Field monitoring support system for the occurrence of Leptocorisa chinensis Dallas (Hemiptera: Alydidae) using synthetic attractants,Field Servers,and image analysis

To realize effective insect counting in pheromone traps set in remote sites, a remote monitoring and image processing system based on a sensor network system of “Field Servers” has been developed, and two practical methods based on image analysis using this system has been proposed. This system has been employed to monitor the occurrence of the rice bug, Leptocorisa chinensis, in rice paddy fields as a means of reducing the burden of manual insect counting work.A Field Server with a high-resolution digital camera was installed near the pheromone trap for close monitoring. The image data and other monitoring data such as temperature were sent via wireless LAN and the Internet every 5 minutes. A remote management system for the Field Server, located about 7.5 km from the experimental field, managed data collection and analyzed the data to provide useful information on insect count. An image analysis algorithm based on a background differencing technique has been developed to support counting L. chinensis by implementing an image-processing module in the remote management system. The image-processing module provides three analysis functions: cropping, subtracting, and binarizing the target image.One method is to filter extraneous image data containing no observed target insects (end-members) on the pheromone trap. In this method, the difference between collected image data and the reference image data was calculated, and the total number of pixels whose value was greater than a threshold value for the difference result (number of white pixels) was used for filtering. This method managed to maintain Sensitivity at 100% during the experiment. Accuracy was observed to be 89.1% on average. Using this method, the time spent looking at extraneous image data without L. chinensis can be reduced by 85%.The other method for reducing labor in counting involves estimating the number of end-members automatically using a partial image area that is cropped to focus on a low-noise area, permitting easy analysis. With this method, the image data was analyzed using the first method, and the entire number of end-members was estimated using the number of white pixels and a pixel value equivalent to one end-member. The results of this method correspond reasonably closely to the results obtained by manual counting. The correlation coefficient for the daily occurrence rate was 0.974 and that for the hourly rate was 0.916.     

WebGIS县域耕地资源模式化管理系统研究

针对目前大量耕地评价成果资源共享利用、数据更新维护方面存在的问题，提出了基于WebGIS的县城耕地资源模式化管理方案。并以湖北省京山县为例，在Oracle Spatial空间及属性数据一体化管理数据库系统支持下，运用MapXtreme2004组件进行系统开发。经试运行表明，该系统能对耕地资源数据进行有效管理，成果资源的利用率得到了提高，模式化管理方案取得了预期的效果。     

一种基于空间数据仓库的作物信息多维数据模型

空间数据仓库(Spatial Data Warehouse)是GIS技术和数据仓库技术相结合的产物,它大大扩展了GIS的应用功能。本文探讨了空间数据仓库的特征、体系结构、关键技术;并从分析作物数据本身固有的特性出发,建立了基于空间数据仓库的具有多层维度和度量属性的作物信息共享数据模型,解决作物信息共享问题。     

Hardware-based image processing for high-speed inspection of grains

A high-speed, low-cost, image-based sorting device was developed to detect and separate grains having slight color differences or small defects. The device directly combines a complementary metal–oxide–semiconductor (CMOS) color image sensor with a field-programmable gate array (FPGA) which was programmed to execute image processing in real-time, without the need of an external computer. Spatial resolution of the imaging system is approximately 16 pixels/mm. The system includes three image sensor/FPGA combinations placed around the perimeter of a single-file stream of kernels, so that most of the surface of each kernel is be inspected. A vibratory feeder feeds kernels onto an inclined chute that kernels slide down in a single-file manner. Kernels are imaged immediately after dropping off the end of the chute and are diverted by activating an air valve. The system has a throughput rate of approximately 75 kernels/s per channel which is much higher than previously developed image inspection systems. This throughput rate corresponds to an inspection rate of approximately 8 kg/h of wheat and 40 kg/h of popcorn. The system was initially developed to separate white wheat from red wheat, and to remove popcorn having blue-eye damage, which is indicated by a small blue discoloration in the germ of a popcorn kernel. Testing of the system resulted in accuracies of 88% for red wheat and 91% for white wheat. For popcorn, the system achieved 74% accuracy when removing popcorn with blue-eye damage and 91% accuracy at recognizing good popcorn. The sorter should find uses for removing other defects found in grain, such as insect-damaged grain, scab-damaged wheat, and bunted wheat. Parts for the system cost less than $2000, suggesting that it may be economical to run several systems in parallel to keep up with processing plant rates.     

