农户绿色生产技术采纳行为及其效应——以测土配方施肥技术为例

为揭示农户绿色生产技术采纳行为决策的规律性和显化其行为效应,基于鄱阳湖平原6个产粮大县的607份调查数据,利用内生转换回归（ESR）模型实证分析了农户采纳测土配方施肥技术的影响因素及其采纳行为的经济和生态效应。结果表明：农户采纳测土配方施肥技术主要受到家庭总收入、耕种面积和信息获取渠道的正向影响,耕地破碎度和家离农技机构距离的负向影响。测土配方施肥技术的采纳有助于农户实现水稻的增产和化肥的减量化施用,表现为在反事实假设情景下,实际采纳该技术的农户若未采纳,其水稻单位面积产值下降6.38%、化肥施用量增加2.14%;实际未采纳该技术的农户若采纳,其水稻单位面积产值提高1.83%、化肥施用量减少1.00%。鉴于此,建议降低耕地破碎度,实现适度规模经营,加强技术的宣传推广,构建技术培训体系,显化技术效益,发挥技术的示范带动效果。     

狂犬病毒中和抗体检测试验中病毒回归试验的重要性

狂犬病毒中和试验的病毒回归试验表明,病毒攻毒液的实际剂量与理论剂量不完全一致.建议在新版<中华人民共和国兽用生物制品质量标准>中增加对病毒攻毒实际剂量范围的规定,以使结果的判定更为合理.     

农户种草意愿及其影响因素的实证分析

为寻求促进扩大栽培牧草种植面积的有效途径,本研究对西藏拉萨、日喀则和山南地区的797个农户的种草意愿情况进行调查,并采用Logistic回归分析对影响该地区农户种草意愿的因素进行分析。结果表明,农户的受教育年限、家庭总收入、耕地总面积、牲畜头数、牧草种子来源受到政府或项目支持及农户参加牲畜合作社对农户种草意愿具有积极的影响,而家庭劳动力人数对种草意愿具有负向影响。其中,户主年龄、家庭人口数和户主是否有村干部或科技特派员经历3个因素对种草意愿无显著影响。基于以上研究结果,本研究提出了加快普及种草养畜相关知识、研发适宜农区种草相关技术和加强牧草种植补贴额度的对策。     

油茶耐低磷指标鉴定及芽苗砧筛选

目的 本研究旨在探讨不同油茶半同胞子代实生苗的耐低磷能力,筛选耐低磷性强的砧木以及可用来鉴定油茶耐低磷性的关键指标,为油茶良种繁育以及耐低磷的机制研究奠定基础。 方法 以12个品种油茶的半同胞实生苗为研究对象,进行盆苗试验,设定正常磷1 mmol·L−1 KH2PO4、低磷0 mmol·L−1 KH2PO4 2个浓度,测定生物量、叶形态、根系形态、全磷等14个指标,以耐低磷系数为衡量油茶耐低磷的依据,建立逐步回归模型判别耐低磷关键指标。 结果 低磷胁迫减少了大部分油茶地上部分和根系的生物量积累,增加了根冠比和总磷利用效率。主成分分析将14个指标转化为4个独立的综合指标,累计贡献率达90.398%。依据综合评价值（D）,12个品种油茶半同胞子代聚类为3种类型,其中,GF20、CL3、84-3为相对不耐低磷类型;W1、CL53、GX48为中间型;G8、CL4、W2、CL40、CL18、83-4为相对耐低磷类型。PA（总磷积累量）、SPC（地上全磷）、TRA（总根表面积）、LW（叶宽）、RPC（根全磷）指标的回归模型为：D = −0.960 + 0.666PA + 0.341SPC + 0.379TRA + 0.460LW + 0.197RPC。 结论 低磷胁迫或许会抑制油茶的生长,但普遍增加根冠比和总磷利用效率。长林18、长林40、赣8、长林4、赣无2、赣石83-4相对耐低磷。总磷积累量、地上全磷、总根表面积、叶宽、根全磷可作为油茶耐低磷性的判断指标。     

基于贝叶斯模型平均法构建杉木林分蓄积量生长模型

目的 探究杉木林分蓄积量变化的影响因素,为在气候变化背景下科学经营管理杉木人工林提供理论支撑。 方法 以福建邵武卫闽林场的杉木（Cunninghamia lanceolata）人工密度试验林为研究对象,分别利用贝叶斯模型平均法（BMA）和逐步回归法（SR）构建杉木林分蓄积量与林分变量因子（包括初植密度、每公顷胸高断面积、每公顷株数、平方平均胸径、林分优势高、年龄）和气候因子（包括年均气温、最热月平均温度、最冷月平均温度、年均降水量、年均湿热指数、低于0℃天数、夏季平均最高温度、冬季平均最低温度、春季平均气温）的关系模型。 结果 杉木林分蓄积量随着每公顷胸高断面积、平方平均胸径、林分优势高、年龄、夏季平均最高温、春季平均温和低于0℃天数的增加而增加,对于诸多的影响因子,SR法所确定的模型并不在BMA选出的后验概率较高的前5个模型中,模型表现出一定的不确定性,从模型后验概率角度看,SR模型精度较低。 结论 杉木林分蓄积量受到林分变量因子和气候因子的显著影响。相比于SR法,在构建杉木林分蓄积量模型方面,BMA方法考虑了模型的不确定性,模型表现更好。     

