精确农业导论

不管农田固有的空间差异,采用单一方法进行管理,是当前普遍采用的一种传统管理方式。由于农业机械化的需要,地块越来越大,这就使这种管理方式的弊端日趋严重。精确农业（ｐｒｅｃｉｓｉｏｎ ｆａｒｍｉｎｇ）是在信息技术支撑下的一种新型管理方式,它可以使经营者更深刻地理解和精确地控制农场的生产状况。精确农业的核心是对变化因素进行管理。最明显的变化因素有三个：空间（ｓｐａｔｉａｌ）、时间（ｔｅｍｐｏｒａｌ）和预     

Sensing technologies for precision specialty crop production

With the advances in electronic and information technologies, various sensing systems have been developed for specialty crop production around the world. Accurate information concerning the spatial variability within fields is very important for precision farming of specialty crops. However, this variability is affected by a variety of factors, including crop yield, soil properties and nutrients, crop nutrients, crop canopy volume and biomass, water content, and pest conditions (disease, weeds, and insects). These factors can be measured using diverse types of sensors and instruments such as field-based electronic sensors, spectroradiometers, machine vision, airborne multispectral and hyperspectral remote sensing, satellite imagery, thermal imaging, RFID, and machine olfaction system, among others. Sensing techniques for crop biomass detection, weed detection, soil properties and nutrients are most advanced and can provide the data required for site specific management. On the other hand, sensing techniques for diseases detection and characterization, as well as crop water status, are based on more complex interaction between plant and sensor, making them more difficult to implement in the field scale and more complex to interpret. This paper presents a review of these sensing technologies and discusses how they are used for precision agriculture and crop management, especially for specialty crops. Some of the challenges and considerations on the use of these sensors and technologies for specialty crop production are also discussed.     

中国农作物长势遥感监测研究综述

农作物长势监测的目的是为早期估产提供依据,同时为田间管理提供及时的信息。笔者总结了中国农作物长势监测的研究进展、研究方法,指出用于长势监测的遥感数据空间分辨率较低,常用的监测指标具有局限性,监测精度有待提高。“3S”技术的集成发展,进一步实现一体化应用于该领域仍是今后的发展方向。随着农作物长势运行化监测系统的进一步完善,对田间管理的诊断需求会日益加剧,因此作物长势的诊断将成为今后的研究重点。     

PhenologyMMS: A program to simulate crop phenological responses to water stress

Crop phenology is fundamental for understanding crop growth and development, and increasingly influences many agricultural management practices. Water deficits are one environmental factor that can influence crop phenology through shortening or lengthening the developmental phase, yet the phenological responses to water deficits have rarely been quantified. The objective of this paper is to provide an overview of a decision support technology software tool, PhenologyMMS V1.2, developed to simulate the phenology of various crops for varying levels of soil water. The program is intended to be simple to use, requires minimal information for calibration, and can be incorporated into other crop simulation models. It consists of a Java interface connected to FORTRAN science modules to simulate phenological responses. The complete developmental sequence of the shoot apex correlated with phenological events, and the response to soil water availability for winter and spring wheat (Triticum aestivum L.), winter and spring barley (Hordeum vulgare L.), corn (Zea mays L.), sorghum (Sorghum bicolor L.), proso millet (Panicum milaceum L.), hay/foxtail millet [Setaria italica (L.) P. Beauv.], and sunflower (Helianthus annus L.) were created based on experimental data and the literature. Model evaluation consisted of testing algorithms using “generic” default phenology parameters for wheat (i.e., no calibration for specific cultivars was used) for a variety of field experiments to predict developmental events. Results demonstrated that the program has general applicability for predicting crop phenology and can aid in crop management.     

A comparison between spatial clustering models for determining N-fertilization management zones in orchards

Precision Agriculture - Site-specific agricultural management (SSM) relies on identifying within-field spatial variability and is used for variable rate input of resources. Precision agricultural...     

Spatial variability in commercial orange groves. Part 1: canopy volume and height

Precision Agriculture - Characterizing crop spatial variability is crucial for estimating the opportunities for site-specific management practices. In the context of tree crops, ranging sensor...     

Management zone delineation using a modified watershed algorithm

Site-specific management (SSM) is a common way to manage within-field variability. This concept divides fields into site-specific management zones (SSMZ) according to one or several soil or crop characteristics. This paper proposes an original methodology for SSMZ delineation which is able to manage different kinds of crop and/or soil images using a powerful segmentation tool: the watershed algorithm. This image analysis algorithm was adapted to the specific constraints of precision agriculture. The algorithm was tested on high-resolution bio-physical images of a set of fields in France.     

