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1.
Joe-Air Jiang Hsiang-Yun Chang Ke-Han Wu Cheng-Shiou Ouyang Man-Miao Yang En-Cheng Yang Tse-Wei Chen Ta-Te Lin 《Computers and Electronics in Agriculture》2008,60(2):190-200
Although X-ray scanners are commonly used in airports or customs for security inspection, practical application of X-ray imaging in quarantine inspection to prevent propagation of alien insect pests in imported fruits is still unavailable. The first step to identify insect infestation in fruit by X-ray imaging technique is image acquisition. This is followed by the image segmentation procedure, which can locate sites of infestation. Since the grey level of X-ray images depends on the density and thickness of the test samples, the relative contrast of infestation site to the intact region inside a typical fruit varies with its position. To accurately determine whether a fruit has signs of insect infestation, we have developed an adaptive image segmentation algorithm based on the local pixels intensities and unsupervised thresholding algorithm. This paper presents the detailed image processing procedure including the grid formation, local thresholding, threshold value interpolation, background removal, and morphological filtering for the determination of infestation sites of a fruit in X-ray image. The real-time image processing procedure was tested with X-ray images of several types of fruit such as citrus, peach, guava, etc. Additional tests and analyses were also performed using the developed algorithm on the X-ray images obtained with different image acquisition parameters. 相似文献
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ZHANG Gui-fen MA De-ying WANG Yu-sheng GAO You-hua LIU Wan-xue ZHANG Rong FU Wen-jun XIAN Xiao-qing WANG Jun KUANG Meng WAN Fang-hao 《农业科学学报》2020,19(7):1912-1917
Tuta absoluta (Meyrick) originated in South America and is one of the most serious pests of tomatoes. It is also known to attack other solanaceous crops, including potato, eggplant, pepper, tobacco, and weedy species such as black nightshade. After accidental introduction into Spain in 2006, this pest spread rapidly throughout Afro-Eurasia and has become a major threat to tomato production worldwide. Here, we report the first record of T. absoluta as an invasive pest in China. It was found in tomato fields in Ili Kazakg Autonomous Prefecture, Xinjiang Uygur Autonomous Region (Ili, Xinjiang), China, and its occurrence was confirmed by both morphological and molecular approaches. In Ili, T. absoluta has been found to attack eggplant, potato, and black nightshade. We found the larvae generally mining and feeding on leaves and boring into tomato fruits, with multiple larvae sometimes observed in a single fruit. Its infestation levels differ among the tomato fields and host species. In all of the surveyed tomato fields, T. absoluta infested 100% of plants. In some of the fields, up to 90% of the eggplant and 100% of the potato plants were infested. Since no natural enemies were found under field conditions, suitable management practices are urgently needed to stop the further spread of this destructive pest in China. 相似文献
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Line-scan hyperspectral imaging system for real-time inspection of poultry carcasses with fecal material and ingesta 总被引：1，自引：0，他引：1
Seung Chul Yoon Bosoon ParkKurt C. Lawrence William R. WindhamGerald W. Heitschmidt 《Computers and Electronics in Agriculture》2011,79(2):159-168
In poultry processing plants, fecal material and ingesta are the primary source of carcass contamination with microbial pathogens. The current practice of the poultry inspection in the United States is primarily human visual observations. Since the visual inspection is becoming more challenging in poultry processing plants adopting high-speed lines, a rapid sorting system could significantly improve the detection and monitoring of carcasses with surface fecal material and ingesta. As a result, we developed a prototype line-scan hyperspectral imaging system configured as a real-time multispectral imaging subsystem for online detection of surface fecal material and ingesta. Specifically, we integrated a commercially available off-the-shelf hyperspectral image camera into the system with two line lights and a custom software program for real-time multispectral imaging. The bottleneck of the imaging system was the data acquisition. For that reason, a multithreaded software architecture was designed and implemented not only to meet the application requirements such as speed and detection accuracy, but also to be customizable to different imaging applications such as systemic disease detection in the future. The image acquisition and processing speed tests confirmed the system could operate to scan poultry carcasses in commercial poultry processing plants. The fecal detection algorithm was based on the previous research using different hyperspectral imaging systems. A new carcass detection and image formation algorithm was developed to allow existing image processing and detection algorithms reusable without any modifications. Sixteen