土壤团聚体有机碳研究进展

土壤有机碳是衡量土壤肥力的重要指标,对于促进土壤养分循环、增加养分有效性有重要作用。土壤团聚体是土壤的重要组成部分,是组成土壤结构的最小单元,受到自然因素和人为因素的影响,其形成转化过程与土壤固碳过程息息相关,因而研究团聚体和有机碳的关系及团聚体有机碳影响因素对于土壤结构的改善和土壤质量的提升具有重要意义。本文通过对文献的总结,明晰了土壤团聚体和有机碳的关系,阐述了土壤类型、施肥方式、土地利用和矿区复垦对土壤团聚体有机碳的影响,并从生物质炭的长期定位研究和复垦矿区的土壤修复两方面对土壤团聚体有机碳的研究进行展望,研究结果可为合理的农业生产提供科学依据。     

小麦4B染色体上LOX基因的等位变异及其区域分布

为了解中国不同麦区小麦种质资源籽粒脂肪氧化酶（lipoxygenase,LOX）活性相关基因TaLox-B1的差异和分布,利用小麦4B染色体上的功能标记LOX16和LOX18对7个麦区的436份种质资源进行分子检测。结果表明：在供试材料中共检测到3种TaLox-B1基因等位变异类型,分别为TaLox-B1a（与高LOX活性相关)、TaLox-B1b（与低LOX活性相关）和杂合型,其频率分别为19.0％、70.4％和10.6％。小麦LOX活性基因不同变异类型在各生态区的分布存在明显差异：基因型TaLox-B1a在黄淮冬麦区、北部冬麦区和长江中下游冬麦区分布较多,其比例分别为21.1%、19.8%和17.6%;基因型TaLox-B1b在西南冬麦区和长江中下游冬麦区分布较多,比例分别为87.9%、72.5%;杂合型仅存在于北部冬麦区、黄淮冬麦区与长江中下游冬麦区,比例分别为14.2%、12.4%和9.8%。利用标记LOX16和LOX18对53个自选高代品系进行分子检测,发现自选品系仅有TaLox-B1b与杂合型两种基因型,其中基因型TaLox-B1ab有32个,比例为60.4%。采用分子标记辅助选择,有利于快速鉴定小麦籽粒LOX活性,加速LOX的遗传改良和新品种选育。     

不同施肥处理对马铃薯农田土壤理化性状及产量的影响

为了探究不同施肥处理对马铃薯农田土壤理化性状及产量的影响,试验地采用马铃薯连作模式,设置3个施肥处理,即：单施化肥(T)、有机肥配施化肥(YTF 1/2)、全量有机肥(YTF)。结果表明：在不同施肥处理下马铃薯农田土壤的理化性质和马铃薯产量发生了变化,其中变化最为明显的土壤指标有土壤容重、孔隙度、饱和导水率、有效磷。YTF处理较T处理可分别显著(P<0.05)降低土壤容重16.8%,增加土壤孔隙度12.7%,提升饱和导水率25.3%。YTF处理可显著提升土壤有效磷含量43.0%,但各处理间土壤pH、有机碳、全氮、全磷、碱解氮、速效钾之间差异并未达到显著水平。同时,较之T处理,YTF处理亦可显著提升土壤团聚体含量。YTF和YTF 1/2处理可分别较T处理提升马铃薯产量24.6%和12.8%。因此,施用有机肥不仅可以改善土壤结构,改良土壤物理性状,亦能促产增收。     

Prediction of baking results from farinograph measurements by using stepwise linear regression and artificial neuronal networks

In an effort to extract additional data from farinograph experiments a model was developed to simulate the measurements and correlate the parameters of the model with results from baking tests. This additional information can be used in bakeries to predict the baking properties of the flours and adjust the recipes to maintain a constant product quality. For this eight different flours were characterized with a farinograph and 13 different results from baking experiments. An approach with five nonlinear differential equations was able to model the farinograph measurements very well (average R² = 0.995 ± 0.005). While a stepwise multilinear regression only showed weak correlations in cross validation between a single parameter of the model and the baking volume (R² = 0.745) and the volume yield (R² = 0.796) respectively, the artificial neuronal network was more successful. For the baking weight (R² = 0.926), the dough yield gross (R² = 0.909) and net (R² = 0.913) strong correlations were found. A good correlation for the baking volume (R² = 0.853) was also determined, while the volume yield showed comparable results to the linear regression (R² = 0.792).     

Utilizing a DUALEM‐421 and inversion modelling to map baseline soil salinity along toposequences in the Hunter Valley Wine district

In the oldest commercial wine district of Australia, the Hunter Valley, there is the threat of soil salinization because marine sediments underlie the area. To understand the risk requires information about the spatial distribution of soil properties. Electromagnetic (EM) induction instruments have been used to identify and map the spatial variation of average soil salinity to a certain depth. However, soils vary with depth dependent on soil forming factors. We collected data from a single‐frequency and multiple‐coil DUALEM‐421 along a toposequence. We inverted this data using EM4Soil software and evaluated the resultant 2‐dimensional model of true electrical conductivity (σ – mS/m) with depth against electrical conductivity of saturated soil pastes (EC_p – dS/m). Using a fitted linear regression (LR) model calibration approach and by varying the forward model (cumulative function‐CF and full solution‐FS), inversion algorithm (S1 and S2), damping factor (λ) and number of arrays, we determined a suitable electromagnetic conductivity image (EMCI), which was optimal (R² = 0.82) when using the full solution, S2, λ = 3.6 and all six coil arrays. We conducted an uncertainty analysis of the LR model used to estimate the electrical conductivity of the saturated soil‐paste extract (EC_e – dS/m). Our interpretation based on estimates of EC_e suggests the approach can identify differences in salinity, how these vary with parent material and how topography influences salt distribution. The results provide information leading to insights into how soil forming factors and agricultural practices influence salinity down a toposequence and how this can guide soil management practices.     