Automatic corn plant location and spacing measurement using laser line-scan technique

Identifying corn plant location and/or spacing is important for predicting yield potential and making decisions for in-season nitrogen application rate. In this study, an automatic corn stalk identification system based on a laser line-scan technique was developed to measure stalk locations during corn mid-growth stages. A laser line-scan technique is advantageous in this application because the line-scan data sets taken from various points of view of a plant stalk results in less interference and higher probability of plant recognition. Data were collected for two 10-meter-long corn rows at the growth stages of V8 and V10 using a mobile test platform in 2011. Each potential stalk cluster was identified in a scan and registered with the same stalks in previous scans. The final location of a stalk was the average of the measured locations in all scans. The current system setup with data processing algorithms achieved 24.0 and 10.0 % of mean total errors in plant counting at the V8 and V10 growth stages, respectively. The root-mean-squared error (RMSE) between system measured plant locations and manually measured ones were 2.3 and 2.6 cm at the V8 and V10 growth stages, respectively. The interplant spacing measured by the developed system had a good correlation with the manual measurement with an R ² of 0.962 and 0.951 for the V8 and V10 growth stages, respectively. This system can be ultimately integrated in a variable-rate-spraying system to improve real-time, high spatial resolution variable-rate nitrogen applications.     

Development of an automated climatic data scraping, filtering and display system

One of the many challenges facing scientists who conduct simulation and analysis of biological systems is the ability to dynamically access spatially referenced climatic, soil and cropland data. Over the past several years, we have developed an Integrated Agricultural Information and Management System (iAIMS), which consists of foundation class climatic, soil and cropland databases. These databases serve as a foundation to develop applications that address different aspects of cropping systems performance and management. In this paper we present the processes and approaches involved in the development of a climatic data system designed to automatically fetch data from different web sources, consolidate the data into a centralized database, and delivery the data through a web-based interface.Climatic data are usually available via web pages or FTP sites. The exact steps to scrape data from different sources vary depending on how the data are rendered. The climatic data building process presented herein is broken down into 5 major program modules, corresponding to different phases of the process: Data Requester, Data Fetcher, Data Parser, Data Filter, and Data Explorer. The Data Requester is responsible for processing the web pages that lead to the determination of the requested weather data. The Data Fetcher is responsible for fetching weather data that is made available by the data sources based on the request from the Data Requester. The Data Parser is responsible for decompressing and parsing the contents of the original data file and saving the data to an SQL Server 2005 database. The Data Filter is responsible for data quality control and for estimating missing data and saving the filtered data. The Data Explorer is designed to provide web-based user access to the consolidated and filtered climatic data using both dropdown lists and map-based navigation.Three types of data are stored in the process: original climatic data in file format, parsed climatic data in SQL Server database, and filtered climatic data in SQL Server database. The resulting consolidated and filtered climatic database provides a common foundation that allows us to develop diversified applications that require dynamic access to near real-time data. A number of applications have been and are being developed that seamlessly access the foundation class climatic database. Collectively these applications address water conservation, crop production and management, land use suitability analysis, and bioenergy refinery site selection.     

Real-time,volatile-detection-assisted control for microwave drying

A real-time, volatile-detection-assisted control system was designed for microwave drying. Detected volatile signals were integrated to a fuzzy logic algorithm to determine the drying temperature. A phase controller was used to automatically and continuously adjust the microwave power. A data acquisition unit with developed program was employed to integrate the entire control. Carrot samples were used in system tests. The results showed that the designed system could successfully achieve the desired temperature, power, and volatiles control and lead to acceptable product's quality.     

