基于卷积神经网络的拖拉机工况识别

农机工况识别在细化农机作业状态和帮助掌握区域污染物排放趋势方面有着重要的研究价值。基于拖拉机不同运行状态下的行驶速度、发动机转速以及实时油耗等时间序列,首次提出将图像识别方法引入到拖拉机工况识别中的思路,并分别应用参数优化的支持向量机与卷积神经网络对实际作业拖拉机工况进行研究。结果表明:(1)基于参数优化的支持向量机可以较好地实现样本点的工况识别且识别准确度达到99.851 9%,但无法实现农机工况的连续性识别,同时无法对农机工况转换阶段进行有效识别。(2)以拖拉机运行速度与发动机转速等信息构建样本图像来描述农机工况变化的数据表达,并在此基础上应用卷积神经网络可以有效实现农机工况的连续性识别,且识别准确率可以达到93.3%。本研究在农机工况识别方面具有一定参考价值,并为后续农机不同工况下区域污染物排放研究提供技术支持。     

基于声振信号对称极坐标图像的苹果霉心病早期检测

为实现苹果早期霉心病较高精度的检测，该研究采用对称极坐标法（Symmetrized Dot Pattern，SDP）将苹果声振信号变换为雪花图，然后采用AlexNet、VGG16和ResNet50卷积神经网络以迁移学习方式深度挖掘SDP雪花图像的特征信息，将其输入到支持向量机（Support Vector Machine，SVM）分类器，对霉心程度≤7%的苹果进行检测。研究结果表明，当时间间隔系数为25和角度放大因子为50°时，健康果与早期霉心果声振信号的SDP图形状特征差异最大，在此条件下获取的SDP图经卷积神经网络AlexNet、VGG16和ResNet50提取特征并构建了不同核函数的SVM霉心果检测模型，在各类SVM模型中，ResNet50-SVM-gaus（高斯基）模型用相对较少的训练时间和参数量可取得训练集霉心果较高分类准确率，经超参数优化训练该模型对健康果和早期霉心果测试集不平衡样本（10∶1）的总体分类准确率达到96.97%，平均查准率、平均查全率、平均加权调和均值、Kappa系数和马修斯相关系数值分别为80.19%、90.36%、86.21%，82.54%和82.68%，该模型不仅对多数类的健康果保持较高分类准确率，而且对少数类的早期霉心果也具有较高判别能力。这些研究结果为声振法应用于果蔬内部病害的早期在线检测系统研发提供了技术支撑。     

福建省高素质农民发展跟踪分析

为反映福建省高素质农民的发展状况,探索高素质农民培育的更有效途径,采用比较分析方法,跟踪调查2015—2018年福建省高素质农民的总量、性别比例、年龄结构、文化程度等数据,并以此为基础,重点分析农业新型经营主体家庭农场经营者、农民合作社负责人等群体的发展情况,同时比较研究福建省高素质农民重点群体之间的发展特点。从文化程度、培育供求、产学矛盾、政策扶持等方面深入剖析当前高素质农民发展的制约因素,从加快推进福建省高素质农民培育工作、构建高素质农民终身学习体系、探索培育新型农业经营模式、推进线上线下融合培育、创设高素质农民扶持政策等方面提出相应的对策建议。     

生态系统视角下农村失独家庭的困境应对策略研究

农村失独父母是我国计划生育政策实施以来产生的一个特殊弱势群体。由于农村社会经济发展的特殊性,处于失独困境的家庭亟待政府和社会的更多关注和支持。农村失独家庭面临家庭关系紧张、精神承受重压、经济水平落后、生活缺乏照顾、养老医疗困顿、人际关系贫瘠等难题。为了化解上述难题,必须尽可能发挥政府和社会的保障支持功能。基于生态系统理论,需要通过多主体协同,从宏观、外层、中层、微观四个层次构建对于农村失独家庭的社会保障、社会支持体系,形成为农村失独家庭服务的系统性支持保障网络。     

Mitigating nitrous oxide emissions from agricultural soils by precision management

Nitrous oxide (N₂O) emissions make up a significant part of agricultural greenhouse gas emissions. There is an urgent need to identify new approaches to the mitigation of these emissions with emerging technology. In this short review four approaches to precision managements of agricultural systems are described based on examples of work being undertaken in the UK and New Zealand. They offer the opportunity for N₂O mitigation without any reduction in productivity. These approaches depend upon new sensor technology, modeling and spatial information with which to make management decisions and interventions that can both improve agricultural productivity and environmental protection.     

