3 resultados para Green energy sources

em eResearch Archive - Queensland Department of Agriculture


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Response curves were established for different supplements, offered at intakes ranging from 0 to 20 g/kg liveweight (W).day to young Bos indicus crossbred steers fed low-quality Rhodes grass (Chloris gayana) hay ad libitum in two pen experiments. Supplements included protein meals of varying rumen-degradability (cottonseed meal (CSM) or fishmeal), as well as ‘energy sources’ comprising grains of high and low ruminal starch degradability (barley and sorghum) and a highly fermentable sugar source (molasses), with all diets adjusted for rumen-degradable nitrogen and mineral content. Unsupplemented steers gained 0.08 and 0.15 kg/day, in Experiments 1 and 2, respectively. Growth of steers increased linearly with intake of ‘energy source’ supplements in increasing order of molasses, sorghum and barley (all differences P < 0.05). Steer growth rate also increased linearly with fishmeal, albeit over a narrow intake range (0–4.1 g/kg W.day), whereas the response with CSM was asymptotic, showing a steep response at low intake before levelling at ~1.2 kg/day. All supplement types were associated with a linear reduction in hay intake by the steers (energy substitution) where the reduction was greater (P < 0.05) for barley and molasses (not different) than for sorghum (P < 0.05), and for fishmeal compared with CSM (P < 0.05). In concurrent metabolism studies with the same rations, organic matter digestibility of the total ration (561–578 g/kg DM, unsupplemented) was increased linearly by barley and molasses (both P < 0.05) but was unaffected by CSM and sorghum supplements. The efficiency of microbial protein synthesis in steers increased linearly, from 91 g microbial crude protein/kg digestible organic matter (unsupplemented), in both molasses and CSM-supplemented steers, with the trend for a higher response to molasses (P = 0.05), and appeared most closely related to digestible organic matter intake. The response curves from these studies provide the practical framework upon which to formulate rations for cattle grazing low-quality forages.

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The genetic variability of 28 sorghum genotypes of known senescence phenotype was investigated using 66 SSR markers well-distributed across the sorghum genome. The genotypes of a number of lines from breeding programmes for stay-green were also determined. This included lines selected phenotypically for stay-green and also RSG 03123, a marker-assisted backcross progeny of R16 (recurrent parent) and B35 (stay-green donor). A total of 419 alleles were detected with a mean of 6.2 per locus. The number of alleles ranged from one for Xtxp94 to 14 for Xtxp88. Chromosome SBI-10 had the highest mean number of alleles (8.33), while SBI-05 had the lowest (4.17). The PIC values obtained ranged from zero to 0.89 in Xtxp94 and Xtxp88, respectively, with a mean of 0.68. On a chromosome basis, mean PIC values were highest in SBI-10 (0.81) and lowest in SBI-05 (0.53). Most of the alleles from B35 in RSG 03123 were found on chromosomes SBI-01, SBI-02 and SBI-03, confirming the successful introgression of quantitative trait loci associated with stay-green from B35 into the senescent background R16. However, the alternative stay-green genetic sources were found to be distinct based on either all the SSRs employed or using only those associated with the stay-green trait in B35. Therefore, the physiological and biochemical basis of each stay-green source should be evaluated in order to enhance the understanding of the functioning of the trait in the various backgrounds. These genetic sources of stay-green could provide a valuable resource for improving this trait in sorghum breeding programmes.

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The recent summary report of a Department of Energy Workshop on Plant Systems Biology (P.V. Minorsky [2003] Plant Physiol 132: 404-409) offered a welcomed advocacy for systems analysis as essential in understanding plant development, growth, and production. The goal of the Workshop was to consider methods for relating the results of molecular research to real-world challenges in plant production for increased food supplies, alternative energy sources, and environmental improvement. The rather surprising feature of this report, however, was that the Workshop largely overlooked the rich history of plant systems analysis extending over nearly 40 years (Sinclair and Seligman, 1996) that has considered exactly those challenges targeted by the Workshop. Past systems research has explored and incorporated biochemical and physiological knowledge into plant simulation models from a number of perspectives. The research has resulted in considerable understanding and insight about how to simulate plant systems and the relative contribution of various factors in influencing plant production. These past activities have contributed directly to research focused on solving the problems of increasing biomass production and crop yields. These modeling approaches are also now providing an avenue to enhance integration of molecular genetic technologies in plant improvement (Hammer et al., 2002).