CN105243599A - Method for building rice storage quality evaluation model - Google Patents

Abstract

The invention discloses a method for constructing a rice storage quality evaluation model. Screen the sensitivity indicators that affect the storage quality of rice, and find out the indicators that have a good correlation with the storage time and storage method from the multiple indicators as the sensitivity indicators, and perform variance analysis on the above indicators to determine the fatty acid value, reducing sugar content, and hardness. The three indicators are the sensitivity indicators for evaluating the storage quality, and the quadratic polynomial regression analysis is carried out to establish the rice storage quality evaluation model: Y/10=-1.281+0.074*X ₁ +3.845*X ₂ +0.0011*X ₃ . The method of the invention can evaluate, utilize and effectively avoid the reduction of cooking quality and eating quality of rice during storage, and has good feasibility and adaptability.

Description

A method for constructing a rice storage quality evaluation model

technical field

The invention relates to the establishment of a rice aging model, and the method belongs to the technical field of agricultural production, in particular to a method for constructing a rice storage quality evaluation model.

Background technique

Rice is one of the important foods of our people. Since there is no protection of rice husk and the endosperm is directly exposed, it is more sensitive to the influence of external temperature, humidity and oxygen concentration; at the same time, the direct invasion of pests and molds leads to accelerated loss of rice nutrients. It is prone to aging and reduces the storage quality.

Compared with starch and protein in rice, lipids are more likely to cause aging and deterioration of rice. During storage, lipids are affected by air and high temperature, which can easily accelerate the rate of rice deterioration, resulting in a decline in the eating quality of rice. Therefore, my country's current rice storage quality judgment rules (GB/T20569-2006) use the free fatty acid value as a standard to reflect the degree of grain deterioration and storage quality. However, the change of rice storage quality is a dynamic process. Due to the different sensitivities of various indicators during the storage process, there are differences in the impact on the freshness of rice. An isolated indicator cannot be used to evaluate its storage quality. Therefore, the establishment of A scientific and effective quality evaluation method has practical significance for the good storage of rice, but there are few relevant research reports so far.

Contents of the invention

The problem to be solved by the present invention is to provide a method for constructing an evaluation model of rice storage quality. The method utilizes the analysis of variance (ANOVA) method to screen the rice sensitivity index, and utilizes the quadratic polynomial regression analysis method to establish a fast and accurate rice Storage quality evaluation index system.

In order to achieve the above object, the technical scheme adopted in the present invention is:

A method for constructing a rice storage quality evaluation model,

(1) Simulate the rice storage experiment, screen the sensitive indicators that affect the rice storage quality, and measure the stored rice fatty acid value, total acid value, reducing sugar content, hardness, and gelatinization temperature indicators.

(2) Find the index with better correlation with storage time and storage mode from multiple indexes as the sensitivity index, and use variance analysis to screen the index in (1) for the sensitivity of storage quality;

(3) Using quadratic polynomial regression analysis to establish a rice storage quality evaluation model:

Y/10＝-1.281+0.074*X1 ₊ 3.845*X2 ₊ 0.0011* _X3 ;

Among them, Y is the storage time, X1 is the fatty acid value, mgKOH/100g dry matter _; X2 is the reducing sugar content, _mg glucose/100g sample; _X3 is the hardness, g.

The advantages that the present invention has are:

1. The present invention establishes a rice storage quality evaluation model, and screening sensitive indicators to establish an evaluation index system to predict storage quality is more accurate and reliable than a single index.

2. The present invention can evaluate the use and effectively avoid the decline of the cooking quality and eating quality of rice during storage, and has good feasibility and adaptability.

3. The experiment involved in the present invention is not complicated, convenient and accurate in data, can objectively reflect the change of rice quality in storage, and is easy to implement in practice.

detailed description

The present invention will be further elaborated below in conjunction with embodiment, but does not therefore present the present invention.

Example 1

A method for constructing a rice storage quality evaluation model, comprising the following steps:

(1) Simulated storage experiment: Rice samples were packaged in commercially available woven bags, and placed in artificial climate chambers at temperatures of 15, 25, and 30° C. (60% RH) for simulated storage experiments.