chicken carcasses and four different types of fecal and ingesta samples were used in a study to test the imaging system at two different speeds (140 birds per minute and 180 birds per minute) in a pilot-scale poultry processing facility. The study found that the system could grab and process three waveband images of carcasses moving up to 180 birds per minute (a line-scan rate 286 Hz) and detect fecal material and ingesta on their surfaces. The detection accuracy of the system varied between 89% and 98% with minimum false positive errors (less than 1%), depending on tested detection algorithms. Therefore, these findings provide the basis of not only a commercially viable imaging platform for fecal detection but also a single poultry inspection system for multiple tasks such as systemic disease detection and quality sorting. 相似文献
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自然光照条件下苹果识别方法对比研究 总被引：1，自引：0，他引：1
针对自然光照条件下果园苹果识别效果不佳的问题,从苹果的颜色分割和形状提取2方面进行对比研究,提出一种自然光照条件下的苹果识别方法。利用错检率、漏检率和处理速度3个量化指标综合对比分析颜色阈值、SVM和BPNN 3种苹果颜色分割方法的处理效果。比较6种边缘检测算法对苹果区域图像的边缘检测效果,并使用Hough圆检测算法对苹果形状进行提取,以获得苹果的圆心和半径。试验结果表明:由BPNN的苹果颜色分割方法以及结合Log和Hough的苹果形状提取方法所构建的果实识别算法具有较高的鲁棒性和准确性,能有效克服果实遮挡、重叠和颜色变异等问题,果实平均识别率可达91.6%。 相似文献
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S. Cubero N. Aleixos F. Albert A. Torregrosa C. Ortiz O. García-Navarrete J. Blasco 《Precision Agriculture》2014,15(1):80-94
The mechanisation and automation of citrus harvesting is considered to be one of the best options to reduce production costs. Computer vision technology has been shown to be a useful tool for fresh fruit and vegetable inspection, and is currently used in post-harvest fruit and vegetable automated grading systems in packing houses. Although computer vision technology has been used in some harvesting robots, it is not commonly utilised in fruit grading during harvesting due to the difficulties involved in adapting it to field conditions. Carrying out fruit inspection before arrival at the packing lines could offer many advantages, such as having an accurate fruit assessment in order to decide among different fruit treatments or savings in the cost of transport and marketing non-commercial fruit. This work presents a computer vision system, mounted on a mobile platform where workers place the harvested fruits, that was specially designed for sorting fruit in the field. Due to the specific field conditions, an efficient and robust lighting system, very low-power image acquisition and processing hardware, and a reduced inspection chamber had to be developed. The equipment is capable of analysing fruit colour and size at a speed of eight fruits per second. The algorithms developed achieved prediction accuracy with an R2 coefficient of 0.993 for size estimation and an R2 coefficient of 0.918 for the colour index. 相似文献
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《Computers and Electronics in Agriculture》2009,65(2):194-201
Different measurement modes, reflectance and transmittance, were compared for their ability to identify the internal insect infestation in tart cherry (c.v. Montomorency) using visible and near infrared spectroscopy. The cherries were collected in the summers of 2004, 2005, 2006 and 2007 from different orchards in Michigan. The samples included intact (Level 0) as well as infested cherries with different damage levels (Levels 1–5). The spectra were recorded for whole cherries with a spectroradiometer within a wavelength region between 550 and 950 nm. MANOVA analysis indicates that the spectral data, both of the transmittance or reflectance, basically falls into three clusters, showing that the intact cherries and the cherries with Level 1 infestation (slightly infested) are in one cluster; Samples with infestation degree from Levels 3 to 5 (seriously infested) are clearly distinguishable from the intact and slight infested samples; the cherries with Level 2 infestation degree are scattered in between the intact and serious infested samples. According to the results of the discriminant analysis, transmittance works slightly better than reflectance in terms of the total classification accuracy. Spectroscopic technology should provide the cherry industry with a valuable tool for rapidly detecting insect infestation in tart cherry. 相似文献
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以福建沙县为研究区,以SPOT-5影像为数据源,采用灰度共生矩阵方法提取健康林分与受害林分的纹理特征,构建最佳纹理量,分别采用像元统计和面向对象的方法进行虫害信息提取,结果精度分别为72.00%、74.75%。研究结果证明了利用遥感影像纹理特征进行马尾松毛虫害监测的可行性,为利用融合影像光谱信息与纹理信息进行虫害信息提取研究提供了实例支撑和技术参考,同时面向对象的方法优于传统的基于像元统计的分类方法,精度稍高,"椒盐现象"也有所改善。 相似文献
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黄椋子树是重要的木本油料之一。黄椋种子小蜂是晋东南黄椋子产区的毁灭性害虫,幼虫于种实内食害种仁,致成空壳,被害果较正常健果小呈粉红至褐色,健果墨绿色。从1959年以来由于连年受其为害,几乎无好种实可收,造成当地人民食油困难。作者对其形态、生活史及习性作了系统观察研究,绘制了形态图。并开展了大面积防治示范,收到良好的效果。以老熟幼虫于被害种实内滞育越冬,多数一年1代,部分可滞育1-2年。5月中旬至6月上旬为化蛹期,蛹期7-12天。成虫出种实后2-3天开始交配产卵;雌雄比3-4:1;卵产于幼果内,每果只产1粒卵,卵期5-7天。幼虫8月中旬至9月上旬老熟越冬。采用农业、人工和药剂相结合的综合防治措施,收到良好效果。5月底成虫始发期地面施用触杀剂,毒杀成虫效果很好。 相似文献
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果蔬重要实蝇属的分布、危害与形态特征比较研究 总被引：3，自引：3，他引：0
阐述了果实蝇属、寡鬃实蝇属、小条实蝇属、按实蝇属、绕实蝇属5个检疫性害虫果蔬实蝇属的地理分布、寄主及其主要形态特征,比较了各个属形态特征的异同,并提出了一些防治果蔬重要实蝇属的措施。 相似文献
10.
