CN114018859A - Method for rapidly and synchronously measuring apparent amylose, amylose and amylopectin contents of rice flour - Google Patents
Method for rapidly and synchronously measuring apparent amylose, amylose and amylopectin contents of rice flour Download PDFInfo
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- 235000007164 Oryza sativa Nutrition 0.000 title claims abstract description 90
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- 229920000856 Amylose Polymers 0.000 title claims abstract description 84
- 229920000945 Amylopectin Polymers 0.000 title claims abstract description 49
- 235000013312 flour Nutrition 0.000 title claims abstract description 41
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- 241000209094 Oryza Species 0.000 claims abstract description 89
- 238000002329 infrared spectrum Methods 0.000 claims abstract description 19
- 238000001228 spectrum Methods 0.000 claims abstract description 17
- 239000000843 powder Substances 0.000 claims abstract description 14
- 238000002835 absorbance Methods 0.000 claims description 9
- 238000000227 grinding Methods 0.000 claims description 7
- 238000003801 milling Methods 0.000 claims description 7
- 238000007873 sieving Methods 0.000 claims description 6
- 238000002360 preparation method Methods 0.000 claims description 4
- 238000000985 reflectance spectrum Methods 0.000 claims description 3
- 238000003860 storage Methods 0.000 claims description 3
- 239000008186 active pharmaceutical agent Substances 0.000 claims description 2
- 238000004458 analytical method Methods 0.000 abstract description 7
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- 230000001360 synchronised effect Effects 0.000 abstract description 2
- 239000000126 substance Substances 0.000 description 16
- 229920002472 Starch Polymers 0.000 description 11
- 239000008107 starch Substances 0.000 description 11
- 235000019698 starch Nutrition 0.000 description 11
- 238000009826 distribution Methods 0.000 description 8
- 230000000694 effects Effects 0.000 description 5
- 229940100486 rice starch Drugs 0.000 description 4
- ZCYVEMRRCGMTRW-UHFFFAOYSA-N 7553-56-2 Chemical compound [I] ZCYVEMRRCGMTRW-UHFFFAOYSA-N 0.000 description 3
- 235000013339 cereals Nutrition 0.000 description 3
- 229910052740 iodine Inorganic materials 0.000 description 3
- 239000011630 iodine Substances 0.000 description 3
- 238000006116 polymerization reaction Methods 0.000 description 3
- 108010028688 Isoamylase Proteins 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 239000002994 raw material Substances 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- WQZGKKKJIJFFOK-GASJEMHNSA-N Glucose Natural products OC[C@H]1OC(O)[C@H](O)[C@@H](O)[C@@H]1O WQZGKKKJIJFFOK-GASJEMHNSA-N 0.000 description 1
- 238000011993 High Performance Size Exclusion Chromatography Methods 0.000 description 1
- 240000002582 Oryza sativa Indica Group Species 0.000 description 1
- 240000008467 Oryza sativa Japonica Group Species 0.000 description 1
- 210000001015 abdomen Anatomy 0.000 description 1
- 102000004139 alpha-Amylases Human genes 0.000 description 1
- 108090000637 alpha-Amylases Proteins 0.000 description 1
- 229940024171 alpha-amylase Drugs 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 238000004737 colorimetric analysis Methods 0.000 description 1
- 150000001875 compounds Chemical class 0.000 description 1
- 238000010411 cooking Methods 0.000 description 1
- 230000002596 correlated effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000029087 digestion Effects 0.000 description 1
- 125000000524 functional group Chemical group 0.000 description 1
- 238000005227 gel permeation chromatography Methods 0.000 description 1
- 239000008103 glucose Substances 0.000 description 1
- 229930182478 glucoside Natural products 0.000 description 1
- 150000008131 glucosides Chemical class 0.000 description 1
- 238000004192 high performance gel permeation chromatography Methods 0.000 description 1
- 230000031700 light absorption Effects 0.000 description 1
- 210000001161 mammalian embryo Anatomy 0.000 description 1
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- 238000002798 spectrophotometry method Methods 0.000 description 1
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Abstract
The invention relates to the technical field of rice powder analysis and detection, and discloses a method for rapidly and synchronously determining apparent amylose, amylose and amylopectin contents of rice powder, which comprises the following steps: (1) scanning the rice flour to be detected by using a near-infrared analyzer, and recording a near-infrared diffuse reflection spectrum; (2) and substituting the near-infrared diffuse reflection spectrum into a near-infrared spectrum prediction model of the content of the apparent amylose, the amylose and the amylopectin to obtain the content of the apparent amylose, the amylose and the amylopectin in the rice flour to be detected. The method utilizes a near infrared analysis technology and a specific near infrared spectrum prediction model, can realize the synchronous determination of the content of the apparent amylose, the amylose and the amylopectin in the rice powder, has the advantages of simple determination process, short time and low cost, simultaneously has high accuracy, and has good application prospect for the rapid screening and breeding of rice test materials, the improvement of the rice quality or the genetic research of the rice quality.
