IMPROVEMENT OF SANDY SOIL WITH WATERCONSERVING MEMBRANE AND ITS EFFECT ON CROP GROWTH

1INTRODUCTIONArid, semi-arid, and semi-humid areas abound in sandysoil, which causes water to leak into deep soil orgroundwater so that soil′s water-conserving capabilitybecomes lower and water is used with low efficiency.Water is one of the important fa…     

SPECIALTY CROPLAND IN CALIFORNIA*

ABSTRACT. Census data do not support the widespread popular perception that urban encroachment on cropland in California is serious enough to justify programs of farmland preservation. Between 1949 and 1997 the acreage of harvested cropland declined near Los Angeles, in the San Francisco Bay area, and near Sacramento, but the high‐value specialty agricultural production displaced from these areas has been relocated to more distant areas, where it has replaced lower‐value field crops, and specialized agricultural production has increased steadily in the state. Vegetable production in the Salinas Valley and dairying near Los Angeles illustrate the twin processes of relocation and replacement. Urban encroachment actually has been a boon to California agriculture, because it has transferred massive amounts of urban capital to cash‐strapped farmers and enabled them to develop efficient modern operations. Much of the concern about loss of farmland really is concern about loss of open space and amenities, and urban demand for water probably will be a greater constraint on California agriculture than will urban demand for land.     

Explaining the stickiness of supply chain relations in the Brazilian soybean trade

The global trade of agricultural commodities has profound social-ecological impacts, from potentially increasing food availability and agricultural efficiency, to displacing local communities, and to incentivizing environmental destruction. Supply chain stickiness, understood as the stability in trading relationships between supply chain actors, moderates the impacts of agricultural commodity production and the possibilities for supply-chain interventions. However, what factors determine stickiness, that is, how and why farmers, traders, food processors, and consumer countries, develop and maintain trading relationships with specific producing regions, remains unclear. Here, we use data on the Brazilian soy supply chain, a mixed methods approach based on extensive actor-based fieldwork, and an explanatory regression model, to identify and explore the factors that influence stickiness between places of production and supply chain actors. We find four groups of factors to be important: economic incentives, institutional enablers and constraints, social and power dimensions, and biophysical and technological conditions. Among the factors we explore, surplus capacity in soy processing infrastructure, (i.e., crushing and storage facilities) is important in increasing stickiness, as is export-oriented production. Conversely, volatility in market demand expressed by farm-gate soy prices and lower land-tenure security are key factors reducing stickiness. Importantly, we uncover heterogeneity and context-specificity in the factors determining stickiness, suggesting tailored supply-chain interventions are beneficial. Understanding supply chain stickiness does not, in itself, provide silver-bullet solutions to stopping deforestation, but it is a crucial prerequisite to understanding the relationships between supply chain actors and producing regions, identifying entry points for supply chain sustainability interventions, assessing the effectiveness of such interventions, forecasting the restructuring of trade flows, and considering sourcing patterns of supply chain actors in territorial planning.     

Crystallization Kinetics of Potassium Sulphate in Aqueous System Mg~(2+),K~+//Cl,SO_4~(2-)-H_2O

正As an excellent chemical fertilizer,Potassium Sulphate(K2SO4)could provide both potassium and sulfur elements for crops.However,it is well known that potassium resource is very poor in China.To understand the Crystallization Kinetics(CK)of K2SO4could be conducive to utilize the limited potassium resource,promote the yield and purity of K2SO4.In this study saturated solution of potassium sulphate was prepared according to the phase diagram of Mg2+、     

基于作物双时相遥感特征的花生种植区提取

基于花生生长中后期2020年8月1日和15日两个时相高分多光谱数据,构建40个作物分类遥感特征,采用ReliefF-Pearson方法优选出15个特征,构造作物可分的4种特征空间。采用最大似然分类法、支持向量机和随机森林分类器,分别耦合4种特征空间,开展作物分类对比试验,进行分类精度和景观评价提出作物双时相遥感分类模型(dual-temporal remote sensing classification model for crop, C-DRSC)。结果表明：该模型具有较高的作物分类和花生识别能力,作物分类总体精度和Kappa系数分别为93.25%和0.89,平均形状指数和平均斑块分维指数分别为1.33和1.13;花生识别的用户精度和制图精度分别为96.20%和96.32%,平均形状指数和平均斑块分维指数分别为1.27和1.11。利用该模型在黄淮海地区的4个花生主产县开展夏花生种植面积遥感测算,与统计面积相比,面积测算相对误差为±16.25%,决定系数为0.9778(达到0.01显著性水平),模型具有较好的适用性。     

Comprehensive study of the biophysical parameters of agricultural crops based on assessing Landsat 8 OLI and Landsat 7 ETM+ vegetation indices

