The invention provides a method for structuring a wheat blumeriagraminis speer early detection model by extracting sensitive parameters on the basis of subwindow permutation analysis (SPA). The method comprises the following steps of 1) acquiring the hyperspectral reflectance of an infected wheat; 2) extracting a sensitive wave band from the original wave band of the hyperspectral reflectance through the SPA algorithm; 3) selecting spectral indexes possibly related to diseases in existing research, and extracting sensitive spectral indexes from the spectral indexes through the SPA algorithm; 4) through partial least square-linear discriminant analysis, taking the sensitive wave band or the sensitive spectral indexes as component input variables to structure the wheat blumeriagraminis speer early detection model; 5) testing the wheat blumeriagraminis speer early detection model through the dichotomy algorithm, evaluating model performance through leave-one-out cross validation on the basis of independent susceptible varieties. Therefore, a wheat blumeriagraminis speer sensitive spectrum extracted on the basis of SPA is accurate in characteristic and few in wave bands, and the structured wheat blumeriagraminis speer detection model is simple, high in accuracy and good in stability.

Method for structuring wheat blumeriagraminis speer early detection model by extracting sensitive parameters on basis of subwindow permutation analysis

The invention relates to a whole industry chain information system of rice food, which comprises an information collecting module, an information transmission module, an information processing module, an integrated decision making module, an information storage module, and an information output module The information being information of all links of the whole industry chain of the rice food includes seedling raising information, planting information, warehouse management information, and processing management information All links of the whole industry chain of the rice food consist of a seedling raising link, a planting link, a storage management link, and a processing management link The information transmission module transmits original information collected at the fields of all links of the whole rice food industry chain to a remote monitoring terminal by a communication module in a wired or wireless manner and transmits control information of the remote monitoring terminal to a control terminal by the communication module With the whole industry chain information platform, generation and migration of various hazard factors are monitored and prevented; the foundation is laid for high-efficiency and secure production of the rice food industry chain; a food source tracing effect is realized truly; and whole-course monitoring and on-line detection are realized

Whole industry chain information system of rice food, and establishment method and application thereof

The invention discloses a shooting identification device and method for morphology of microorganisms, and belongs to the field of microbiological detection The device comprises a box body (16), a lighting source (10), a dodging plate (11), an image sensor (12), an image acquisition card (13) and a record identification system (14), wherein the dodging plate (11) is arranged on the inner side of the box body (16), and the lighting source (10) is arranged between the dodging plate (11) and the box body (16); the image sensor (12) is located on the top face of the box body (16), the image sensor (12) is connected with the image acquisition card (13), and the output end of the image acquisition card (13) is connected with the record identification system (14) According to the method, the morphology of the microorganisms is collected, feature extraction and pattern recognition are performed on the obtained microorganism morphological images by means of a computer vision technology, and the microorganisms are identified combined with biochemistry and mass spectrometry The device is simple in structure, convenient to operate, and fast and accurate in identification

Shooting identification device and method for morphology of microorganisms

Embodiments of the invention relate to the technical field of sample classification, and in particular to a material analysis method and device. The method comprises the following steps of: obtaininga shot image comprising a plurality of materials; segmenting the image to obtain a plurality of pictures, wherein each picture comprises a material; respectively processing the pictures to obtain material information corresponding to the pictures; respectively matching the material information with pre-stored normal material models and abnormal material models so as to obtain material models corresponding to the material information; and processing the image according to the material models corresponding to the material models. Through the method, materials in images can be rapidly analyzed and identified.

Material analysis method and device

The invention discloses an automatic screening device of pediatric rickets based on a support vector machine, and a use method thereof, and belongs to the technical field of automatic detection of in vitro diagnostic reagents. The device comprises a base, an upright post, a linear motor, an objective table, a neck, an image collection sensor and a processor, the device can fix to-be-detected serum samples in batches through the objective table, can transfer the samples in batches below the image collection sensor through the linear motor, perform chromogenic spot image collection of the to-be-detected serum samples by using the image collection sensor, and determine an activity range of bone alkaline phosphatase in the processor by using a support vector machine model according to the color features of chromogenic spots. Furthermore, the use method of the device is provided. By adopting the device and the method disclosed by the invention, batch automatic detection of the activity range of the bone alkaline phosphatase of the serum samples can be realized, the adverse influence of subjective judgment of detection personnel, ambient illumination and other factors on the result is avoided, and the accuracy of the detection result and the detection efficiency are improved.

Automatic screening device of pediatric rickets based on support vector machine, and use method thereof

The invention relates to a method for non-destructive identification and distinction of paddy moldy fungal colony based on computer vision technique, and belongs to a novel fungi identification technology. The method includes acquiring an image of fungal colony with a computer vision device, extracting the image parameters after processing the image of fungal colony, optimizing the characteristic parameters, performing analysis of the different fungal colony characteristics by using a mode recognition technique, and reaching identification and distinction of fungi. The method can realize the accurate identification of the fungi spieces, and is rapider, more accurate and convenient than traditional artificial morphology identification and biological identification. The method provides a novel method for fungi identification, and has very important meaning for preventing and controlling the paddy from mildewing.

Method for non-destructive identification of paddy moldy fungal colony

The invention relates to a rice grain mildew test method based on the computer vision technology, and belongs to a novel test technology. Normal (control group), mildew early stage and mildew later stage images are acquired by a computer vision image acquisition device, and the gray features, color features and texture features of the images are extracted after image processing. A test model is built using a support vector machine and partial least squares discriminant analysis. Normal rice grains and mildewed rice grains are distinguished first, and then, different types mildewed rice grains are distinguished. Through the method, whether rice grains are mildewed can be identified accurately, and mildew caused by different funguses can be distinguished accurately. The method is quicker, more accurate and more convenient than traditional manual detection, and is of great important significance to the prevention and control of rice grain mildew.

Rice grain mildew nondestructive test method

Belonging to the technical field of agricultural product nondestructive detection, the invention discloses a bio-speckle technology based method for nondestructive detection of apple internal quality. The method consists of: acquiring an apple speckle image through a constructed bio-speckle measurement device, extracting image characteristic parameters, and determining apple internal quality indexes (hardness and soluble solid) correspondingly, analyzing the correlation between the image characteristic parameters and internal quality, and establishing a speckle image based apple internal quality detection model. The method can detect the internal quality (hardness and soluble solid) of "Gala" apples and "Red Fuji" apples, and grades apple quality according to national standard GB/T 10651-2008. The method provided by the invention is conducive to comprehensive utilization of apples, and is of important significance for increase of China's apple export rate and enhancement of apples' competitiveness on the international market.

Bio-speckle technology based method for nondestructive detection of apple internal quality

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Method for non-destructive identification of paddy moldy fungal colony

Rice grain mildew nondestructive test method

Bio-speckle technology based method for nondestructive detection of apple internal quality