Improving soil property maps for precision agriculture in the presence of outliers using covariates

Precision Agriculture - This study aimed to evaluate the use of multiple covariates in robust geostatistical modeling of soil chemical properties characterized by the presence of outliers....     

Stereo vision three-dimensional terrain maps for precision agriculture

The combined interest in precision agriculture, information technology, and autonomous navigation has led to a growing interest in the generation of 3D maps of mobile equipment surroundings. This article proposes a method to create 3D terrain maps by combining the information captured with a stereo camera, a localization sensor, and an inertial measurement unit, all installed on a mobile equipment platform. The perception engine comprises a compact stereo camera that captures field scenes and generates 3D point clouds, which are transformed to geodetic coordinates and assembled in a global field map. The results showed that stereo perception can provide the level of detail and accuracy needed in the construction of 3D field maps for precision agriculture and field robotics applications.     

Adaptation of regional digital soil mapping for precision agriculture

In the initial phase of a national project to map clay, sand and soil organic matter (SOM) content in arable topsoil in Sweden, a study area in south-west Sweden comprising about 100 000 ha of arable land was assessed. Models were created for texture, SOM and two estimated variables for lime requirement determination (target pH and buffering capacity), using a data mining method (multivariate adaptive regression splines). Two existing reference soil datasets were used: a grid dataset and a dataset created for individual farms. The predictor data were of three types: airborne gamma-ray spectrometry data, digital elevation from airborne laser scanning, and legacy data on Quaternary geology. Validations were designed to suit applicability assessments of prediction maps for precision agriculture. The predictor data proved applicable for regional mapping of topsoil texture at 50 × 50 m² spatial resolution (root mean square error: clay = 6.5 %; sand = 13.2 %). A novel modelling strategy, ‘Farm Interactive’, in which soil analysis data for individual farms were added to the regional data, and given extra weight, improved the map locally. SOM models were less satisfactory. Variable-rate application files for liming created from derived digital soil maps and locally interpolated soil data were compared with ‘ground truth’ maps created by proximal sensors on one test farm. The Farm Interactive methodology generated the best predictions and was deemed suitable for adaptation of regional digital soil maps for precision agricultural purposes.     

Imaging the electrical conductivity of the soil profile and its relationships to soil water patterns and drainage characteristics

Soil water content (θ) measurement is vital for accurate irrigation scheduling. Electromagnetic induction surveys can be used to map spatial variability of θ when other soil properties are uniform. However, depth-specific θ variations, essential for precision irrigation management, have been less investigated using this method. A quasi-2-dimensional inversion model, capable of inverting apparent soil electrical conductivity (EC_a) data to calculate estimates of true electrical conductivity (σ) down the entire soil profile, was developed using EC_a data collected by a multi-coil Dualem-421S sensor. The optimal relationships between σ and volumetric water content (θv) were established using all coil arrays of the Dualem-421S, a damping factor of 0.04, an initial model of 35 mSm^?1, and with ten iterations (R²?=?0.70, bias?=?0.00 cm³cm^?3, RMSE?=?0.04 cm³cm^?3). These relationships were then used to derive soil profile images of these properties, and as expected, θv and σ follow similar trends down the soil profile. The derived soil profile images for θv have potential use for irrigation scheduling to two EC_a-derived soil management zones under a variable rate irrigation system at this case study site. They reflect the intrinsic soil differences that occur between texture, texture transitions and drainage characteristics. The method can also be used to guide placement of soil moisture sensors for in-season monitoring of spatio-temporal variations of θv. This soil imaging method showed good potential for predicting 2D depth profiles of soil texture, moisture and drainage characteristics, and supporting soil, plant and irrigation management.

     

便携式土壤电导率测试系统的开发

介绍了一种自行设计的，基于电流-电压四端法的便携式土壤电导率(EC)在线测试仪的开发情况。该测试仪包括土壤电导率传感器、控制与数据采集器和计算机应用软件等。传感器有4个电极，2个用于向土壤中输入恒流，另外2个用于检测与土壤电导率密切相关的电压降；控制与数据采集器把传感器产生的电压信号转换为数字信号，计算并显示电导率；计算机应用软件把接收到的数据存入Microsoft Access数据库。在实验室土槽内对该测试仪传感器的性能进行了测试，并与电导率仪测量结果进行了比较分析。结果表明，传感器输出电压与电导率仪测量值变化趋势一致，采用多种非线性数学模型对各组数据进行了曲线拟合，结果均在幂函数模型上获得最佳回归，测定系数(R^2)大于0．99。     

支持精确农业的土壤养分空间分布信息处理的方法

为了获取支持精确农业的农田空间分布信息,扼要介绍了土壤特性空间变异的影响因素,分析了农田土壤的合理采样方法及其特性空间变异的研究方法,并对影响生成土壤特性空间分布图的因素做了介绍.     

