Alternative approaches to predicting methane emissions from dairy cows

Previous attempts to apply statistical models, which correlate nutrient intake with methane production, have been of limited. value where predictions are obtained for nutrient intakes and diet types outside those. used in model construction. Dynamic mechanistic models have proved more suitable for extrapolation, but they remain computationally expensive and are not applied easily in practical situations. The first objective of this research focused on employing conventional techniques to generate statistical models of methane production appropriate to United Kingdom dairy systems. The second objective was to evaluate these models and a model published previously using both United Kingdom and North American data sets. Thirdly, nonlinear models were considered as alternatives to the conventional linear regressions. The United Kingdom calorimetry data used to construct the linear models also were used to develop the three. nonlinear alternatives that were ball of modified Mitscherlich (monomolecular) form. Of the linear models tested,, an equation from the literature proved most reliable across the full range of evaluation data (root mean square prediction error = 21.3%). However, the Mitscherlich models demonstrated the greatest degree of adaptability across diet types and intake level. The most successful model for simulating the independent data was a modified Mitscherlich equation with the steepness parameter set to represent dietary starch-to-ADF ratio (root mean square prediction error = 20.6%). However, when such data were unavailable, simpler Mitscherlich forms relating dry matter or metabolizable energy intake to methane production remained better alternatives relative to their linear counterparts.

The effect of environment on endosperm cell-wall development in Triticum aestivum during grain filling: an infrared spectroscopic imaging study

One of the major factors contributing to the failure of new wheat varieties is seasonal variability in end-use quality. Consequently, it is important to produce varieties which are robust and stable over a range of environmental conditions. Recently developed sample preparation methods have allowed the application of FT-IR spectroscopic imaging methods to the analysis of wheat endosperm cell wall composition, allowing the spatial distribution of structural components to be determined without the limitations of conventional chemical analysis. The advantages of the methods, described in this paper, are that they determine the composition of endosperm cell walls in situ and with minimal modification during preparation. Two bread-making wheat cultivars, Spark and Rialto, were selected to determine the impact of environmental conditions on the cell-wall composition of the starchy endosperm of the developing and mature grain, focusing on the period of grain filling (starting at about 14 days after anthesis). Studies carried out over two successive seasons show that the structure of the arabinoxylans in the endosperm cell walls changes from a highly branched form to a less branched form. Furthermore, during development the rate of restructuring was faster when the plants were grown at higher temperature with restricted water availability from 14 days after anthesis with differences in the rate of restructuring occurring between the two cultivars.

Analysis of the calving pattern of herds in small-scale dairy systems in central Mexico

This study sets out to find the best calving pattern for small-scale dairy systems in Michoacan State, central Mexico. Two models were built. First, a linear programming model was constructed to optimize calving pattern and herd structure according to metabolizable energy availability. Second, a Markov chain model was built to investigate three reproductive scenarios (good, average and poor) in order to suggest factors that maintain the calving pattern given by the linear programming model. Though it was not possible to maintain the optimal linear programming pattern, the Markov chain model suggested adopting different reproduction strategies according to period of the year that the cow is expected to calve. Comparing different scenarios, the Markov model indicated the effect of calving interval on calving pattern and herd structure.

Analysis of feeding strategies for small-scale dairy systems in central Mexico using linear programming

A limitation of small-scale dairy systems in central Mexico is that traditional feeding strategies are less effective when nutrient availability varies through the year. In the present work, a linear programming (LP) model that maximizes income over feed cost was developed, and used to evaluate two strategies: the traditional one used by the small-scale dairy producers in Michoacan State, based on fresh lucerne, maize grain and maize straw; and an alternative strategy proposed by the LIP model, based on ryegrass hay, maize silage and maize grain. Biological and economic efficiency for both strategies were evaluated. Results obtained with the traditional strategy agree with previously published work. The alternative strategy did not improve upon the performance of the traditional strategy because of low metabolizable protein content of the maize silage considered by the model. However, the Study recommends improvement of forage quality to increase the efficiency of small-scale dairy systems, rather than looking for concentrate supplementation.

Forage production and nutrient availability in small-scale dairy systems in central Mexico using linear programming and partial budgeting

Small-scale dairy systems play an important role in the Mexican dairy sector and farm planning activities related to resource allocation have a significant impact on the profitability of such enterprises. Linear programming is a technique widely used for planning and ration formulation, and partial budgeting is a technique for assessing the impact of changes on the profitability of an enterprise. This study used both methods to optimise land use for forage production and nutrient availability, and to evaluate the economic impact of such changes in small-scale Mexican dairy systems. The model showed satisfactory performance when optimal solutions were compared with the traditional strategy. The strategy using fresh ryegrass, maize silage and oat hay, and the strategy using a combination of alfalfa hay, maize silage, fresh ryegrass and oat hay appeared attractive options for providing a better nutrient supply and maintaining a higher stocking rate throughout the year than the traditional strategy.

Transcriptome analysis of grain development in hexaploid wheat

Background: Hexaploid wheat is one of the most important cereal crops for human nutrition. Molecular understanding of the biology of the developing grain will assist the improvement of yield and quality traits for different environments. High quality transcriptomics is a powerful method to increase this understanding. Results: The transcriptome of developing caryopses from hexaploid wheat ( Triticum aestivum, cv. Hereward) was determined using Affymetrix wheat GeneChip (R) oligonucleotide arrays which have probes for 55,052 transcripts. Of these, 14,550 showed significant differential regulation in the period between 6 and 42 days after anthesis ( daa). Large changes in transcript abundance were observed which were categorised into distinct phases of differentiation ( 6 - 10 daa), grain fill ( 12 - 21 daa) and desiccation/maturation ( 28 - 42 daa) and were associated with specific tissues and processes. A similar experiment on developing caryopses grown with dry and/or hot environmental treatments was also analysed, using the profiles established in the first experiment to show that most environmental treatment effects on transcription were due to acceleration of development, but that a few transcripts were specifically affected. Transcript abundance profiles in both experiments for nine selected known and putative wheat transcription factors were independently confirmed by real time RT-PCR. These expression profiles confirm or extend our knowledge of the roles of the known transcription factors and suggest roles for the unknown ones. Conclusion: This transcriptome data will provide a valuable resource for molecular studies on wheat grain. It has been demonstrated how it can be used to distinguish general developmental shifts from specific effects of treatments on gene expression and to diagnose the probable tissue specificity and role of transcription factors.

A novel transcriptomic approach to identify candidate genes for grain quality traits in wheat

A novel methodology is described in which transcriptomics is combined with the measurement of bread-making quality and other agronomic traits for wheat genotypes grown in different environments (wet and cool or hot and dry conditions) to identify transcripts associated with these traits. Seven doubled haploid lines from the Spark x Rialto mapping population were selected to be matched for development and known alleles affecting quality. These were grown in polytunnels with different environments applied 14 days post-anthesis, and the whole experiment was repeated over 2 years. Transcriptomics using the wheat Affymetrix chip was carried out on whole caryopsis samples at two stages during grain filling. Transcript abundance was correlated with the traits for approximately 400 transcripts. About 30 of these were selected as being of most interest, and markers were derived from them and mapped using the population. Expression was identified as being under cis control for 11 of these and under trans control for 18. These transcripts are candidates for involvement in the biological processes which underlie genotypic variation in these traits.