公共财政支持"三农"发展的对策研究

中国自古以来都是以农业大国闻名世界，精耕细作、小农经济是传统中国经济的象征。所 以，中国政府也一直致力于农业的发展建设。目前，“三农”问题是中国共产党所要改善和提升的主要 对象。国内基层群众大部分都属于农民。由此可见，推动农业的发展是当前中国共产党势在必行的 任务。     

The use of infrared spectroscopy and machine learning tools for detection of Meloidogyne infestations

Plant parasitic nematodes are generally soilborne pathogens that attack plants and cause economic losses in many crops. The infested plants show nonspecific symptoms or, often, are symptomless; therefore, diagnosis is performed by taking soil and root tissue samples. Here, we show that a combination of different infrared spectra analysis and machine learning algorithms can be used to detect plant parasitic nematode infestations before symptoms become visible, using leaves instead of roots and soil as samples. We found that tomato and guava plants infested with Meloidogyne enterorlobii produced different spectral patterns compared to uninfested plants. Using partial spectra from 1,450 to 900/cm as the "fingerprint region", principal component analyses indicated that after 5 (tomatoes) or 8 weeks (guava), plants with no visible symptoms of infestations were positively diagnosed. To improve the early detection response, we used machine learning modelling. A support vector machine (SVM) was used to obtain more robust, accurate models. The SVM model contained 34 support vectors, 17 for each level. The overall performance of the model was >97% and the total accuracy was significantly higher, demonstrating the absence of chance prediction. The best prediction of infestation was obtained at the second and fourth weeks for tomatoes and guavas, respectively, reducing the diagnostic time by half. The combined application of these techniques reduces the processing time from field to laboratory and shows enormous advantages by avoiding root and soil sampling.     

The pelagic habitat analysis module for ecosystem‐based fisheries science and management

We have developed a set of tools that operate within an aquatic geographic information system to improve the accessibility, and usability of remote‐sensed satellite and computer‐modeled oceanographic data for marine science and ecosystem‐based management. The tools form the Pelagic Habitat Analysis Module (PHAM), which can be applied as a modeling platform, an investigative aid in scientific research, or utilized as a decision support system for marine ecological management. Applications include fisheries, marine biology, physical and biological oceanography, and marine spatial management. The GIS provides a home for diverse data types and automated tools for downloading remote sensed and global circulation model data. Within the GIS environment, PHAM provides a framework for seamless interactive four‐dimensional visualization, for matching between disparate data types, for flexible statistic or mechanistic model development, and for dynamic application of user developed models for habitat, density, and probability predictions. Here we describe PHAM in the context of ecosystem‐based fisheries management, and present results from case study projects which guided development. In the first, an analysis of the purse seine fishery for tropical tuna in the eastern Pacific Ocean revealed oceanographic drivers of the catch distribution and the influence of climate‐driven circulation patterns on the location of fishing grounds. To support management of the Common Thresher Shark (Alopias vulpinus) in the California Current Ecosystem, a simple empirical habitat utilization model was developed and used to dynamically predict the seasonal range expansion of common thresher shark based on oceanographic conditions.     

Four years validation of decision support optimising herbicide dose in cereals under Spanish conditions

The Danish decision support system Crop Protection Online (CPO) optimises herbicide weed control. CPO recommends specific herbicide solutions to achieve a required level of control. The aim is to apply herbicides as little as possible but as much as necessary. CPOWeeds is a version of CPO adjusted to conditions in North-eastern Spain. The predicted efficacies and the yield obtained with CPOWeeds were validated in winter cereal field trials from 2010 to 2013. All CPOWeeds treatments were related to the efficacies obtained with standard herbicide treatments decided upon by local advisors. The predictions from CPOWeeds were compared to the actually achieved efficacies in the field trials for the nine weed species at different developmental stages and for 84.2% of the comparisons the obtained efficacies were equal to or higher than predicted. The average difference between predicted and observed efficacies was 2.35 percentage points. Yield was measured in three trials and the recommendations from CPOWeeds were maintaining yield. There were two situations where CPOWeeds were performing suboptimal. One is in the early weed growth stages, as the model is not yet prepared to account for water stress on root action herbicides applied at 10-11 BBCH. The second situation was in fields with a prior unidentified population of resistant Alopecurus myosuroides. For key species in winter cereals in Spain, such as Avena sterilis, Lolium rigidum and Papaver rhoeas, CPOWeeds achieved a satisfactory control level. It was concluded that the use of CPOWeeds allowed optimisation of the herbicide application with a very high robustness. The recommendations were satisfactorily for the conditions of the Northeast of Spain and have the potential to decrease the amount of applied herbicides by at least 30%. Therefore, it can be an important tool in Integrated Weed Management.     

台湾地区乡村创业政策对于大陆乡村的启示

【目的/意义】通过研究台湾和大陆乡村的创业政策,积极探索自上而下的国家战略和自下而上的实际需求相互结合的乡村创业政策制定方法,为实现乡村振兴提供参考。【方法/过程】该文采用政策梳理、总结与对比的研究方法,对大陆乡村创客政策进行分析,总结其相关特点和问题。同时,梳理台湾地区乡村创客政策类型和特点,总结其在乡建人才的长效吸引、有认同性的活动策划及政策的长效跟踪等方面的可借鉴经验。【结果/结论】研究结果表明:创业政策有明确恰当的导向是创业成功的基础,而政策对人长期的吸引是振兴的迫切需求,由活动带动建设是活力重塑的关键,政策的长效跟踪是有效实施的保障。