The length of the rice panicle determines the number of grains it can hold, and consequently rice yield; it is therefore one of the most important traits assessed in yield-related research. However, the conventional method of measuring panicle length is still a manual process that is inconsistent, subjective and slow. In this study, a novel prototype, dubbed “Smart-PL”, was developed for the automatic measurement of rice panicle length based on dual-camera imaging. Cameras with a long-focus lens and a short-focus lens were utilized to capture both a detailed image and a complete image of the rice panicle, respectively. Specific image processing algorithms were exploited, to analyze the neck image for neck identification and the whole-panicle image for path extraction. Subsequently, co-registration was used to identify the neck location in the whole-panicle image, and a resampling method was used to search for the path points between the panicle neck and the tip. Finally, the panicle length was calculated as the sum of the distances between each adjacent path point. To evaluate the accuracy of this prototype, six batches of rice panicles were tested. The results showed that the mean absolute percentage error (MAPE) for the system was about 1.23%, and the automatic measurements had a good agreement with manual measurements, regardless of panicle type. To evaluate the efficiency of this prototype, 3108 panicle samples were tested under continuous-measurement conditions, and the measuring efficiency was approximately 900 panicles per hour, 6 times over manual method. In conclusion, the system automatically extracts panicle length while providing three advantages over the manual method: objectiveness, high efficiency and high consistency. 相似文献
11.
Luis O. Solis-Sánchez Rodrigo Castañeda-Miranda Juan J. García-EscalanteIrineo Torres-Pacheco Ramón G. Guevara-GonzálezCelina L. Castañeda-Miranda Pedro D. Alaniz-Lumbreras 《Computers and Electronics in Agriculture》2011,75(1):92-99
One of the main problems in greenhouse crop production is the presence of pests. In order to address this problem, the implementation of a Integrated Pest Management (IPM) system involving the detection and classification of insects (pests) is essential for intensive production systems. Traditionally, this has been done by placing hunting traps in fields or greenhouses and later manually counting and identifying the insects found. This is a very time-consuming and expensive process. To facilitate this process, it is possible to use machine vision techniques. This work describes an application of the machine vision system LOSS V2 algorithm, an expanded version of the LOSS algorithm discussed in a previous work by the same authors. This expanded version demonstrated improved potential and was used to detect and identify the following pest species: Diabrotica (Coleoptera: Chrysomelidae), Lacewings (Lacewings spp.), Aphids (Aphis gossypii Genn.), Glassy (Empoasca spp.), Thrips (Thrips tabaci L.), and Whitefly (Bemisia tabaci Genn.). The algorithm identifies pest presence in the crop and makes it possible for the greenhouse manager to take the appropriate preventive or corrective measures. The LOSS V2 involves the application of the LOSS algorithm for initial pest identification, followed by the application of the image processing technique known as scale invariant feature transform (SIFT). This allows for more accurate pest detection because it is possible to discriminate and identify different types of insects. Therefore, when compared to manual pest counting, the newly developed LOSS V2 algorithm showed more precision in identifying different pest varieties, and also, a much higher determination coefficient, R2 = 0.99. 相似文献
12.