Estimation of soil organic carbon stock and its controlling factors in cropland of Yunnan Province,China

Soil organic carbon (SOC) is the most important indicators of soil quality and health. Identifying the spatial distribution of SOC and its influencing factors in cropland is crucial to understand the terrestrial carbon cycle and optimize agronomic management. Yunnan Province, characterized by mountainous topography and varied elevation, is one of the highest SOC regions in China. Yet its SOC stock of cropland and influencing factors has not been fully studied due to the lack of adequate soil investigation. In this study, the digital mapping of SOC at 1 km resolution and the estimation of total SOC stock in cropland of Yunnan Province was undertaken using 8 637 topsoil (0–20 cm) samples and a series of spatial data through Random Forest (RF) model. It was showed that across the cropland of Yunnan Province, the mean SOC density and total stock were 4.84 kg m^–2 and 337.5 Mt, respectively. The spatial distribution indicated that relatively high SOC density regions resided in the northwest and northeast parts of Yunnan Province. Elevation (19.5%), temperature (17.3%), rainfall (14.5%), and Topographic wetness index (9.9%) were the most important factors which controlled spatial variability of SOC density. Agronomic practices (e.g., crop straw treatments, fertilizer management) should be optimized for the sustainable development of crop production with high SOC sequestration capacity in Yunnan Province.     

Spatio-temporal consideration of soil conditions and site-specific management of nematodes

Site-specific (precision) management (SSM) has potential for application in managing nematodes and soil conditions in environmentally meaningful ways. Successful application of SSM, however, may be dependent on how agronomically, biologically, and ecologically integrated the plan in question is. Otherwise, SSM risks falling into the “Tried but did not last” category. With this background and in addition to describing the concepts and principles of SSM, this presentation discusses the following interrelated points: (1) Case studies of spatio-temporal analysis of soybean cyst nematode (Heterodera glycines) infestations, soil conditions and crop yield in managed ecosystems. Among the critical factors to an accurate and sustained application of SSM are understanding (i) the temporal structure and (ii) the spatial structure of the attribute in question, and (iii) establishing cause-and-effect relationships in the prevailing conditions. New approaches to temporal structure analysis when balancing the purpose of SSM application and nematode biology (as it relates to life stages), population density in soil and root tissue (to determine threshold), and damage functions (physiological stress of the plant during the growing season) are outlined. (2) Application of the concept of fertiliser use efficiency (FUE) to identify soil conditions when managing soil fertility. Defined as increase in host productivity and/or decrease in plant-parasitic nematode population density in response to a given fertiliser treatment, the FUE model recognizes variable responses and identifies four categories of interactions necessary for integrated management decision-making options that account for agronomic, economic, ecological and environmental and pest management issues. (3) Approaches to changing soil conditions in agro-biologically integrated ways. By incorporating nematode community structure (an excellent indicator of soil bio-ecological changes), soil nutrient amendments and crop yield, we have described a modification of the FUE model to identify and monitor changes in soil conditions, thereby creating the necessary bridges to disciplinary and cross-disciplinary gaps and interactions.     

Conservation tillage

Conservation production systems combine tillage and planting practices to reduce soil erosion and loss of water from farmland. Successful conservation tillage practices depend on the ability of farm managers to integrate sound crop production practices with effective pest management systems. More scientific information is needed to determine the relations between tillage practices and physical, chemical, and biological soil factors that affect plant and pest ecology. There is a need to devise improved pest management strategies for conservation tillage and to better understand the impact of conservation tillage on water-quality, especially as it is related to use of agricultural chemicals. While savings in fuel, labor, and soil have induced many farmers to adopt conservation tillage, improved methods and equipment should increase adoption even more.     

The impact of farmers’ assessments of risk management strategies on their adoption willingness

Farmers’ assessments of risk management strategies and how the assessments influence their willingness to adopt these strategies are poorly understood. This study conducts a structured survey of 469 farmers to investigate how farmers assess both crop insurance and crop price insurance, the impact of the assessments on their adoption willingness, and in particular, the differences in assessments and adoption willingness between crop insurance and crop price insurance. Empirical results show that farmers’ assessments on crop insurance can be significantly improved through communication and experience. The most effective way to improve farmers’ assessments on crop price insurance is providing adequate information about the insurance products. Furthermore, farmers’ adoption willingness would be enhanced by improved assessment of both crop yield and crop price insurance. This study provides the first empirical evidence that farmers have limited information to assess insurance, which significantly influences their willingness to adopt. This finding reflects that the dissemination of insurance policies, the effectiveness of insurance, and the availability of insurance services significantly enable farmers’ ability to assess risk management strategies, which potentially increases farmers’ willingness to adopt insurance.     

