Comprehensive evaluation method of quality of agricultural products

A technology for comprehensive evaluation and agricultural products, applied in measurement devices, material analysis by optical means, instruments, etc., can solve problems such as one-sided evaluation results

Active Publication Date: 2016-06-15
尼尔软科(北京)科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, even in developed countries, only sugar content is used as the only evaluation index for fruit grading, and the evaluation results are one-sided

Method used

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  • Comprehensive evaluation method of quality of agricultural products
  • Comprehensive evaluation method of quality of agricultural products
  • Comprehensive evaluation method of quality of agricultural products

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0126] Taking the apples grown under the same conditions and harvested at the same time as the samples to be tested, the comprehensive evaluation and grading shall be carried out according to the following methods:

[0127] (1) Determine the evaluation index as sugar content, acidity, hardness and sugar-acid ratio, and set the weight coefficients of each evaluation index as K 糖度 =0.6, K 酸度 =0.3, K 硬度 =0.07, K 糖酸比 =0.03;

[0128] (2) Use the checkerboard method to select typical apple samples of the same variety with the same planting environment as the samples to be tested as the training set samples. There are 375 samples in the training set, accounting for 5% of the number of samples to be tested. The near-infrared absorption spectrum data is the independent variable, and the evaluation value of each evaluation index is the dependent variable. The partial least squares regression algorithm is used for regression operation, and the near-infrared absorption spectrum quantit...

Embodiment 2

[0154] Take the pears grown under the same conditions and harvested at the same time as the samples to be tested, and carry out comprehensive evaluation and grading according to the following methods:

[0155] (1) Determine the evaluation index as sugar content, acidity, hardness and sugar-acid ratio, and set the weight coefficients of each evaluation index as K 糖度 =0.5, K 酸度 =0.3, K 硬度 =0.1, K 糖酸比 = 0.1;

[0156] (2) Using the checkerboard method to select typical pear samples of the same variety with the same planting environment as the sample to be tested as the training set sample, there are 150 training set samples, accounting for 4% of the number of samples to be tested, taking the training set sample The near-infrared absorption spectrum data is the independent variable, and the evaluation value of each evaluation index is the dependent variable. The partial least squares regression algorithm is used for regression operation, and the near-infrared absorption spectrum...

Embodiment 3

[0182] The peaches grown under the same conditions and harvested at the same time were used as samples to be tested, and the comprehensive evaluation and grading were carried out according to the following methods:

[0183] (1) Determine the evaluation index as sugar content, acidity, hardness and sugar-acid ratio, and set the weight coefficients of each evaluation index as K 糖度 =0.6, K 酸度 =0.2,K 硬度 =0.15, K 糖酸比 =0.05;

[0184] (2) Using the checkerboard method to select typical pear samples of the same variety with the same planting environment as the samples to be tested as the training set samples, the training set samples are 540 in total, accounting for 5% of the number of samples to be tested, and the samples in the training set The near-infrared absorption spectrum data is the independent variable, and the evaluation value of each evaluation index is the dependent variable. The partial least squares regression algorithm is used for regression operation, and the near-...

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Abstract

The invention relates to a comprehensive evaluation method of the quality of agricultural products; the method is based on a vibration spectrum quantitative prediction model, predicted values and model parameters of a plurality of evaluation indexes of to-be-measured samples are obtained based on the model, the prediction values are normalized, the model parameters of the evaluation indexes and weight coefficients of the evaluation indexes are combined, comprehensive evaluation values Z reflecting the comprehensive quality of the agricultural products are calculated, and all the to-be-measured samples are graded according to the distribution range of the Z values. The method provided by the invention gives full consideration to mutual influence between multiple indexes and multiple indexes of the quality of the agricultural products, gives consideration to the prediction performance of the model, and can achieve more scientific, concrete and practical grading of the quality of the agricultural products.

Description

technical field [0001] The invention relates to the field of agricultural product quality safety, in particular to a comprehensive evaluation method for agricultural product quality. Background technique [0002] Agricultural products are one of the food sources that people rely on for survival, and the quality grading of agricultural products is an important means to increase the added value of agricultural products. [0003] At present, the classification status of domestic agricultural product distribution enterprises is that they are not classified according to quality but only according to weight or volume, or they use destructive testing methods for quality classification. The main problem of weight or volume sorting is that the correlation between the sorting results and the quality of agricultural products cannot be guaranteed; while the classification by traditional destructive testing methods mainly has problems such as incomplete sampling coverage and limited test...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/359
CPCG01N21/359
Inventor 王冬潘立刚王纪华靳欣欣贾文珅马智宏李安侯金健万赐晖
Owner 尼尔软科(北京)科技有限公司
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