(2) Screening storage quality sensitivity indicators: on the basis of retaining the fatty acid indicators in the "Rice Storage Quality Judgment Rules", increase the indicators of total acid value, reducing sugar content, hardness, and gelatinization temperature, and find out from a number of indicators that are closely related to The index with better correlation between storage time and storage method was used as the sensitivity index. Carry out variance analysis on the above indicators, and the indicators that have a significant relationship with the storage time and storage method (P<0.05 is significant, P<0.01 is extremely significant) include: fatty acid value, reducing sugar content, hardness, and the above three indicators are selected as Sensitive index for evaluating storage quality.

Table 1.

storage time degrees of freedom sum of square mean square f significant fatty acid 2 67612.573 1679.821 26.0000 ** Acid value 2 30.383 .069 4.956 Reducing sugar content 5 2.056 .411 653.484 ** hardness 5 5.848E7 1.170E7 54.791 ** gelatinization temperature 4 1558.022 389.505 32.059 storage method degrees of freedom sum of square mean square f fatty acid 2 203.238 101.619 1.573 Acid value 2 .056 .028 2.025 Reducing sugar content 2 .017 .008 13.280 **

hardness 2 176366.144 88183.072 .413 gelatinization temperature 2 53.570 26.785 2.205

* means P<0.05, significant correlation; ** means P<0.01, extremely significant correlation.

Check the critical F value according to the variance analysis table:

Among them, after changing the storage time, the fatty acid: F _0.05(2,18) = 3.55, F _0.01(2,18) = 6.01, because F>F _0.01(2,18) , that is, P<0.01, so it is considered that the storage time is Fatty acids have a significant effect. Reducing sugar: F _0.05(2,18) ＝3.55, F _0.01(2,18) ＝6.01, because F>F _0.01(2,18) , that is, P<0.01, it is considered that storage time has a significant impact on reducing sugar. Hardness: F _0.05(5,16) ＝3.01, F _0.05(5,16) ＝4.77, because F>F _0.05(5,16 , that is, P<0.01, it is considered that storage time has a significant impact on hardness; and changing storage After the method, reducing sugar content: F _0.05(2,12) = 3.26, F _0.0,1(2,12) = 5.41, because F>F _0.0,1(2,12) , that is, P<0.01, so it is considered that the storage The method had a significant effect on the reducing sugar content.

(3) Establish a rice storage quality prediction model:

It can be known from the above that the storage time has a very significant impact on the three indicators of fatty acid content, reducing sugar content and hardness in rice. According to the data obtained from the experiment, the regression analysis of the JMP software is obtained: the regression calculation formula of the rice sensitivity index on the storage time is :

Y/10＝-1.281+0.074*X1 ₊ 3.845*X2 ₊ 0.0011* _X3 ;

F=94.858; correlation coefficient R=0.922.

In the following formula, Y is storage time, X ₁ is fatty acid value, mgKOH/100g dry matter; X ₂ is reducing sugar content, mg glucose/100g sample; X ₃ is hardness, g.

Validation model:

1. Store rice packed in woven bags in an artificial climate box at 15°C for 30, 60, 90, and 120 days

2. Store rice packed in woven bags in an artificial climate box at 25°C for 30, 60, 90, and 120 days

3. Store rice packed in woven bags in an artificial climate box at 30°C for 30, 60, 90, and 120 days

It can be seen from the above that the regression equation is basically satisfied.

Claims (1)

1. A method for constructing a rice storage quality evaluation model, characterized in that, screening sensitivity indicators that affect rice storage quality, finding an indicator that has better correlation with storage time and storage mode from multiple indicators as a sensitivity indicator , carry out analysis of variance to above-mentioned index and determine fatty acid value, reducing sugar content, the above three indexes of hardness are the sensitivity indexes of evaluating storage quality, then carry out quadratic polynomial regression analysis, and then establish the rice storage quality evaluation model: Y/10=- 1.281+0.074*X ₁ +3.845*X ₂ +0.0011*X ₃ ; wherein, Y is storage time, X ₁ is fatty acid value, mgKOH/100g dry matter; X ₂ is reducing sugar content, mg glucose/100g sample; X ₃ is hardness, g.