Description
Technical Field
The invention relates to the technical field of rice powder analysis and detection, in particular to a method for rapidly and synchronously determining apparent amylose, amylose and amylopectin contents of rice powder.
Background
The most major component of the edible rice endosperm is starch, which is about 80%. The rice starch is composed of amylose and amylopectin, and the amylose is mainly a high molecular compound in which most of D glucose is combined by alpha-1, 4 glucoside and is connected in a chain, and has few branches. Amylopectin is mainly bound by alpha-1, 6-glucoside, and is highly branched. The content of amylose in the japonica rice starch is generally about 20%, and the highest content of indica rice is generally about 30%. The glutinous rice starch contains substantially no amylose, and generally contains less than 2.0%. Amylose of non-glutinous rice and iodine molecules generate a complex which is blue or violet blue; the amylose content measured by this classical iodine blue method, Takeda et al, 1987, proposed a new concept of "Apparent Amylose Content (AAC)" to distinguish the amylose content measured by iodine colorimetry from the actual Amylose Content (AC) in rice starch. From a chemical composition point of view, AAC is actually composed of two parts, namely true amylose and long chains B of amylopectin with a partial chain length with a degree of polymerization of more than 60.
Beginning in the middle of the 60's of the 20 th century, the Apparent Amylose Content (AAC) in the endosperm is one of the most important indexes for evaluating the quality of rice cooking (Juliano et al, 1965), the AAC content is high, and rice is hard and fluffy; otherwise, it is soft and sticky (Radhika et al, 1993; Ong et al, 1995). However, in the middle of the 80 s, the phenomena that the AAC content is similar (especially the high and medium amylose content) and the texture of the rice is far from the standard are increasingly common, which suggests that new indexes, such as amylose AC (alpha-amylase) and amylopectin (amylopectin content, AP), can be related to the quality of the cooked taste of the rice. Radhika et al (1994); reddy et al (1994); sandhya et al (1995); ramesh et al (1999) and Aoki et al (2006) report that chain B of amylopectin in starch is considered to be related to the texture of rice, and that chain B makes rice hard, and that lack of chain B makes rice soft. Li et al (2016) report that the structure of amylopectin content exuded when rice is cooked has a significant effect on the viscosity of rice. AAC (degree of polymerization >100) and amylopectin with medium and long chain (degree of polymerization 31-92) are significantly negatively correlated with rice viscosity (Tao, Yu, Prakash & Gilbert, 2019).
In the prior art, the contents of AC and AP are determined by gel permeation chromatography (HPSEC), an international standard published in 2015 (ISO-6647-1,2,2015), which specifies the determination of these two parameters. The method has many steps from preparation of rice flour, weighing, gelatinization, separation of amylose and amylopectin by isoamylase, removal of isoamylase activity at high temperature to on-machine determination (including preparation of mobile phase, instrument stability and the like), high cost and long determination time, and a detector in the instrument determination is a differential detector and is easily influenced by temperature, so that strict heat preservation and temperature control are required to ensure the repeatability of the detection. Therefore, the method has the advantages of high accuracy and low cost, is very needed for rapidly measuring AC and AP, and has good promotion effect on aspects such as rice breeding, quality processing and the like.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method for rapidly and synchronously measuring the apparent amylose, amylose and amylopectin contents of rice flour. The method adopts a near-infrared rapid scanning determination method, can simultaneously determine the content of three types of starch in the rice flour, has simple pretreatment process, and has the advantages of rapidness, high efficiency, low cost and high accuracy.