Low-cost photochemical reflectance index measurements of micropropagated plantlets using image analysis

A system for imaging the photochemical reflectance index (PRI) of micropropagated plantlet leaves was developed using a low-cost charge-coupled device (CCD) camera. The reflected light intensities of leaves at 530 and 570 nm were imaged using a monochrome CCD camera with respective band-pass filters. The reflection images were used to estimate the PRI values of the leaves. The relationships between the PRI estimated from images and a chlorophyll fluorescence parameter ΔF/Fm′, determined by pulse-amplitude modulation (PAM) chlorophyll fluorometer and representing PSII quantum yield, were investigated for several plants under various conditions to test the performance of the system. The PRI estimated from images decreased with a decline in the ΔF/Fm′ for strawberry leaves treated with high intensity light under artificial light condition and lettuce leaves treated with abscisic acid. These results suggest that the system can be used for non-destructive estimation of the PRI of leaves. The system was used to estimate the PRI of micropropagated potato leaves from outside the culture vessels. The time course of PSII quantum yield for the individual leaf could be demonstrated by the PRI estimated from images of potato plantlet leaves treated with high light. The findings suggest that the system has the potential for inexpensive, simple and efficient estimation of PRI for micropropagated plantlets.     

Development of a yield monitoring system for citrus mechanical harvesting machines

A load cell based yield monitoring system was developed for the Oxbo citrus mechanical harvesting machines. The yield monitoring system consisted of a GPS receiver, a mass flow sensor and data processing and storage units. The mass flow sensor consisted of four load cells attached to a carbon-fiber plate which sensed the impact force created by the oranges hitting the plate. A mathematical model was developed to relate the impact force to fruit mass. Laboratory tests were conducted on a test rig that replicated the flow of oranges to measure the accuracy of the system under a controlled environment. The system performed very well under laboratory conditions (R ² = 0.99 and an average error of 3.3%). In addition, a field test was conducted in a citrus orchard in Florida to evaluate the performance of the system under field conditions. Of the 72 rows used in the field test, the first 10 rows were used to calibrate the computed weight. A correlation of R ² = 0.97 between the actual weight and the computed weight was found from the field data with an average error of 7.81%.     

土壤铅元素快速检测系统的设计及试验

为快速、低成本地获取土壤铅元素含量信息,设计开发一种土壤铅元素快速检测系统。该系统基于阳极溶出伏安法检测原理设计,由土壤铅元素检测仪和上位机数据处理软件组成。土壤铅元素检测仪基于阳极溶出伏安法检测原理设计,以MSP430混合信号处理器为控制核心,集恒电势仪、电流-电压转换放大电路、电源模块为一体,通过RS232串口通信协议与上位机连接。上位机数据处理软件负责向检测仪发送指令和检测参数,并接收检测仪采集到的数据,进行数据分析。使用标准铅离子溶液进行检测试验,结果表明:该土壤铅元素快速检测系统检测得到的溶出峰电流与铅离子浓度具有良好的线性度,相关系数R2=0.995 1。采用该检测系统对取自不同种植区的16个土壤样本的浸提液进行铅离子浓度检测,其检测结果与原子吸收光谱法检测结果的相对误差8%,且具有很好的重复性。该系统能够实现农田土壤铅元素的快速检测。     

A portable soil nitrogen detector based on NIRS

As one of the most important soil nutrient components, soil total nitrogen (TN) content needs to be measured in precision agriculture. A portable soil TN detector based on the 89S52 microcontroller was developed, and a Back Propagation Neural Network (BP-NN) estimation model embedded in the detector was established using near-infrared reflectance spectroscopy with absorbance data at 1550, 1300, 1200, 1100, 1050, and 940 nm wavelengths. The detector consisted of two parts, an optical unit and a control unit. The optical unit included six near-infrared lamp-houses, a shared lamp-house drive circuit, a shared incidence and reflectance Y-type optical fiber, a probe, and a photoelectric sensor. The control unit included an amplifier circuit, a filter circuit, an analog-to-digital converter circuit, an LCD display, and a U-disk storage component. All six absorbance data as inputs were used to calculate soil TN content by means of the estimation model. Finally, the calculated soil TN content was displayed on the LCD display and at the same time stored in the U-disk. A calibration experiment was conducted. The soil TN content correlation coefficient (R ²) of the BP-NN estimation model was 0.88, and the validation R ² was 0.75. This result indicated that the developed detector had a stable performance and a high precision.     