基于广义混合效应模型的云冷杉林天然更新计数方法研究

天然更新是森林恢复较好的办法,对未来林分结构和生物多样性具有深远的影响。更新模型能够模拟天然更新的现实和未来状况,为森林经营者提供准确的森林计划。以吉林省汪清林业局2013年设置的12块云冷杉针阔混交林为例,选择泊松和负二项分布形式,考虑样地间的随机效应,构建基于林分因子的云冷杉针阔混交林天然更新模型。结果表明：各个树种对林分因子的反应不一,白桦更新株数与林分每公顷株数和平均直径均呈负相关;红松和水曲柳更新株数不受各个林分因子的影响,更新株数是随机的;冷杉更新株数与林分每公顷断面积呈负相关;色木槭和云杉更新株数均与林分平均直径呈负相关。在考虑样地的随机截距效应后,模型的模拟效果显著提高。在构建天然更新模型时,林分密度是十分重要的因子,如果要人工促进天然更新,就要科学合理的采取经营措施,以确保合理的林分密度。另外样地间的差异是不容忽略的因素,需要利用混合效应模型方法来降低预测误差。     

线性红利界下带干扰风险模型的破产概率

考虑到保险公司在实际经营中收益所具有的不确定性和分红策略，建立一类具有线性红利界和带随机扰动的双复合Poisson风险模型，利用鞅方法给出模型关于破产概率的一个定理及上界．     

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).     

Reducing crude protein variability and maximizing savings when formulating corn-soybean meal-based feeds

Crude protein in corn and soybean meal have been documented to vary, and such inherent variability can result in under- or over-feeding of CP when feeds are formulated, leading to reduced bird growth, added input costs, and increased environmental pollution. The purpose of this study was to compare 2 grain-handling techniques and 2 feed formulation methods (linear vs. stochastic programming) to reduce CP variability in finished feeds and determine resulting costs or savings. The 2 grain-handling techniques were placing all the random batches of each delivered ingredient in to (1) a single bin (1-bin method) or (2) segregating above- and below-average samples into 2 bins (2-bin method). A fast way of estimating the composition of the ingredients is now available (near-infrared reflectance spectroscopy). Microsoft Excel workbooks were constructed to solve broiler starter feed formulation problems. Formulating feeds by linear and stochastic models based on the 2-bin method reduced CP variability by at least 50% compared with the 1-bin method. Formula cost was reduced by ˜20 cents per ton (averages of August 2012 United States ingredient prices) when the 2-bin method was used with the linear model. Formulating feed with a margin of safety increased formula cost by $3.40 per ton. Stochastic feed formulation increased formula cost to meet the specified CP level in feed at any probability of success, and formula cost was reduced substantially with the 2-bin method (up to $6.47 per ton). The magnitude of savings and reduced feed variability suggested that, regardless of the costs associated with building extra bins, the 2-bin method can be economically efficient in the long run. Therefore, it could be possible to split the batches of feed ingredients at a feed mill into above- or below-average bins before feed formulation to reduce CP variability and to maximize savings.     

Potato absorption and phytoavailability of Cd,Ni, Cu,Zn and Pb in sierozem soils amended with municipal sludge compost

Effects of sludge utilization on the mobility and phytoavailability of heavy metals in soil-plant systems have attracted broad attention in recent years. In this study, we analyzed the effects of municipal sludge compost(MSC) on the solubility and plant uptake of Cd, Ni, Cu, Zn and Pb in a soil-potato system to explore the mobility, potato plant uptake and enrichment of these five heavy metals in sierozem soils amended with MSC through a potato cultivation trial in Lanzhou University of China in 2014. Ridge regression analysis was conducted to investigate the phytoavailability of heavy metals in amended soils. Furthermore, CaCl_2, CH_3 COONH_4, CH_3COOH, diethylene triamine pentacetic acid(DTPA) and ethylene diamine tetraacetic acid(EDTA) were used to extract the labile fraction of heavy metals from the amended soils. The results show that the MSC could not only improve the fertility but also increase the dissolved organic carbon(DOC) content of sierozem soils. The total concentrations and labile fraction proportions of heavy metals increase with increasing MSC percentage in sierozem soils. In amended soils, Cd has the highest solubility and mobility while Ni has the lowest solubility and mobility among the five heavy metals. The MSC increases the concentrations of heavy metals in the root, stem, peel and tuber of the potato plant, with the concentrations being much higher in the stem and root than in the peel and tuber. Among the five heavy metals, the bioconcentration factor value of Cd is the highest, while that of Ni is the lowest. The complexing agent(DTPA and EDTA) extractable fractions of heavy metals are the highest in terms of phytoavailability. Soil properties(including organic matter, p H and DOC) have important impacts on the phytoavailability of heavy metals. Our results suggest that in soil-potato systems, although the MSC may improve soil fertility, it can also increase the risk of soils exposed to heavy metals.