农户过量施用化肥行为的影响因素分析——以新疆棉花种植户为例

过度施用化肥带来的负外部性使棉区土壤面临着棉花增产和保护生态环境的双重挑战。本文在棉花生产的决策主体农户尺度上,利用对新疆重点植棉地区实地问卷调查所得数据,定量化研究了新疆棉农过度施用化肥程度,并通过经济计量模型分析了导致农户过量施用化肥的主要因素。研究结果表明,新疆棉花种植农户的化肥施用量(折纯量)平均达到610.20 kg·hm~(-2),过量施用率占到实际施用量的59.6%。导致农户过量施用化肥的主要因素是缺乏科学施肥培训和避免收入损失的盲目性。研究结果在农户行为学方面做了有益的科学探讨,并为科学引导农户合理施肥提供了科学依据。     

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。     

Radiation interception and radiation use efficiency of potato affected by different N fertigation and irrigation regimes

Three years of field experiments were carried out to explore the response of potato dry matter production, accumulated intercepted photosynthetic active radiation (Aipar) and radiation use efficiency (RUE) to five N levels providing 0, 60, 100, 140 and 180 kg N ha⁻¹ and three drip irrigation strategies, which were full, deficit and none irrigation. Results showed that, irrespective of years, dry matter production and Aipar were increased by prolonged N fertigation, even though N fertigation was carried out from middle to late growing season. The highest total and tuber dry matter and accumulated radiation interception in all three years were obtained when potatoes were provided with 180 kg N ha⁻¹. RUE on the other hand was not affected by N regime. Thus, increases in total dry matter production with increasing N levels were essentially caused by higher Aipar. The strongest response to N fertilization occurred when most N was applied early in the growing season and the latest N fertilization should be applied no later than 41–50 days after emergence. Deficit irrigation, which received ca.70% of irrigation applied to full irrigation, did not reduce radiation interception and radiation use efficiency.     

Dense planting with less basal nitrogen fertilization might benefit rice cropping for high yield with less environmental impacts

Dense planting and less basal nitrogen (N) fertilization have been recommended to further increase rice (Oryza sativa L.) grain yield and N use efficiency (NUE), respectively. The objective of this study was to evaluate the integrative impacts of dense planting with reduced basal N application (DR) on rice yield, NUE and greenhouse gas (GHG) emissions. Field experiments with one conventional sparse planting (CK) and four treatments of dense planting (increased seedlings per hill) with less basal N application were conducted in northeast China from 2012 to 2013. In addition, a two-factor experiment was conducted to isolate the effect of planting density and basal N rate on CH₄ emission in 2013. Our results show that an increase in planting density by about 50% with a correspondingly reduction in basal N rate by about 30% (DR1 and DR2) enhanced NUE by 14.3–50.6% and rice grain yield by 0.5–7.4% over CK. Meanwhile, DR1 and DR2 reduced GWP by 6.4–12.6% and yield-scaled GWP by 7.0–17.0% over CK. According to the two-factor experiment, soil CH₄ production and oxidation and CH₄ emission were not affected by planting density. However, reduced basal N rate decreased CH₄ emission due to it significantly reduced soil CH₄ production with a smaller reduction in soil CH₄ oxidation. The above results indicate that moderate dense planting with less basal N application might be an environment friendly mode for rice cropping for high yield and NUE with less GHG emissions.     

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).     

In-field management of corn cob and residue mix: Effect on soil greenhouse gas emissions

In-field management practices of corn cob and residue mix (CRM) as a feedstock source for ethanol production can have potential effects on soil greenhouse gas (GHG) emissions. The objective of this study was to investigate the effects of CRM piles, storage in-field, and subsequent removal on soil CO₂ and N₂O emissions. The study was conducted in 2010–2012 at the Iowa State University, Agronomy Research Farm located near Ames, Iowa (42.0°′N; 93.8°′W). The soil type at the site is Canisteo silty clay loam (fine-loamy, mixed, superactive, calcareous, mesic Typic Endoaquolls). The treatments for CRM consisted of control (no CRM applied and no residue removed after harvest), early spring complete removal (CR) of CRM after application of 7.5 cm depth of CRM in the fall, 2.5 cm, and 7.5 cm depth of CRM over two tillage systems of no-till (NT) and conventional tillage (CT) and three N rates (0, 180, and 270 kg N ha⁻¹) of 32% liquid UAN (NH₄NO₃) in a randomized complete block design with split–split arrangements. The findings of the study suggest that soil CO₂ and N₂O emissions were affected by tillage, CRM treatments, and N rates. Most N₂O and CO₂ emissions peaks occurred as soil moisture or temperature increased with increase precipitation or air temperature. However, soil CO₂ emissions were increased as the CRM amount increased. On the other hand, soil N₂O emissions increased with high level of CRM as N rate increased. Also, it was observed that NT with 7.5 cm CRM produced higher CO₂ emissions in drought condition as compared to CT. Additionally, no differences in N₂O emissions were observed due to tillage system. In general, dry soil conditions caused a reduction in both CO₂ and N₂O emissions across all tillage, CRM treatments, and N rates.