土壤中根皮苷和根皮素对桃幼苗的影响

以一年生桃嫁接苗为试材,在盆栽条件下研究了苹果园土壤中特征酚酸类物质——根皮苷和根皮素对桃苗生物量、根系活力、根系保护性酶活性和MDA含量的影响。结果表明,根皮苷对桃幼苗的伤害显著,与对照相比,鲜质量、干质量分别降低了16.66%和21.58%,根系活力降低了33.04%,SOD、POD活性分别降低了40.80%和31.10%,MDA含量提高了116.34%。根皮素对桃苗的影响不大。高锰酸钾处理明显缓解了根皮苷对桃苗的伤害,苹果园土壤中的根皮苷含量降低了57.80%,提高了桃苗的生物量、根系活力和保护性酶活性,降低了MDA含量。综上,老龄苹果园土壤实测含量的根皮苷(0.343mg·kg~(-1))可降低桃苗的生物量,适量的高锰酸钾能缓解根皮苷的伤害作用。     

黄土坡面结皮对土壤水稳性团聚体的稳定性和可蚀性的影响

为了探析微地形下土壤受雨滴打击后产生的结皮类型及团聚体组成差异。通过人工模拟降雨,研究坡面不同位置的结皮土壤水稳性团聚体分布特征、稳定性以及土壤可蚀性的变化情况。结果表明：（1）土壤水稳性团聚体以大团聚体（粒径>0.25 mm）含量为指标,原状土、结构结皮、沉积结皮、过渡带结皮>0.25 mm粒级的水稳性团聚体分别占37.28%、43.58%、36.69%、40.34%;（2）以降雨历时5 min为例,原状土、结构结皮、沉积结皮、过渡带结皮的水稳性团聚体的破坏率分别为：51.49%、46.00%、62.76%、51.02%;（3）原状土、结构结皮、沉积结皮、过渡带结皮的水稳性团聚体的平均重量直径分别为：0.15、0.20、0.14、0.17 mm;（4）原状土、结构结皮、沉积结皮、过渡带结皮土壤可蚀性K值的大小分别为：0.223、0.200、0.229、0.205。微地形下产生结皮差异使得水稳性团聚体分布有所区别,因此土壤水稳性团聚体稳定性和可蚀性存在差异。     

林地水土保持功能持续提高的机制及对策

通过对不同林地水土保持功能分析得出,其发展过程可分为成长期、成熟期和减退期,并定义成熟期为可持续发展期。分析了影响水土保持功能持续提高的环境分配系数r和环境利用系数k,认为r是林地中光、水、肥分配的参数,k为光、水、肥利用的参数。林地水土保持功能的持续提高,应通过调整r和k,即调控林地的树种组成、林分层次和林分密度,形成合理的林分结构,保持成熟期的持续发展。并在此基础上提出了林地水土保持功能持续提高的相应对策。     

温度和湿度对土壤中噁唑酰草胺降解的影响

噁唑酰草胺是一种芳氧苯氧丙酸酯类除草剂,近年来在我国使用面积快速上升。本文建立了土壤中噁唑酰草胺的快速灵敏检测方法,测定了土壤温度和湿度对土壤中噁唑酰草胺降解的影响。研究结果表明建立的土壤中噁唑酰草胺的高效液相色谱检测方法,最低定量限(LOQ)为4.00×10~(-3)μg/kg,最低检测限LOD为1.20×10~(-3)μg/kg。土壤温度为5、15、25和35℃时,土壤中10 mg/kg的噁唑酰草胺半衰期分别为16.8、9.9、3.5和0.9 d;土壤湿度为40%和80%时,土壤中噁唑酰草胺的半衰期分别为3.6和4.3 d。与土壤湿度相比,土壤温度对土壤中噁唑酰草胺降解的影响更大。     

兴山县优质烟叶产区植烟土壤养分动态状况分析

2010年在兴山全县选取1 995个植烟土壤样品进行分析,并与2000年土壤测定结果进行对比,研究兴山县优质烟叶产区(烟区)植烟土壤养分动态变化情况。结果表明,全区土壤有机质含量有所上升,但呈现两级分化趋势,土壤中全氮和碱解氮含量下降,土壤中全磷处于中偏低状态,全烟区普遍缺硼;兴山县烟区应根据"持续控氮、适度增磷,全面补硼"的原则进行施肥调整。     