Design of a spatial sampling scheme considering the spatial autocorrelation of crop acreage included in the sampling units

Information on crop acreage is important for formulating national food polices and economic planning.Spatial sampling,a combination of traditional sampling methods and remote sensing and geographic information system(GIS)technology,provides an efficient way to estimate crop acreage at the regional scale.Traditional sampling methods require that the sampling units should be independent of each other,but in practice there is often spatial autocorrelation among crop acreage contained in the sampling units.In this study,using Dehui County in Jilin Province,China,as the study area,we used a thematic crop map derived from Systeme Probatoire d’Observation de la Terre(SPOT-5)imagery,cultivated land plots and digital elevation model data to explore the spatial autocorrelation characteristics among maize and rice acreage included in sampling units of different sizes,and analyzed the effects of different stratification criteria on the level of spatial autocorrelation of the two crop acreages within the sampling units.Moran’s I,a global spatial autocorrelation index,was used to evaluate the spatial autocorrelation among the two crop acreages in this study.The results showed that although the spatial autocorrelation level among maize and rice acreages within the sampling units generally decreased with increasing sampling unit size,there was still a significant spatial autocorrelation among the two crop acreages included in the sampling units(Moran’s I varied from 0.49 to 0.89),irrespective of the sampling unit size.When the sampling unit size was less than3 000 m,the stratification design that used crop planting intensity(CPI)as the stratification criterion,with a stratum number of 5 and a stratum interval of 20%decreased the spatial autocorrelation level to almost zero for the maize and rice area included in sampling units within each stratum.Therefore,the traditional sampling methods can be used to estimate the two crop acreages.Compared with CPI,there was still a strong spatial correlation among the two crop acreages included in the sampling units belonging to each stratum when cultivated land fragmentation and ground slope were used as stratification criterion.As far as the selection of stratification criteria and sampling unit size is concerned,this study provides a basis for formulating a reasonable spatial sampling scheme to estimate crop acreage.     

Development of Insect-Resistant Hybrid Rice by Introgressing the Bt Gene from Bt Rice Huahui 1 into 11-32A/B,a Widely Used Cytogenic Male Sterile System

Huahui 1 is an elite transgenic male sterile restorer line of wild rice abortive-type that expresses a Bacillus thuringiensis （Bt） δ-endotoxin and provides effective and economic control oflepidopteran insects. To exploit Huahui 1 to develop a new Bt rice, the insertion site of the Bt gene was determined by thermal asymmetric interlaced PCR （TAIL-PCR）. Bt was located in the promoter region ofLOC. Os10g10360, approximately 5.35 Mb from the telomere of the short arm of chromosome 10. For the first time, a Bt cytoplasmic male sterile （CMS） system was developed by introgressing Bt from Huahui 1. The recipient CMS system used consisted of Indonesia paddy rice-type II-32B （maintainer line） and II-32A （male sterile line）. Marker-assisted selection was used to increase selection efficiency in the backcrossing program. In BC5F1, the Bt plant 85015-8 was selected for further analyses, as it had the highest SSR marker homozygosity. In addition, the linkage drag of the foreign Bt gene in 85015-8 was minimized to 8.01-11.46 Mb. The foreign Bt gene was then delivered from 85015-8 into II-32A. The resultant Bt II-32A and Bt II-32B lines were both resistant to lepidopteran in field trials, and agronomic traits were not disturbed. The maintainability of II-32B, and the male sterility and general combining ability of II-32A, were not affected by the Bt introgression. This study demonstrates a simple and fast approach to develop Bt hybrid rice.     

