Rainfall erosivity and erosivity density through rainfall synthetic series for São Paulo State,Brazil: Assessment,regionalization and modeling

Rainfall is the main cause of erosion of Brazilian soils, which makes assessing the rainfall erosivity factor (RE) and the erosivity density (ED) fundamental for soil and water conservation. Therefore, the objectives of this study were: i) to estimate the RE and ED for São Paulo State, Brazil, using synthetic series of pluviographic data; ii) to define homogeneous regions regarding rainfall erosivity; and iii) to generate regression models for rainfall erosivity estimates in each of the homogeneous regions. Synthetic series of pluviographic data were initially obtained on a sub-daily scale from the daily rainfall records of 696 rainfall gauges. The RE values were then estimated from the synthetic rainfall data, and ED was calculated from the relationship between erosivity and rainfall amounts. Monthly and annual maps for RE and ED were obtained. Hierarchical clustering analysis was used to define homogeneous regions in terms of rainfall erosivity, and regionalized regression models for estimating RE were generated. The results demonstrate high spatial variability of RE in São Paulo, where the highest annual values were observed in the coastal region. December to March concentrate approximately 60% of the intra-annual erosivity. The highest values of annual ED were observed in regions with intense agricultural activity. The definition of five homogeneous regions concerning the rainfall erosive potential evidenced distinct seasonal patterns of the spatial distribution of erosivity. Finally, the high predictive accuracy of the regionalized models obtained characterizes them as essential tools for reliable estimates of rainfall erosivity, and contribute to better soil conservation planning.     

A comparison of linear and exponential regression for estimating diffusive CH4 fluxes by closed-chambers in peatlands

The closed-chamber method is the most common approach to determine CH₄ fluxes in peatlands. The concentration change in the chamber is monitored over time, and the flux is usually calculated by the slope of a linear regression function. Theoretically, the gas exchange cannot be constant over time but has to decrease, when the concentration gradient between chamber headspace and soil air decreases. In this study, we test whether we can detect this non-linearity in the concentration change during the chamber closure with six air samples. We expect generally a low concentration gradient on dry sites (hummocks) and thus the occurrence of exponential concentration changes in the chamber due to a quick equilibrium of gas concentrations between peat and chamber headspace. On wet (flarks) and sedge-covered sites (lawns), we expect a high gradient and near-linear concentration changes in the chamber. To evaluate these model assumptions, we calculate both linear and exponential regressions for a test data set (n = 597) from a Finnish mire. We use the Akaike Information Criterion with small sample second order bias correction to select the best-fitted model. 13.6%, 19.2% and 9.8% of measurements on hummocks, lawns and flarks, respectively, were best fitted with an exponential regression model. A flux estimation derived from the slope of the exponential function at the beginning of the chamber closure can be significantly higher than using the slope of the linear regression function. Non-linear concentration-over-time curves occurred mostly during periods of changing water table. This could be due to either natural processes or chamber artefacts, e.g. initial pressure fluctuations during chamber deployment. To be able to exclude either natural processes or artefacts as cause of non-linearity, further information, e.g. CH₄ concentration profile measurements in the peat, would be needed. If this is not available, the range of uncertainty can be substantial. We suggest to use the range between the slopes of the exponential regression at the beginning and at the end of the closure time as an estimate of the overall uncertainty.     

Kernel vitreousness and protein content: Relationship,interaction and synergistic effects on durum wheat quality

Four sets of durum samples were used in this study to further understand the interrelationships among hard vitreous kernels (HVK), protein content, and pigment concentration, with a focus on the interaction and synergistic effects of protein content and vitreousness on durum quality. HVK level increases with higher protein content in the range of 9.5–12.5%, but this relationship is less evident in durum samples with high protein content (12.5–14.5%). Both protein content and kernel vitreousness can significantly affect durum milling quality. White starchy kernels (WSK) in low protein durum have a very detrimental impact on milling and pasta processing quality, but high protein content can mitigate the adverse impact of WSK on durum quality. Although protein content plays a dominant role, higher HVK might contribute positively to pasta firmness. There was no significant difference in yellow pigment content between HVK and WSK. However, pigment loss from semolina to dough was higher for WSK than HVK. Despite the difference in protein content, HVK and WSK have little difference in gluten strength. The monomeric protein was preferentially accumulated in HVK. The glutenin proteins of HVK and WSK were similar in the ratios of 1Bx/1By and HMW/LMW-GS.     