Comparing temperature correction models for soil electrical conductivity measurement

There are various factors that affect soil electrical conductivity (EC) measurements, including soil texture, soil water content, cation exchange capacity (CEC) and others. Temperature is an important environmental variable, and different models can be used to correct for its effect on EC measurements and standardize the measurements to 25°C. It is relevant to analyze these models and to determine whether they are consistent with each other. Some models were wrongly cited. We found that the exponential model of Sheets and Hendrickx as corrected by Corwin and Lesch in 2005 performs the best. The ratio model also performs well between 3°C and 47°C.     

Soil apparent electrical conductivity and geographically weighted regression for mapping soil

To resolve the spatial variation in soil properties intensively is expensive, but such knowledge is essential to manage the soil better and to achieve greater economic and environmental benefits. The objective of this study was to determine whether the soil apparent electrical conductivity (EC_a), alone or combined with other variables, is a useful alternative for providing detailed information on the soil in the Extremadura region of Spain. Apparent soil electrical conductivity was measured and geographically weighted regression was used to characterize the spatial variation in soil properties, which in turn can be used for soil management. This study shows that soil cation exchange capacity, calcium content, clay percentage and pH have a relatively strong spatial correlation with EC_a in the soil of the study area.     

Mobile TDR for geo-referenced measurement of soil water content and electrical conductivity

The development of site-specific crop management is constrained by the availability of sensors for monitoring important soil and crop related conditions. A mobile time-domain reflectometry (TDR) unit for geo-referenced soil measurements has been developed and used for detailed mapping of soil water content and electrical conductivity within two research fields. Measurements made during the early or late season, when soil moisture levels are close to field capacity, are related to the amount of plant available water and soil texture. Combined measurements of water content and electrical conductivity are closely related to the clay and silt fractions of a variable field. The application to early season field mapping of water content, electrical conductivity and clay content is presented. The water and clay content maps are to be used for automated delineation of field management units. Based on a spatial analysis of the soil water measurements, recommendations are made with respect to sampling strategies. Depending on the variability of a given area, between 15 and 30 ha can be mapped with respect to soil moisture and electrical conductivity with sufficient detail within 8 h.     

Soil electrical conductivity as a function of soil water content and implications for soil mapping

Apparent soil electrical conductivity (EC_a) has shown promise as a soil survey tool in the Midwestern United States, with a share of this interest coming from the precision agriculture community. To fully utilize the potential of EC_a to map soils, a better understanding of temporal changes in EC_a is needed. Therefore, this study was undertaken to compare temporal changes in soil EC_a between different soils, to investigate the influence of changes in soil water content on soil EC_a, and to explore the impacts these EC_a changes might have on soil mapping applications. To this end, a 90 m long transect was established. Soil EC_a readings were taken in the vertical and horizontal dipoles at five points once every one to two weeks from June until October in 1999 and 2000. At the same time, soil samples were collected to a depth of 0.9 m for volumetric soil water content analysis. Soil EC_a readings were compared to soil water content. At four of the five sites linear regression analysis yielded r ² values of 0.70 or higher. Regression line slopes tended to be greater in lower landscape positions indicating greater EC_a changes with a given change in soil water content. Two of the soils had an EC_a relationship that changed as the soils became dry. This is an item of concern if EC_a is to be used in soil mapping. Results indicated that soil water content has a strong influence on the EC_a of these soils, and that EC_a has its greatest potential to differentiate between soils when the soils are moist. Soil water content is an important variable to know when conducting EC_a surveys and should be recorded as a part of any report on EC_a studies.     

一种多点土壤电导率实时监测系统的研制

为获取建立溶质运移模型所需的土壤溶质浓度参数,根据土壤溶液电导率与溶液浓度c的线性关系,应用电流电压四端法,研制出一种多点土壤电导率实时监测系统。该系统硬件部分自行设计的四针微型探头可减小对溶质运移的扰动,且可高密度分布在土壤中;连接8路电导率探头和1路温度探头的高精度数据采集器DAB能够实现8通道土壤电导率测量及温度辅助测量,并可通过485总线接口实现系统规模的扩展。采用VC开发的监测显示平台能够完成采集器参数设置,数据采集、显示与存储功能。通过对采集器通道和探头的标定,有效解决了多点土壤电导率实时监测的一致性问题。标定试验结果表明,数据采集器8通道电导测量值与标准电导的相关系数为0.999 5,表明通道标定后有效提高了其测量准确度,减小了各通道测量差异;通道标定后采集器各通道测量的标准溶液电导G与其电导率σ具有良好的线性关系,但不同电导率条件下探头的测量结果存在较为明显的偏差,说明探头制作过程引起的结构差异不可忽略,进而采用分段标定方法对每一个探头的结构常数进行标定。     

Calculation of soil electrical conductivity using a genetic algorithm

The aim of this paper is to present an optimization methodology based on a genetic algorithm to obtain the soil electrical conductivity and its respective thicknesses. The method uses an experimental conductivity curve generated from the measurements made in the soil. This experimental curve is compared with a theoretical electrical conductivity curve produced by a genetic algorithm. The theoretical curve is based on Sunde’s algorithm and is exactly the inverse process of soil horizontal stratification into multi layers. The comparison between the two curves provides the error produced by the soil stratification process. Using the obtained values of electrical conductivity, the method intends to estimate characteristics such as water content, texture and salinity of the subsoil layers.     