For three agricultural crop types, winter wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), and canola (Brassica napus L.), we estimated biophysical parameters including fresh and dry biomass, leaf area index (LAI), and vegetation water content, for which we found the equivalent water thickness (EWT), fuel moisture content per fresh weight (FMC_FW), and fuel moisture content per dry weight (FMC_DW). We performed these estimations using data from the newly launched Landsat 8 Operational Land Imager (OLI) sensor, as well as its predecessor the Landsat 7 Enhanced Thematic Mapper Plus (ETM+). Progress in the design of the new sensor (i.e., Landsat 8), including narrower near-infrared (NIR) wavebands, higher signal-to-noise ratio (SNR), and greater radiometric resolution highlights the necessity to investigate the biophysical parameters of agricultural crops, especially compared to data from its predecessor. This study aims to evaluate vegetation indices (VIs) derived from the Landsat 8 OLI and the Landsat 7 ETM+. Both the Landsat 8 OLI and Landsat 7 ETM+ VIs agreed well with in-situ data measurements. However, the Landsat 8 OLI-derived VIs were generally more consistent with in situ data than the Landsat 7 ETM+ VIs. We also note that the Landsat 8 OLI is better able to capture the small variability of the VIs because of its higher SNR and wider radiometric range; in addition, the saturation phenomenon occurred earlier for the Landsat 7 ETM+ than for the Landsat 8 OLI. This indicates that the new sensor is better able to estimate the biophysical parameters of crops.     

Identifying farmer attitudes towards genetically modified (GM) crops in Scotland: Are they pro- or anti-GM?

The GM debate in the European Union has been consistently presented as being conflictual and contentious, characterised as being polarised into those who are pro-GM and those who are anti-GM. This is largely based on the positions adopted by the public (consumers), non-governmental organisations (NGOs), and industry and corporate bodies. One group largely lacking from this debate is farmers, and yet their decisions about whether or not to cultivate GM crops will be crucial to the future of the technology in European agriculture. This paper reports findings from a study investigating farmers’ attitudes to GM crops in Scotland using Q methodology. Results reveal three discourses, one inclined to be positive towards the idea of GM and demonstrating an expectation of benefits, the second representing a more uncertain position, wary of the potential risks of the technology but likely to be reluctant adopters, and the third describing a group who demonstrate a somewhat fatalistic attitude towards the issue of GM technology adoption and impact. These findings contribute to the GM debate by elaborating the views of this important stakeholder group and suggest that they may be less profoundly pro- or anti-GM than other groups involved in the debate. This is significant if they represent the ‘middle ground’ between the biotechnology industry and the public.     

GIS下农用地分等专家系统

以《农用地分等规程》及《农用地分等数据库标准》为准绳,把专家系统的思想融合到G IS开发环境中,设计了满足因素法进行县级农用地分等的专家系统,该系统具有知识库创建、知识库选择、土地利用系数与经济系数等值划分与制图、自然质量等指数与利用等指数及经济等指数计算、自然等与利用等及经济等划分与制图等功能模块。研究与实验表明:该系统通用性强,提高了分等过程的自动化程度及图件成果的标准化程度。     

基于多时相影像的农业作物非参数与概率分类

本文提出了一种新的结合多光谱和变化检测技术的多时相卫星数据集分类方法。该方法以数理统计中的最近邻法为基础,其目标函数是使得正确分类的平均概率得到最优化,即把每个分类类别看成同等重要。该新算法被应用于一个农业作物分类的研究区域,并利用覆盖该区的不同季节的SPOT和LANDSAT TM多时像影像。结果表明,与单时像影像相比,使用五个不同季节的多时像影像可以充分地提高分类精度。为了说明该方法在大尺度范围内的效果,本文选取瑞典道拉河流域作为研究区。由于不同地物的分布高度重叠,不可能得到像元水平上满意的分类精度。这就需要引进一种新的概念：像元概率分类法。基于像元的概率向量可用于判别传统分类法的可靠性并测量单个像元的不确定性（熵）。概率分类法同时提供了不同地物的面积的无偏估计,无论所感兴趣的区域的大小。这已经在不同特性的耕地试验点进行了检验。     

基于GPS照片数据处理系统的地面样方调查

集成GPS模块的相机拍摄的农作物照片可同时记录地物类型和空间位置。为了处理大量的地面样方照片数据并及时转换为遥感监督分类的训练样本,开发了一个能够高效处理样方GPS照片数据的软件系统。该系统通过人机交互判识照片中的地物类型,同时提取照片的地理位置信息,并对样本的地理位置进行修正或补充,在地图与遥感影像的辅助下生成有效的样本信息。以宁夏银川灌区农作物采样样本为例,对系统进行了测试。结果表明,1 000个典型的训练样本可在1 h内产生,减少了样本的处理时间,提高了样本的质量。