分瓣臀凹盾蚧Phenacaspis kentiae Kuwana防治指标的研究 总被引：3，自引：0，他引：3
本文报道了茶花分瓣臀凹盾蚧 Phenacaspis kentiae Kuwana 防治指标的研究结果。防治指标的确定,是害虫综合防治的重要环节。经过两年来的研究,根据蚧虫在叶片上的虫口密度与茶花叶片枯黄、枯枝、高生长以及被害茶花的经济损失等关系,确定该虫的防治指标为5头/叶。经在大理洱海公园、昆明昙华寺公园的实践,在生产上是可行的。 相似文献
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入侵害虫红脂大小蠹的研究进展 总被引：3，自引：0，他引：3
红脂大小蠹是我国近年来重要的入侵害虫。对红脂大小蠹的研究进展进行综述,提出加强检验检疫技术研究,防止扩散;加大信息素、天敌等生物因子的应用和科学育林等林业管理措施。 相似文献
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Development of an automatic monitoring system for rice light-trap pests based on machine vision 
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下载免费PDF全文 YAO Qing FENG Jin TANG Jian XU Wei-gen ZHU Xu-hua YANG Bao-jun Lü Jun XIE Yi-ze YAO Bo WU Shu-zhen KUAI Nai-yang WANG Li-jun 《农业科学学报》2020,19(10):2500-2513
Monitoring pest populations in paddy fields is important to effectively implement integrated pest management. Light traps are widely used to monitor field pests all over the world. Most conventional light traps still involve manual identification of target pests from lots of trapped insects, which is time-consuming, labor-intensive and error-prone, especially in pest peak periods. In this paper, we developed an automatic monitoring system for rice light-trap pests based on machine vision. This system is composed of an intelligent light trap, a computer or mobile phone client platform and a cloud server. The light trap firstly traps, kills and disperses insects, then collects images of trapped insects and sends each image to the cloud server. Five target pests in images are automatically identified and counted by pest identification models loaded in the server. To avoid light-trap insects piling up, a vibration plate and a moving rotation conveyor belt are adopted to disperse these trapped insects. There was a close correlation(r=0.92) between our automatic and manual identification methods based on the daily pest number of one-year images from one light trap. Field experiments demonstrated the effectiveness and accuracy of our automatic light trap monitoring system. 相似文献
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张可池 《福建农林大学学报(自然科学版)》1992,(2)
橄榄皮细蛾(Spulerina sp.)在福州1a发生4代,平均各代历期:第1代45d,第2代31d,第3代46.5d,越冬代近8个月.以预蛹期幼虫在橄榄秋梢嫩茎和复叶叶轴的基部至中部上吐丝结茧越冬.越冬代成虫于5月初羽化.第1代幼虫为害春梢;第2代主要为害果实;第3代为害夏梢;第4代(越冬代)为害秋梢.其中以第2代幼虫潜食橄榄幼果所造成的经济危害最大.此虫在果上发育1个世代,其各虫态历期平均为:卵期7d,幼虫期19.5d,蛹期3.5d,雌蛾产卵前期1d.5月中旬至下旬为橄榄座果期和春梢生长期,是防治橄榄皮细蛾保果的关键时期.用特制杀虫粉炮(中国专利号90204382·X)每株大树放炮1粒,3d后重复1次,保果效果达95.22％. 相似文献
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《农业科学学报》2014,13(11):2460-2470
The rice leaffolder (RLF), Cnaphalocrocis medinalis Guenée (Lepidoptera: Pyralidae), and the white-backed rice planthopper (WBPH), Sogatella furcifera Horváth (Hemiptera: Delphacidae), are major insect pests in China and several other Asian countries. These two pests commonly occur simultaneously or in a temporal sequence. Thus, the investigation of the effect of complex infestations or temporal sequence infestations by these pests on rice yield has a practical significance for the control of these pests. The present study comprised experiments with the following four different variables in potted rice at the tillering stage: single pest species infestation, complex infestation, complete combination infestation and temporal sequence infestation (C. medinalis infestation prior to S. furcifera and S. furcifera infestation prior to C. medinalis). The results showed that the four infestations resulted in a significant decrease in 1000-grain weight (1000GW) and rate of yield loss (RYL) but an increase in blighted grain rate (BGR), with a significant positive correlation with the infestation density. However, the influences of the complex infestation, complete combination infestation or sequence infestation on the 1000GW, BGR and RYL were greater than those of the single pest species infestations but did not have addition effects, i.e., the effects of the complex infestation and combination infestation or sequence infestation on the 1000GW, BGR and RYL were less than the additive effects of the two single pest species infestations at the same densities. In the condition of the same total infestation pressure, no significant differences in the 1000GW, BGR and RYL were found between C. medinalis infestation prior to S. furcifera and S. furcifera infestation prior to C. medinalis as well as between the sequence infestation and the complex infestation. 相似文献