4 resultados para unity

em eResearch Archive - Queensland Department of Agriculture


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Thirty-seven surface (0-0.10 or 0-0.20 m) soils covering a wide range of soil types (16 Vertosols, 6 Ferrosols, 6 Dermosols, 4 Hydrosols, 2 Kandosols, 1 Sodosol, 1 Rudosol, and 1 Chromosol) were exhaustively cropped in 2 glasshouse experiments. The test species were Panicum maximum cv. Green Panic in Experiment A and Avena sativa cv. Barcoo in Experiment B. Successive forage harvests were taken until the plants could no longer grow in most soils because of severe potassium (K) deficiency. Soil samples were taken prior to cropping and after the final harvest in both experiments, and also after the initial harvest in Experiment B. Samples were analysed for solution K, exchangeable K (Exch K), tetraphenyl borate extractable K for extraction periods of 15 min (TBK15) and 60 min (TBK60), and boiling nitric acid extractable K (Nitric K). Inter-correlations between the initial levels of the various soil K parameters indicated that the following pools were in sequential equilibrium: solution K, Exch K, fast release fixed K [estimated as (TBK15-Exch K)], and slow release fixed K [estimated as (TBK60-TBK15)]. Structural K [estimated as (Nitric K-TBK60)] was not correlated with any of the other pools. However, following exhaustive drawdown of soil K by cropping, structural K became correlated with solution K, suggesting dissolution of K minerals when solution K was low. The change in the various K pools following cropping was correlated with K uptake at Harvest 1 ( Experiment B only) and cumulative K uptake ( both experiments). The change in Exch K for 30 soils was linearly related to cumulative K uptake (r = 0.98), although on average, K uptake was 35% higher than the change in Exch K. For the remaining 7 soils, K uptake considerably exceeded the change in Exch K. However, the changes in TBK15 and TBK60 were both highly linearly correlated with K uptake across all soils (r = 0.95 and 0.98, respectively). The slopes of the regression lines were not significantly different from unity, and the y-axis intercepts were very small. These results indicate that the plant is removing K from the TBK pool. Although the change in Exch K did not consistently equate with K uptake across all soils, initial Exch K was highly correlated with K uptake (r = 0.99) if one Vertosol was omitted. Exchangeable K is therefore a satisfactory diagnostic indicator of soil K status for the current crop. However, the change in Exch K following K uptake is soil-dependent, and many soils with large amounts of TBK relative to Exch K were able to buffer changes in Exch K. These soils tended to be Vertosols occurring on floodplains. In contrast, 5 soils (a Dermosol, a Rudosol, a Kandosol, and 2 Hydrosols) with large amounts of TBK did not buffer decreases in Exch K caused by K uptake, indicating that the TBK pool in these soils was unavailable to plants under the conditions of these experiments. It is likely that K fertiliser recommendations will need to take account of whether the soil has TBK reserves, and the availability of these reserves, when deciding rates required to raise exchangeable K status to adequate levels.

