods, Generalised Method of Moments (GMM) techniques and nested exogeneity tests are employed in the estimation. The results confirm a small, but nevertheless statistically significant negative effect of ambient ozone levels on wheat yields.

Comparing rice production systems: A challenge for agronomic research and for the dissemination of knowledge-intensive farming practices

This article is a commentary on several research studies conducted on the prospects for aerobic rice production systems that aim at reducing the demand for irrigation water which in certain major rice producing areas of the world is becoming increasingly scarce. The research studies considered, as reported in published articles mainly under the aegis of the International Rice Research Institute (IRRI), have a narrow scope in that they test only 3 or 4 rice varieties under different soil moisture treatments obtained with controlled irrigation, but with other agronomic factors of production held as constant. Consequently, these studies do not permit an assessment of the interactions among agronomic factors that will be of critical significance to the performance of any production system. Varying the production factor of "water" will seriously affect also the levels of the other factors required to optimise the performance of a production system. The major weakness in the studies analysed in this article originates from not taking account of the interactions between experimental and non-experimental factors involved in the comparisons between different production systems. This applies to the experimental field design used for the research studies as well as to the subsequent statistical analyses of the results. The existence of such interactions is a serious complicating element that makes meaningful comparisons between different crop production systems difficult. Consequently, the data and conclusions drawn from such research readily become biased towards proposing standardised solutions for possible introduction to farmers through a linear technology transfer process. Yet, the variability and diversity encountered in the real-world farming environment demand more flexible solutions and approaches in the dissemination of knowledge-intensive production practices through "experiential learning" types of processes, such as those employed by farmer field schools. This article illustrates, based on expertise of the 'system of rice intensification' (SRI), that several cost-effective and environment-friendly agronomic solutions to reduce the demand for irrigation water, other than the asserted need for the introduction of new cultivars, are feasible. Further, these agronomic Solutions can offer immediate benefits of reduced water requirements and increased net returns that Would be readily accessible to a wide range of rice producers, particularly the resource poor smallholders. (C) 2009 Elsevier B.V. All rights reserved.

A critical assessment of a desk study comparing crop production systems: The example of the 'system of rice intensification' versus 'best management practice'

When assessing hypotheses, the possibility and consequences of false-positive conclusions should be considered along with the avoidance of false-negative ones. A recent assessment of the system of rice intensification (SRI) by McDonald et al. [McDonald, A.J., Hobbs, P.R., Riha, S.J., 2006. Does the system of rice intensification outperform conventional best management? A synopsis of the empirical record. Field Crops Res. 96, 31-36] provides a good example where this was not done as it was preoccupied with avoiding false-positives only. It concluded, based on a desk study using secondary data assembled selectively from diverse sources and with a 95% level of confidence, that 'best management practices' (BMPs) on average produce 11% higher rice yields than SRI methods, and that, therefore, SRI has little to offer beyond what is already known by scientists.

A note on the accuracy of PAC-likelihood inference with microsatellite data

Stephens and Donnelly have introduced a simple yet powerful importance sampling scheme for computing the likelihood in population genetic models. Fundamental to the method is an approximation to the conditional probability of the allelic type of an additional gene, given those currently in the sample. As noted by Li and Stephens, the product of these conditional probabilities for a sequence of draws that gives the frequency of allelic types in a sample is an approximation to the likelihood, and can be used directly in inference. The aim of this note is to demonstrate the high level of accuracy of "product of approximate conditionals" (PAC) likelihood when used with microsatellite data. Results obtained on simulated microsatellite data show that this strategy leads to a negligible bias over a wide range of the scaled mutation parameter theta. Furthermore, the sampling variance of likelihood estimates as well as the computation time are lower than that obtained with importance sampling on the whole range of theta. It follows that this approach represents an efficient substitute to IS algorithms in computer intensive (e.g. MCMC) inference methods in population genetics. (c) 2006 Elsevier Inc. All rights reserved.

Allelic size standards and reference genotypes to unify international cocoa (Theobroma cacao L.) microsatellite data

Standardisation of microsatellite allele profiles between laboratories is of fundamental importance to the transferability of genetic fingerprint data and the identification of clonal individuals held at multiple sites. Here we describe two methods of standardisation applied to the microsatellite fingerprinting of 429 Theobroma cacao L. trees representing 345 accessions held in the worlds largest Cocoa Intermediate Quarantine facility: the use of a partial allelic ladder through the production of 46 cloned and sequenced allelic standards (AJ748464 to AJ48509), and the use of standard genotypes selected to display a diverse allelic range. Until now a lack of accurate and transferable identification information has impeded efforts to genetically improve the cocoa crop. To address this need, a global initiative to fingerprint all international cocoa germplasm collections using a common set of 15 microsatellite markers is in progress. Data reported here have been deposited with the International Cocoa Germplasm Database and form the basis of a searchable resource for clonal identification. To our knowledge, this is the first quarantine facility to be completely genotyped using microsatellite markers for the purpose of quality control and clonal identification. Implications of the results for retrospective tracking of labelling errors are briefly explored.