基于Quickbird遥感影像的农田管理分区划分研究

 【目的】以高空间分辨率Quickbird遥感影像作为管理分区划分的数据源，结合地面土壤养分采样数据进行管理分区划分研究。【方法】在对数据进行空间变异分析的基础上，采用3种不同的分区方式对研究区进行田块尺度内管理分区的划分：1）利用土壤养分数据划分管理分区；2）利用冬小麦遥感长势信息划分管理分区；3）利用土壤养分信息结合冬小麦长势信息划分管理分区。【结果】与划分前的地块变异情况相比，利用土壤养分数据进行管理分区划分的方法，在很大程度上提高了不同分区内土壤的均一度，而光谱指数和产量的变异系数也有所降低；利用光谱数据进行管理分区划分，土壤养分的变异系数总体上有所减低，但降低的幅度小于利用土壤养分数据划分的管理分区，光谱指数和产量的变异系数都有大幅度降低；利用土壤数据结合光谱数据进行管理分区划分，土壤养分和光谱指数以及产量的变异系数普遍降低。【结论】在划分管理分区时，综合考虑土壤养分和光谱数据的空间变异情况是最佳选择，但当缺乏土壤养分数据时，利用遥感影像进行管理分区的划分也是可行的。     

RS和GIS技术与作物模型结合的研究进展

借助于RS和GIS技术,可以将作物模型的应用提升为区域尺度。在文献综述的基础上,全面总结了RS、GIS技术与作物模型结合的国内外研究进展,阐述了RS与GIS技术和作物模型各自的优势、结合的必要性以及相结合的方式、层次和结合点,列举了一些结合应用的例子,目前研究应用的现状,并分析了二者与作物模型结合的不足与研究前景。随着RS与GIS技术发展越来越成熟,RS与GIS技术和作物模型结合,是作物模型发展的重要趋势之一,并且这一趋势将促进RS、GIS、作物模型在农业中的广泛应用。     

Spatial variability in grape yield and quality influenced by soil and crop nutrition characteristics

Knowledge of spatial variability of soil fertility and plant nutrition is critical for planning and implementing site-specific vineyard management. To better understand the key drivers behind vineyard variability, yield mapping from 2002 to 2005 and 2007 (the monitor broke down in 2006) was used to identify zones of different productive potential in a Pinot Noir field located in Raimat (Lleida, Spain). Simultaneously, the vineyard field was sampled in 2002, 2003 and 2007, applying three different schemes (depending on the number of target vines in different grape yield zones). The sampling carried out in 2002, which involved different soil, topographic and crop properties (mineral contents in petiole), made it possible to evaluate the influence of these parameters on the grape yield variability. The zones of lowest yield coincided with locations in which the nutritional status of the crop exhibited the lowest values, particularly with respect to petiole contents of calcium and manganese. Sampling systems adopted in 2003 and 2007 (grape quality and soil attributes) confirmed the inverse spatial correlation between grape yield and some grape quality parameters and, more importantly, showed that the percentage of soil carbonates had a great influence on grape quality probably due to the reduced availability of manganese in calcareous soils. Site-specific vineyard management could therefore be considered using two different strategies: variable-rate application of foliar fertilizers to increase the yield in areas with low production and also foliar or soil fertilizers to improve the quality specifications in some areas.     

作物信息技术及其在棉花生产中的应用与展望

阐述了作物信息技术的内涵以及作物生长模拟模型、农业专家系统和作物生产决策系统的应用及发展概况 ,并阐述了作物信息技术在棉花生产中的应用状况和发展前景。     

Spatial variability and temporal stability of apparent soil electrical conductivity in a Mediterranean pasture

The general objectives of this study were to evaluate (i) the specificity of the spatial and temporal dynamics of apparent soil electrical conductivity (EC_a) measured by a electromagnetic induction (EMI) sensor, over 7 years, in variable conditions (of soil moisture content (SMC), soil vegetation cover and grazing management) and, consequently, (ii) the potential for implementing site-specific management (SSM). The DUALEM 1S sensor was used to measure the EC_a in a 6 ha pasture experimental field four times between June 2007 and February of 2013. Soil spatial variability was characterized by 76 samples, geo-referenced with the global positioning system (GPS). The soil was characterized in terms of texture, moisture content, pH, organic matter content, nitrogen, phosphorus and potassium. This study shows a significant temporal stability of the EC_a patterns under several conditions, behavior that is an excellent indicator of reliability of this tool to survey spatial soil variability and to delineate potential site-specific management zones (SSMZ). Significant correlations were obtained in this work between the EC_a and relative field elevation, pH, silt and soil moisture content. These results open perspectives for using the EMI sensor as an indicator of SMC in irrigation management and of needs of limestone correction in Mediterranean pastures. However, it is interesting to extend the findings to other types of soil to verify the origin of the lack of correlation between the EC_a data measured by DUALEM sensor and properties such as the clay, organic matter or phosphorus soil content, fundamental parameters for establishment of pasture SSM projects.     