Optimum Soil Water Content for Chickpea Emergence in Heavy‐Textured Soils of North‐West Bangladesh

Sowing of chickpea in the heavy‐textured soils of north‐west Bangladesh with minimum tillage technology aims to increase the timely planting of large areas during a relatively short sowing window before soil water deficit limits germination and emergence. However, the seedbed conditions into which chickpea is sown need to be better quantified, so that limiting factors which affect germination and emergence can be identified. Two of the soil physical characteristics of importance are soil water and aeration. Growth cabinet studies have identified the fastest germination and emergence of chickpea on representative soils for this area at gravimetric water contents of 17–18 %, whilst soil water contents above and below this delayed germination and emergence. Emergence was recorded at soil water potentials between field capacity (?10 kPa) and wilting point (?1500 kPa). Emergence was possible at lower soil water potentials in the finer textured soil, whilst in coarser textured soil, emergence was still possible at higher soil water potentials.     

A review of visual soil evaluation techniques for soil structure

Soil structure forms a key component of soil quality, and its assessment by semi‐quantitative visual soil evaluation (VSE) techniques can help scientists, advisors and farmers make decisions regarding sampling and soil management. VSE techniques require inexpensive equipment and generate immediate results that correlate well with quantitative measurements of physical and biochemical properties, highlighting their potential utility. We reviewed published VSE techniques and found that soils of certain textures present problems and a lack of research into the influence of soil moisture content on VSE criteria. Generally, profile methods evaluate process interactions at specific locations within a field, exploring both intrinsic aspects and anthropogenic impacts. Spade methods focus on anthropogenic characteristics, providing rapid synopses of soil structure over wider areas. Despite a focus on structural form, some methods include criteria related to stability and resiliency. Further work is needed to improve existing methods regarding texture influences, on‐farm sampling procedures and more holistic assessments of soil structure.     

Short‐term releases of CO2 from newly mixed biochar and calcareous soil

The work aimed to quantify native organic C mobilized in one calcareous soil in the 21 days after addition of biochar at a range of large to very large applications. The experiment was carried out in unplanted microcosms, and CO₂ flux was used as a measure of net mineralization. A rapid methodological approach, which does not require ¹³C as a tracer, was used to assess any priming effects induced by the biochar. The amount of CO₂‐C mobilized was small relative to the amount of biochar C and proportional to the amount of the biochar added. The additional CO₂‐C was similar to the content of the water‐soluble organic carbon in the biochar added with each application. No interaction with native soil C, that is priming effect, was observed.     

Enhancing pedotransfer functions with environmental data for estimating bulk density and effective cation exchange capacity in a data‐sparse situation

Soil bulk density (BD) and effective cation exchange capacity (ECEC) are among the most important soil properties required for crop growth and environmental management. This study aimed to explore the combination of soil and environmental data in developing pedotransfer functions (PTFs) for BD and ECEC. Multiple linear regression (MLR) and random forest model (RFM) were employed in developing PTFs using three different data sets: soil data (PTF‐1), environmental data (PTF‐2) and the combination of soil and environmental data (PTF‐3). In developing the PTFs, three depth increments were also considered: all depth, topsoil (<0.40 m) and subsoil (>0.40 m). Results showed that PTF‐3 (R²; 0.29–0.69) outperformed both PTF‐1 (R²; 0.11–0.18) and PTF‐2 (R²; 0.22–0.59) in BD estimation. However, for ECEC estimation, PTF‐3 (R²; 0.61–0.86) performed comparably as PTF‐1 (R²; 0.58–0.76) with both PTFs out‐performing PTF‐2 (R²; 0.30–0.71). Also, grouping of data into different soil depth increments improves the estimation of BD with PTFs (especially PTF‐2 and PTF‐3) performing better at subsoils than topsoils. Generally, the most important predictors of BD are sand, silt, elevation, rainfall, temperature for estimation at topsoil while EVI, elevation, temperature and clay are the most important BD predictors in the subsoil. Also, clay, sand, pH, rainfall and SOC are the most important predictors of ECEC in the topsoil while pH, sand, clay, temperature and rainfall are the most important predictors of ECEC in the subsoil. Findings are important for overcoming the challenges of building national soil databases for large‐scale modelling in most data‐sparse countries, especially in the sub‐Saharan Africa (SSA).