Spatial patterns of soil microbial communities and implications for precision soil management at the field scale

Precision Agriculture - Understanding the spatial patterns of soil microbial communities and influencing factors is a prerequisite for soil health assessments and site-specific management to...     

不同降雨强度下剖面土壤电导率的空间变异研究

应用传统统计学和地统计学方法,分析了重庆市中梁山坡耕地土壤电导率在无雨尧小雨、中雨和大雨4种降雨强度下的空间分布特征,并分析了不同降雨强度下土壤电导率与相关参数的相关性。结果表明：在一定条件下袁土壤孔隙水电导率和土壤含水率是影响土壤电导率的主要因素;土壤电导率具有明显空间变异性,不同降雨强度下同一土层电导率差异显著,不同土层间土壤电导率差异显著;对不同降雨强度下土壤电导率的变异函数理论模型拟合精度较高,无雨条件下,土壤电导率空间具有中等或强烈空间相关性,自相关域最大,不同降雨强度下0~10cm土层土壤电导率结构比为0,10~30、30~50 cm土层结构比均有不同程度下降。     

不同土地利用方式对土壤含水量、pH值及电导率的影响

以林芝地区八一镇5种植被类型下土壤为研究对象,研究其土壤剖面(0—50 cm)的含水量、pH值及电导率分布特征。结果表明,土地利用方式影响了土壤含水量、pH值和电导率在垂直剖面上的空间分布,尤其以表层(0—20 cm)土壤含水量和电导率受影响最为明显。草地土壤含水量表现出明显的“表聚”效应,即随着土层加深,含水量呈降低趋势。在区域空间上,土壤含水量和电导率具有较强的空间变异性,而土壤pH值的空间变异性较小。随着土层加深,各层土壤含水量和电导率之间的变异性逐渐减小。     

Adoption of precision agriculture technologies by German crop farmers

In recent years, precision farming has been receiving more attention from researchers. Precision farming, which provides a holistic system approach, helps farmers to manage the spatial and temporal crop and soil variability within a field in order to increase profitability, optimize yield and quality, and reduce costs. There has been considerable research in farmers’ adoption of precision agriculture technologies. However, most recent studies have considered only a few aspects, whereas in this study a wide range of farm characteristics and farmer demographics are tested to gain insight into the relevant aspects of adoption of precision farming in German crop farming. The results of a logistic regression analysis show that predictors with positive influence on the adoption of precision farming are agricultural contractor services such as an additional farming business, having under 5 years’ experience in crop farming, having between 16 and 20 years’ experience in crop farming, and having more than 500 ha of arable land. However, having a farm of less than 100 ha and producing barley are factors that exert a negative influence on the adoption of precision farming. The results of this study provide manifold starting points for the further proliferation of precision agriculture technologies and future research directions.     

Evaluation of vegetation indices and apparent soil electrical conductivity for site-specific vineyard management in Chile

Spatial variability of Chilean vineyards, in terms of yield and quality, is high, which fully justifies site-specific management, particularly differential harvest. In this study, the most common zoning tools (NDVI and ECa measurements) were evaluated and compared. Comparisons also included a calibrated GVI. Two contrasting large field experiments (pruning, irrigation, and N fertilization treatments) were established in vineyards to (1) evaluate two vegetation indices: (i) a non-calibrated airplane-based NDVI and (ii) calibrated satellite-based GVI and to (2) evaluate the ECa measurements. The GVI was also assessed at the commercial level, in different vineyards and valleys. The GVI was more sensitive in discriminating grape yields and quality while the NDVI failed to adequately sense vigor patterns and fruit quality in the more homogeneous site. Thus, a calibrated GVI can be recommended as a better tool than NDVI for defining management zones as well as making spatial and temporal comparisons among fields and seasons. In general, ECa explained few differences in the alluvial soil properties and did not predict differences in plant vigor as measured by either vegetation indices, therefore ECa by itself was not a good estimator of the most commonly measured soil properties for establishing management zones in these fields with low variability in terms of EC and other soil characteristics.     

中国农业的发展与精确农业技术体系

介绍了精确农业技术体系的基本内容，论述了我国作为农业大国研究和发展精确农业高新技术的必要性；讨论了我国发展精确农业应注意的几个问题及开发推广精确农业技术的对策。     

Methodology and tools for analyzing on-site data in precision agriculture

It is suggested to use all possible statistical analysis methods and then a comparative analysis of the results to increase the reliability of management decisions in precision agriculture.     

Adaptive modeling and control of a manure spreader for precision agriculture

This paper describes a general modeling and control approach for automating various agricultural machines for precision farming applications. Experimental validation of control designs was performed on a modified New Holland manure spreader. An adaptive numerical modeling approach for describing the system input–output dynamics is proposed, and an optimal control that accounts for the control hardware limits is developed. Field tests have demonstrated the effectiveness of the theoretical development.