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The genetics of heifer performance in tropical 'wet' and 'dry' seasons, and relationships with steer performance, were studied in Brahman (BRAH) and Tropical Composite (TCOMP) (50% Bos indicus, African Sanga or other tropically adapted Bos taurus; 50% non-tropically adapted Bos taurus) cattle of northern Australia. Data were from 2159 heifers (1027 BRAH, 1132 TCOMP), representing 54 BRAH and 51 TCOMP sires. Heifers were assessed after post-weaning 'wet' (ENDWET) and 'dry' (ENDDRY) seasons. Steers were assessed post-weaning, at feedlot entry, over a 70-day feed test, and after similar to 120-day finishing. Measures studied in both heifers and steers were liveweight (LWT), scanned rump fat, rib fat and M. longissimus area (SEMA), body condition score (CS), hip height (HH), serum insulin-like growth factor-I concentration (IGF-I), and average daily gains (ADG). Additional steer measures were scanned intra-muscular fat%, flight time, and daily (DFI) and residual feed intake (RFI). Uni- and bivariate analyses were conducted for combined genotypes and for individual genotypes. Genotype means were predicted for a subset of data involving 34 BRAH and 26 TCOMP sires. A meta-analysis of genetic correlation estimates examined how these were related to the difference between measurement environments for specific traits. There were genotype differences at the level of means, variances and genetic correlations. BRAH heifers were significantly (P < 0.05) faster-growing in the 'wet' season, slower-growing in the 'dry' season, lighter at ENDDRY, and taller and fatter with greater CS and IGF-I at both ENDWET and ENDDRY. Heritabilities were generally in the 20 to 60% range for both genotypes. Phenotypic and genetic variances, and genetic correlations, were commonly lower for BRAH. Differences were often explained by the long period of tropical adaptation of B. indicus. Genetic correlations were high between corresponding measures at ENDWET and ENDDRY, positive between fat and muscle measures in TCOMP but negative in BRAH (mean of 13 estimates 0.50 and -0.19, respectively), and approximately zero between steer feedlot ADG and heifer ADG in BRAH. Numerous genetic correlations between heifers and steers differed substantially from unity, especially in BRAH, suggesting there may be scope to select differently in the sexes where that would aid the differing roles of heifers and steers in production. Genetic correlations declined as measurement environments became more different, the rates of decline (environment sensitivity) sometimes differing with genotype. Similar measures (LWT, HH and ADG; IGF-I at ENDWET in TCOMP) were genetically correlated with steer DFI in heifers as in steers. Heifer SEMA was genetically correlated with steer feedlot RFI in BRAH (0.75 +/- 0.27 at ENDWET, 0.66 +/- 0.24 at ENDDRY). Selection to reduce steer RFI would reduce SEMA in BRAH heifers but otherwise have only small effects on heifers before their first joining.

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1. Many organisms inhabit strongly fluctuating environments but their demography and population dynamics are often analysed using deterministic models and elasticity analysis, where elasticity is defined as the proportional change in population growth rate caused by a proportional change in a vital rate. Deterministic analyses may not necessarily be informative because large variation in a vital rate with a small deterministic elasticity may affect the population growth rate more than a small change in a less variable vital rate having high deterministic elasticity. 2. We analyse a stochastic environment model of the red kangaroo (Macropus rufus), a species inhabiting an environment characterized by unpredictable and highly variable rainfall, and calculate the elasticity of the stochastic growth rate with respect to the mean and variability in vital rates. 3. Juvenile survival is the most variable vital rate but a proportional change in the mean adult survival rate has a much stronger effect on the stochastic growth rate. 4. Even if changes in average rainfall have a larger impact on population growth rate, increased variability in rainfall may still be important also in long-lived species. The elasticity with respect to the standard deviation of rainfall is comparable to the mean elasticities of all vital rates but the survival in age class 3 because increased variation in rainfall affects both the mean and variability of vital rates. 5. Red kangaroos are harvested and, under the current rainfall pattern, an annual harvest fraction of c. 20% would yield a stochastic growth rate about unity. However, if average rainfall drops by more than c. 10%, any level of harvesting may be unsustainable, emphasizing the need for integrating climate change predictions in population management and increase our understanding of how environmental stochasticity translates into population growth rate.

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Significant genotypic differences in tolerance of pollen germination and seed set to high temperatures have been shown in sorghum. However, it is unclear whether differences were associated with variation in either the threshold temperature above which reproductive processes are affected, or in the tolerance to increased temperature above that threshold. The objectives of this study were to (a) dissect known differences in heat tolerance for a range of sorghum genotypes into differences in the threshold temperature and tolerance to increased temperatures, (b) determine whether poor seed set under high temperatures can be compensated by increased seed mass, and (c) identify whether genotypic differences in heat tolerance in a controlled environment facility (CEF) can be reproduced in field conditions. Twenty genotypes were grown in a CEF under four day/night temperatures (31.9/21.0 °C, 32.8/21.0 °C, 36.1/21.0 °C, and 38.0/21.0 °C), and a subset of six genotypes was grown in the field under four different temperature regimes around anthesis. The novelty of the findings in this study related to differences in responsiveness to high temperature—genotypic differences in seed set percentage were found for both the threshold temperature and the tolerance to increased maximum temperature above that threshold. Further, the response of seed set to high temperature in the field study was well correlated to that in the CEF (R2 = 0.69), although the slope was significantly less than unity, indicating that heat stress effects may have been diluted under the variable field conditions. Poor seed set was not compensated by increased seed mass in either CEF or field environments. Grain yield was thus closely related to seed set percentage. This result demonstrates the potential for development of a low-cost field screening method to identify high-temperature tolerant varieties that could deliver sustainable yields under future warmer climates.