Soil aggregate formation and stability induced by starch and cellulose

Soil aggregate (SA) can be formed and stabilized when soil organic matter (SOM) is decomposed in the soil. However, the relationships between the SA dynamics and SOM with different decomposition rates have not been clarified. Therefore, this study examined the effects of the addition of polysaccharides to soil on SA formation and stability. A Japanese tropical soil was incubated for 99 d at 30 °C in a dark environment following the addition of 0.5% (w/w) starch or cellulose. The decomposition rates of the amendments, and SA formation and stability were evaluated by measuring soil respiration rates, and distribution fractions of soil aggregate sizes and mean weight diameter (MWD) of SA, respectively. The cumulative soil respirations with all treatments rapidly increased until Day 12 of the incubation. The initial slope of the cumulative soil respiration in the soil with starch was significantly higher than that in the soil with cellulose. In either soil with starch or cellulose, the fractions of macro-aggregates (>1000 μm in diameter) significantly increased, respectively, compared with control soil. However, the fractions of meso-aggregates (250–1000 μm) and nano-aggregate (<20 μm) in the soil with starch significantly decreased, while those fractions in the soil with cellulose fluctuated until Day 6. The MWDs reached the maximum on Day 6, indicating the SA formation in the soils with starch or cellulose. The increasing rate of the SA formation in the starch-amended soil was greatly higher than that in the cellulose-amended soil. After Day 6, the MWDs in the soils with either polysaccharide decreased with similar trends with no significant differences between treatments, indicating similar stability of the SA in both treatments. This study showed that the different decomposability of the organic amendments might influence the SA formation differently, but not the SA stability.     

Activity of polygalacturonases from Moniliophthora perniciosa depends on fungus culture conditions and is enhanced by Theobroma cacao extracts

We report the first analysis of polygalacturonase regulation in the basidiomycete Moniliophthora perniciosa. Non-secreted and secreted polygalacturonase activity was obtained from M. perniciosa cultivated on bran-based solid medium or liquid media containing additional carbon sources or cacao extracts (infected or not by the fungus). Polygalacturonase activity assays were carried out under different temperatures and incubation periods. The best secreted polygalacturonase activity was obtained when the enzymatic assay was made at 50 °C for 10 min. Moreover, the polygalacturonase activity was enhanced when the fungus was cultivated on potato dextrose medium, in the presence of additional fermentable carbon sources, in the presence of cacao pulp or non infected cacao extracts.     

A new lean no time test baking method with improved discriminating power

In response to customer concerns related to gluten strength in commercial baking, the Canadian Grain Commission assessed whether the Canadian Short Process (CSP) test bake method was generating useful data related to intrinsic strength of wheat varieties. Assessment of CSP loaf volume data for Canadian variety trials spanning 2003 to 2013 showed very little correlation with dough strength parameters as measured by farinograph and extensigraph. A lean no time (LNT) test baking method was developed that can better discriminate genotypes and provide objective indicators of the effect of intrinsic dough strength on baking quality. From early method development, through method validation and verification using diverse sets of samples targeting different Canadian wheat classes and grown in three different crop years, results showed the LNT method to be more discriminating and easily adopted by other laboratories. In 2015, the LNT method was adopted as the method of choice in future Canadian variety registration trials. The LNT method is fast, simple and well-suited to high throughput test baking conditions encountered in the evaluation of large numbers of breeder lines. A new objective parameter, loaf top ratio, was also introduced and found to correlate well with dough strength and dough handling properties.     

Breeding for increased grain protein and micronutrient content in wheat: Ten years of the GPC-B1 gene

To provide food and nutrition security for a growing world population, continued improvements in the yield and nutritional quality of agricultural crops will be required. Wheat is an important source of calories, protein and micronutrients and is thus a priority to breed for improvements in these traits. The GRAIN PROTEIN CONTENT-B1 (GPC-B1) gene is a positive regulator of nutrient translocation which increases protein, iron and zinc concentration in the wheat grain. In the ten years since it was cloned, the impacts of GPC-B1 allelic variation on quality and yield traits have been extensively analyzed in diverse genetic backgrounds in field studies spanning forty environments and seven countries. In this review, we compile data from twenty-five studies to summarize the impact of GPC-B1 allelic variation on fifty different traits. Taken together, the results demonstrate that the functional copy of the GPC-B1 gene is associated with consistent positive effects on grain protein, Fe and Zn content with only marginally negative impacts on yield. We conclude that the GPC-B1 gene has the potential to increase nutritional and end use quality in a wide range of modern cultivars and environments and discuss the possibilities for its application in wheat breeding.     

家禽诊疗文本多实体关系联合抽取模型研究

针对传统实体关系抽取方法中主体特征与句向量难以有效融合、现有BIO标注策略难以有效处理重叠关系的问题,提出一种基于BERT和双重指针标注的家禽疾病诊疗文本实体关系联合抽取模型(Joint extraction of entity relationship of poultry disease diagnosis and...     

农户经营性收入的影响因素分析

农民收入是农村经济发展的基础,也是农村经济发展的晴雨表。农业经营性收入是农民收入的重要部分。文章利用回归方法,分析调研数据,结果表明,生产要素持续投入和产业结构类型对经营性收入有显著的正向影响,而科技培训流于形式,对经营性收入有显著负向影响;区域位置和农户受教育程度对经营性收入无显著影响;新型产销衔接方式没有提高农户的议价能力,未表现出应有的增收效应。建议从加快土地流转、落实结构调整政策、加强科技创新与推广、创新产销衔接方式等方面,促进农户规模化经营水平,提高农业经营性收入。     

利用模糊数学方法预测秋白菜适宜收获期

依据秋白菜受冻的日最低气温指标,利用本溪市1957～2008年逐日最低气温资料,应用模糊数学隶属度函数预测日最低≤-7℃的初日趋势,建立多元回归模型预测日最低气温≤-7℃初日,为指导秋白菜适时收获、合理安排上期提供科学的气象依据。