The specific technical scheme of the invention is as follows:
a method for rapidly and synchronously measuring the apparent amylose, amylose and amylopectin contents of rice flour comprises the following steps:
(1) scanning the rice flour to be detected by using a near-infrared analyzer, and recording a near-infrared diffuse reflection spectrum;
(2) and substituting the near-infrared diffuse reflection spectrum value into a near-infrared spectrum prediction model of the content of the Apparent Amylose (AAC), the Amylose (AC) and the Amylopectin (AP) to obtain the content of the apparent amylose, the amylose and the amylopectin of the rice flour to be detected.
The near-infrared analysis technology can directly scan a sample, record the near-infrared spectrum of the sample, process the spectrogram through software and record the chemical value of the sample to establish a calibration prediction model (near-infrared spectrum prediction model), thereby simplifying the complicated pretreatment and instrument measurement procedures of the sample, and achieving the analysis with rapidness, accuracy, simplicity and low cost.
The method can simultaneously determine the content of three types of starch in the rice flour by utilizing a near infrared analysis technology, greatly simplifies the pretreatment process of the sample, does not need enzymolysis pretreatment in the process of determining the content of amylose and amylopectin and a chromatographic column of a gel permeation chromatograph, does not need digestion and spectrophotometric determination in the process of determining the content of apparent amylose, and has the advantages of high speed, high efficiency, low cost and high accuracy.
Preferably, in the step (1), the near infrared diffuse reflection spectrum is converted into an absorbance value for storage.
Preferably, in step (2), the near infrared spectrum prediction model of the apparent amylose content is as follows:
YAAC＝-14.6+385.7X1-1327X2-5740.7X3-3246.4X4+579.9X5-444.5X6-2964.2X7+642.0X8+358.0X9+495.3X10-554.8X11-7841.9X12-2228.2X13+48.9X14+904.6X15+25192.9X16+4194.8X17-4028.8X18+4273.5X19+19272.0X20-1317.8X21-3854.7X22+29185.9X23+2716.4X24-3854.0X25+3668.7X26-1525.9X27+6873.7X28+2262.0X29+3351.0X30-531.7X31-3829.7X32+17739.7X33-1501.1X34-1243.8X35+1260.6X36-1059.5X37-51.8X38+532.8X39+117.6X40+330.4X41-976.2X42-481.0X43+1511.5X44+475.8X45+387.2X46-7619.4X47+75.5X48+1102.1X49+4276.4X50+698.1X51+2065.3X52-1891.5X53+974.6X54+9648.1X55+3715.5X56+4197.8X57+1217.5X58+1983.5X59-2184.2X60+457.9X61+1191.4X62-312.2X63，
wherein, YAACTo the apparent amylose content, X1,X2,X3,……,X63Respectively is the absorbance values under 63 characteristic wavelengths in the near infrared diffuse reflection spectrum of the rice flour to be detected.
Preferably, in the step (2), the near infrared spectrum prediction model of the amylose content is as follows:
YAC＝-71.9+1715.1X1-964.1X2-6396.3X3-6938.2X4-1796.9X5+3030.7X6+21.9X7+525.0X8+324.2X9+1117.8X10+1920.9X11-4347.3X12-206.9X13-5358.2X14-1166.4X15+40372.8X16+5280.6X17-6727.9X18-3762.3X19+15294.3X20-302.3X21-7017.0X22+1583.9X23+2378.3X24-4171.7X25+3844.9X26-1020.7X27+2882.7X28+2549.8X29+2318.9X30-3650.4X31-1178.9X32+20222.2X33-4188.7X34+314.1X35+713.4X36-958.4X37-251.7X38+769.4X39-739.8X40-883.8X41-1843.9X42+2527.5X43+3736.7X44+86.8X45-1003.7X46-15207.3X47-62.5X48+2034.2X49+10420.7X50+309.2X51+4020.0X52-2694.7X53-2594.2X54+6062.6X55+6176.7X56+3794.4X57-331.1X58+1338.9X59-2184.2X60+457.9X61+1191.4X62-4690.8X63，
wherein, YACIs the amylose content, X1,X2,X3,……,X63Respectively is the absorbance values under 63 characteristic wavelengths in the near infrared diffuse reflection spectrum of the rice flour to be detected.