Do cover crops change the lability of phosphorus in a clayey subtropical soil under different phosphate fertilizers?

Plants have developed different mechanisms to absorb and solubilize phosphorus (P) in the soil, especially in environments with low P availability. This study evaluated the effects of different winter cover crops on soil P availability in a clayey subtropical (Hapludox) soil receiving soluble P fertilizer and a rock phosphate applied to the summer crop, under no‐tillage. The experiment was carried out over 3 yrs (2009–2011) with five different cover crop species: common vetch, fodder radish, ryegrass, black oat, white clover and fallow as control. The soil was sampled after the third year of cover crop cultivation and analysed for inorganic and organic P forms according to the well‐established Hedley fractionation procedure. Phosphate fertilizers promoted accumulation of both labile and nonlabile P pools in soil in the near surface layer, especially under rock phosphate. Fertilizer applications were not able to change P fractions in deeper layers, emphasizing that the Brazilian clayey soils are a sink of P from fertilizer and its mobility is almost nil. Although the cover crops recycled a great amount of P in tissue, in a short‐term evaluation (3 yrs) they only changed the content of moderately labile P in soil, indicating that long‐term studies are needed for more conclusive results.     

Soil quality assessments in integrated crop–livestock–forest systems: A review

Integrated crop–livestock–forest is a promising strategy to improve soil quality. It comprises four different integrated farming systems: crop–livestock, crop–forest, forest–livestock and crop–livestock–forest. This work systematically reviewed studies about integrated crop–livestock–forest systems and soil quality. A total of 92 papers were retrieved from the Web of Science—Clarivate Analytics platform, and the following information was analysed: publication year, institution, region of the studied site, type of integrated system, soil type, tillage system, maximum soil depth and the soil quality indicators assessed. Most studies were published in the second half of the 2010s. Brazil is a prominent focus of research about soil quality and integrated crop–livestock–forest systems, with significant contribution from its central and southern regions. The Embrapa was the main publishing institution, present in over one‐third of the studies. Crop–livestock was the most common integrated system, Ferralsols was the most common soil group, and most of the studied soils were clayey. No tillage was the main tillage system. Most studies focused on the topsoil, assessing physical and/or chemical soil quality indicators. More emphasis on biological indicators of soil quality is required, as well as assessments integrating biological, physical and chemical indicators of soil quality. Future works should compare different integrated systems, including assessments deeper in the soil profile, especially in systems with the forest component, and also in sandy and silty soils. Soil quality indicators that have been rarely used should be further tested. Novel indicators should be added to better understand the promotion of soil quality by integrated crop–livestock–forest systems.     

橡胶园酸性、中性土壤交换性钙、镁测定方法研究

为了获得简单、易操作、准确度高的橡胶园酸性、中性土壤交换性钙、镁测定方法,本试验通过响应面优化试验,建立称样量、提取液体积、提取方式与交换性钙测定结果之间的数学模型。结果表明：在25℃条件下,以1 mol/L的乙酸铵为土壤浸提液,称样量为2 g、提取液体积175 mL、振荡36 min,为橡胶园酸性、中性土壤的最佳提取条件。将上述条件下得到的结果与标准方法条件下得到的结果相对比,两结果的相对误差在1.25~3.04之间,均属合理范围。利用标准样品对优化方法进行试验验证,结果与推荐值相符。改进后的方法分析成本低、操作简便、测定结果准确、稳定性好,可用于橡胶园酸性、中性土壤交换性钙、镁的测定。     

Genome-wide association mapping of phenolic acids in tetraploid wheats

Phenolic acids are major components of cell walls in wheat and have important implications on human health as antioxidants with anti-tumor activity. Our objectives were to identify phenolic acid genes in wheat by single nucleotide polymorphisms (SNPs) detected within the coding sequences of candidate genes, and to identify chromosomal regions associated with single phenolic acids and total soluble phenolic compounds. A set of candidate genes involved in the biosynthesis of hydroxycinnamic acid derivatives were identified by comparative genomics. SNPs found in the coding sequences of six genes (PAL1, PAL2, C4H, C3H, COMT1 and COMT2) were used to determine their chromosomal location and accurate map position on two reference consensus linkage maps. The genome-wide association study (GWAS), based on genotyping a tetraploid wheat collection with 81,587 gene-associated SNPs, detected 22 quantitative trait loci (QTL) distributed on almost all durum wheat chromosomes. Two QTL for p-coumaric acid were coincident with the phenylalanine ammonia-lyase (PAL2) and p-coumarate 3-hydroxylase (C3H) genes on chromosome arms 2AL and 1AL, respectively. The availability of candidate gene-based markers can allow elucidating the mechanism of phenolic acids accumulation in wheat kernels and exploiting the genetic variability of phenolic acids content for the nutritional improvement of wheat end-products.