可持续土壤管理:土壤学服务社会发展的挑战

国际土壤年唤醒了全社会对土壤变化的关注。地球环境与生命发育历史赋予了土壤自然资源资产价值,提供了生命和生态系统发育的多种服务,从而惠及全人类,支撑了社会的可持续性发展。全球土壤的这种支撑能力建立在"体-质-量"统一的土壤属性基础上。然而,在人类快速发展的驱动下,全球土壤已经或正在发生十分普遍和严重的土壤退化,土壤连续体遭到破坏,土壤功能严重削弱,且地表土壤覆盖被大面积固封。因此,必须充分认识土壤变化对于人类长远发展的潜在风险,着力构建可持续土壤管理体系,致力于保持土壤自然资产价值、平衡和最大化土壤的生态系统服务、优化兼顾农业安全(粮食安全-环境安全-生态安全)的土壤利用与保护。保持土壤自然资产、保持土壤的生态系统服务和保持土壤对全人类的惠利应该纳入生态文明的土壤观。而管控土壤变化势必成为可持续土壤管理的核心任务。这需要在政策上,推行生态补偿机制来处理利用者与受益者的利益关系;在行动上,实施区域土壤可持续管理工程,应对土壤变化;而在技术上,创新兼效多赢的管理实践措施,特别是有利于自然养育或恢复的土壤保护和培育技术。推进土壤可持续管理研究,探索可持续土壤管理途径,对于中国社会经济的可持续发展具有至关重要的意义。     

SUSTAINABLE PLANT PEST MANAGEMENT THROUGH OPTIMIZATION AND MINIMIZATION

Plant pests and diseases have significant negative impacts on global food security, world trade and rural livelihoods. Climate change exacerbates these impacts in certain parts of the world. Overreliance on pesticides as the primary tool for plant pest management leads to problems such as pesticide resistance and pest resurgence. Environmental and food safety concerns are also associated with overuse of pesticides in crop production. There is clearly a need for a shift in pest management strategies and practices globally. Optimization of structures and functions in crop production agroecosystems through soil conservation practices and cropping diversification can improve pest regulation services provided in the systems. Prioritization of safer alternatives and practices in the IPM pyramid, such as resistant varieties and biopesticides, helps minimize the use of potentially risky agricultural inputs such as synthetic pesticides. Investment is needed to boost the development of innovative green technologies and practices. Production, distribution, use and regulatory capacities need to be strengthened to facilitate large-scale adoption of green technologies and practices. Finally, policy, financial and market instruments should be wielded to provide an enabling environment for the transformation to sustainable plant pest and disease management strategies and practices worldwide.     

Assessing UAV-collected image overlap influence on computation time and digital surface model accuracy in olive orchards

Addressing the spatial and temporal variability of crops for agricultural management requires intensive and periodical information gathering from the crop fields. Unmanned Aerial Vehicle (UAV) photogrammetry is a quick and affordable method for information collecting; it provides spectral and spatial information when required with the added value of Digital Surface Models (DSMs) that reconstruct the crop structure in 3D using “structure from motion” techniques. In the full process from UAV flights to image analysis, DSM generation is one bottle-neck due to its high processing time. Despite its importance, the optimization of the required forward overlap for saving time in DSM generation has not yet been studied. UAV images were acquired at 50 and 100 m flight altitudes over two olive orchards with the aim of generating DSMs representing the tree crowns. Several DSMs created with different forward laps (in intervals of 5–6% from 58 to 97%) were evaluated in order to determine the optimal generation time according to the accuracy of tree crown measurements computed from each DSM. Based on our results, flying at 100 m altitude and with a 95% forward lap reported the best configuration. From the analysis derived from this configuration, tree volume was estimated with 95% accuracy. In addition, computing time was 85% lower in comparison to the maximum overlap studied (97%). It allowed computing the 3D features of 600 trees in a 3-ha parcel in a highly accurate and quick (a few hours after the UAV flights) manner by using a standard computer.