XML在林业空间信息发布系统中的应用研究

林业应用中所需的空间信息大都具有格式多样、来源复杂、分布广等特点，造成了用户使用这些空间信息时的巨大困难。本文介绍了一种使用XML描述空间信息并将其发布到网络中以解决上述问题的方法。重点论述了XML在林业空间信息发布系统中的应用，并给出对XML数据的访问实现思路。     

基于ATmega128的温室滴灌施肥控制系统设计

开发了一种以计算机为平台的温室滴灌施肥控制系统,以实现对温室内不同地块间滴灌施肥量的控制.系统以计算机为核心,采用ATmega128单片机作为系统数据采集和处理的内核,以及Digmesa FM系列多液流式液体流量传感器对不同量的液体肥料进行控制,并以VC+ +6.0作为上位软件开发工具,编制了人机交互界面友好的温室滴灌...     

基于SDE的土壤信息系统空间数据库的设计与构建

空间数据引擎是实现空间数据库的核心技术。对空间数据引擎的存储模型进行了对比分析,以重庆市土壤信息空间数据库的构建及其客户端查询软件的开发为例,实现了客户／服务结构下土壤信息空间数据库的管理体系,证明了土壤信息以空间数据库方式管理是可行的。     

空间数据存储器的关键问题研究

空间数据引擎是实现海量空间数据存储和管理的解决方案.随着GIS应用的扩大,多用户并发操作成为空间数据引擎的基本要求.从空间数据存储模型的研究出发,对空间数据存储器的架构、多用户并发控制等关键问题进行阐述,提出了锁和版本并发控制方式.     

A ground-based hyperspectral imaging system for characterizing vegetation spectral features

A cropping system is usually characterized by continuous spatio-temporal vegetation variability. Vegetation variability can be detected by changes in several vegetation parameters defined according to purpose. Estimation of these vegetation parameters has been made possible by calculating various vegetation indices (VIs), usually by ratioing, differencing, ratioing differences and sums, or by forming linear combinations of spectral band data. Spectrometers or sensors have been used to acquire visible and infrared spectral properties of vegetation. This paper presents a ground-based hyperspectral imaging system for characterizing vegetation spectral features. The hyperspectral sensor used was a ground-based line sensor, ImSpector (V10-12-102), with a nominal spectral resolution of 1.5–2 nm and a wavelength range of 360–1010 nm. A graphical user interface (GUI) was developed in a MATLAB environment to aid in processing and analysis of acquired multidimensional spectral image data. Issues that arise when applying the imaging system to a particular field include acquiring hyperspectral images, selecting appropriate vegetation features or VIs, and quantifying the selected vegetation features or indices with the GUI developed. Vegetation features extracted by the proposed imaging system contribute not only to monitoring vegetation variability in crop systems, but also provide a potential source of relevant variables that can be used to estimate various vegetation parameters. A study that was set up to investigate the alternate bearing phenomenon of citrus trees illustrates the basic elements of the proposed approach.     

AFLA-maize,a mechanistic model for Aspergillus flavus infection and aflatoxin B1 contamination in maize

A mechanistic weather-driven model was developed based on the infection cycle of Aspergillus flavus on maize to predict the risk of aflatoxin contamination in field on a daily basis from silk emergence to harvest; hourly data of temperature, relative humidity and rain were used as model input. The work was done in four steps: (i) development of the model prototype; (ii) collection of Italian field data on aflatoxin contamination in maize with related crop and weather data; (iii) development of a probability index to exceed the legal limit of 5 μg of aflatoxin B₁ per kg of unprocessed maize by combining model predictions and field data in a logistic regression; and (iv) validation with Italian data of the probability index and release of the predictive model, named AFLA-maize. Predictions of maize contamination above the threshold of 5 μg/kg in the data set used for parameterization of the regression equation were correct for 73% of field samples; 59% and 14%, respectively, were not contaminated and contaminated. In a second independent data set, 68% of samples were correctly predicted. The model AFLA-maize provides prediction of A. flavus infection and aflatoxin contamination along the growing season and at harvest. This information is useful to support decision-making for (i) crop management, (ii) harvest timing, (iii) maize lots cleaning and logistic, and (iv) maize sampling for aflatoxin analysis at consignment.