Establishing a soybean germplasm core collection

Core collections are of strategic importance as they allow the use of a small part of a germplasm collection that is representative of the total collection. The objective of this study was to develop a soybean core collection of the USDA Soybean Germplasm Collection by comparing the results of random, proportional, logarithmic, multivariate proportional and multivariate logarithmic sampling strategies. All but the random sampling strategy used stratification of the entire collection based on passport data and maturity group classification. The multivariate proportional and multivariate logarithmic strategies made further use of qualitative and quantitative trait data to select diverse accessions within each stratum. The 18 quantitative trait data distribution parameters were calculated for each core and for the entire collection for pairwise comparison to validate the sampling strategies. All strategies were adequate for assembling a core collection. The random core collection best represented the entire collection in statistical terms. Proportional and logarithmic strategies did not maximize statistical representation but were better in selecting maximum variability. Multivariate proportional and multivariate logarithmic strategies produced the best core collections as measured by maximum variability conservation. The soybean core collection was established using the multivariate proportional selection strategy. (C) 2010 Elsevier B.V. All rights reserved.

Adapting the CROPGRO perennial forage model to predict growth of Brachiaria brizantha

Warm-season grasses are economically important for cattle production in tropical regions, and tools to aid in management and research of these forages would be highly beneficial. Crop simulation models synthesize numerous physiological processes and are important research tools for evaluating production of warm-season grasses. This research was conducted to adapt the perennial CROPGRO Forage model to simulate growth of the tropical species palisadegrass [Brachiaria brizantha (A. Rich.) Stapf. cv. Xaraes] and to describe model adaptation for this species. In order to develop the CROPGRO parameters for this species, we began with values and relationships reported in the literature. Some parameters and relationships were calibrated by comparison with observed growth, development, dry matter accumulation and partitioning during a 2-year experiment with Xaraes palisadegrass in Piracicaba, SP, Brazil. Starting with parameters for the bahiagrass (Paspalum notatum Flugge) perennial forage model, dormancy effects had to be minimized, and partitioning to storage tissue/root decreased, and partitioning to leaf and stem increased to provide for more leaf and stem growth and less root. Parameters affecting specific leaf area (SLA) and senescence of plant tissues were improved. After these changes were made to the model, biomass accumulation was better simulated, mean predicted herbage yield per cycle was 3573 kg ha(-1), with a RMSE of 538 kg DM ha(-1) (D-Stat = 0.838, simulated/observed ratio = 1.028). The results of the adaptation suggest that the CROPGRO model is an efficient tool to integrate physiological aspects of palisadegrass and can be used to simulate growth. (C) 2010 Elsevier B.V. All rights reserved.

How to unravel and solve soil fertility problems

This book provides a way for farmers in developing countries to benefit from scientific knowledge on plant nutrition and soil fertility. Specifically, it will help farmers recognise and deal with shortages or excesses of chemical elements.

Temperature and sowing date affect the linear increase of sunflower harvest index

The linearity of daily linear harvest index (HI) increase can provide a simple means to predict grain growth and yield in field crops. However, the stability of the rate of increase across genotypes and environments is uncertain. Data from three field experiments were collated to investigate the phase of linear HI increase of sunflower (Helianthus annuus L,) across environments by changing genotypes, sowing time, N level, and solar irradiation level. Linear increase in HI was similar among different genotypes, N levels, and radiation treatments (mean 0.0125 d(-1)). but significant differences occurred between sowings, The linear increase in HI was not stable at very low temperatures (down to 9 degrees C) during grain filling, due to possible limitations to biomass accumulation and translocation (mean 0.0091 d(-1)). Using the linear increase in HI to predict grain yield requires predictions of the duration from anthesis to the onset of linear HI increase (lag phase) and the cessation of linear RT increase. These studies showed that the lag phase differed, and the linear HI increase ceased when 91% of the anthesis to physiological maturity period had been completed.

Engineered detoxification confers resistance against a pathogenic bacterium

We generated transgenic sugarcane plants that express an albicidin detoxifying gene (albD), which was cloned from a bacterium that provides biocontrol against leaf scald disease. Plants with albicidin detoxification capacity equivalent to 1-10 ng of AlbD enzyme per mg of leaf protein did not develop chlorotic disease symptoms in inoculated leaves, whereas all untransformed control plants developed severe symptoms. Transgenic lines with high AlbD activity in young stems were also protected against systemic multiplication of the pathogen, which is the precursor to economic disease. We have shown that genetic modification to express a toxin-resistance gene can confer resistance to both disease symptoms and multiplication of a toxigenic pathogen in its host.

Slaking, dispersion, and crust formation

Soil structure is generally defined as the arrangement, orientation, and organization of the primary particles of sand, silt, and clay into compound aggregates, which exhibit properties that are unequal to the properties of a mass of nonaggregated material with a similar texture.6 Therefore the nature of soil structure is that it conveys specific properties to the soil and any alteration, i.e., breakdown or structural development, to the soil structural units will affect the physical properties of the soil. The aggregation and organization of the soil particles tend to form a hierarchical order4, 5 where the lower orders tend to have higher densities and greater internal strength than the higher orders. A schematic diagram of the hierarchical nature of soil structural elements in a clay soil is given in Fig. 1.4 Clay particles tend to form domains (packets of parallel clay sheets, generally consisting of 5-7 sheets), in turn several domains form clusters, followed by several orders of clusters, micro- and macroaggregates. The hierarchical nature implies that the destruction of a lower order will result in the destruction of all higher hierarchical orders. An example is the dispersion of sodic clay domains which results in the destruction of all higher orders, resulting in a dense soil with low hydraulic conductivity. Hence the clay domains are the fundamental building blocks of the soil and its integrity may determine the soil's physical properties and behavior.