Preferably, in the step (2), the near infrared spectrum prediction model of the amylopectin content is as follows:
YAP＝113.7-2071.3X1+684.7X2+5779.0X3+5225.6X4-2868.2X5-2165.2X6+1257.0X7-1043.4X8-1586.7X9+750.9X10+3137.2X11+2118.3X12+3117.6X13+6795.3X14+4407.7X15-29828.6X16-11311.1X17+3921.9X18-1886.9X19-14290.1X20+3044.6X21-331.8X22-10775.6X23-351.3X24+3080.3X25-3500.2X26+1004.3X27-1271.4X28-1506.5X29-2971.1X30+3560.6X31-2696.8X32-18816.5X33+3296.9X34-2213.7X35-1150.7X36+175.7X37+67.1X38-518.0X39+677.6X40+1559.8X41+431.7X42-3451.5X43-1755.5X44+992.3X45+1403.3X46+21511.2X47+362.0X48+100.3X49-2812.4X50-706.3X51-3794.9X52+5325.0X53+3839.7X54-3180.2X55-4430.9X56-2511.7X57+2047.2X58+60.1X59-286.6X60+987.6X61-427.7X62+4271.8X63
wherein, YAPIs the amylopectin content, X1,X2,X3,……,X63Respectively is the absorbance values under 63 characteristic wavelengths in the near infrared diffuse reflection spectrum of the rice flour to be detected.
By adopting the near infrared spectrum prediction model, the prediction decision coefficients of three starch contents (apparent amylose, amylose and amylopectin contents) are all larger than 0.85 and the prediction standard deviation is smaller through the verification of 52 rice flour samples to be detected. Therefore, the model provided by the invention has the advantages of higher detection accuracy and better data repeatability when being used for detecting the content of three types of starch in rice flour.
Further, X1,X2,X3,……,X63The wavelengths in the near infrared diffuse reflection spectrum of the rice flour to be detected are 1300nm,1316nm,1332nm,1348nm,1364nm,1380nm,1396nm,1412nm,1428nm,1444nm,1460nm,1476nm,1492nm,1508nm,1524nm,1540nm,1556nm,1572nm,1588nm,1604nm,1620nm,1636nm,1652nm,1668nm,1684nm,1700nm,1716nm,1732nm, 1768 nm,1764nm,1780nm,1796nm,1812nm,1828nm,1844nm,1860nm,1876nm,1892nm,1908nm,1924nm,1940nm,1956nm,1972nm,1988nm,2004nm,2020nm,2036nm, 2062 nm,2068nm,2084nm, 2138 nm, 2266 nm, 2138 nm,2116nm, 2118 nm, 2188 nm, 2182 nm, 21876 nm and 21876 nm under the wavelengths of 2276nm and the wavelengths of 22196 nm and the wavelengths of the light absorption values.
The invention selects the 63 wavelengths, because: some characteristic wavelengths, such as 1460nm, 1684nm,1700nm, 1732nm, 1764nm, 1956nm, 2100nm and the like, show higher spectral peaks, and are multi-stage frequency doubling of groups or groups such as C-H, C-C, C ═ O and the like, and are directly related to starch or apparent amylose, amylose and amylopectin structures, i.e. the selected characteristic wavelength includes key chemical functional groups with starch (apparent amylose, amylose and amylopectin), which is effectively selected.
Further, in the step (1), the scanning wavelength range of the near infrared analyzer is 1300-2300 nm, the average scanning frequency is 64, and the acquisition interval is 16 nm.
Preferably, in step (1), the preparation method of the rice flour to be tested comprises the following steps: and grinding the polished rice to be detected, and sieving to obtain the rice powder to be detected with the fineness of 0.150-0.180 mm.
The fineness of rice flour affects the near infrared diffuse reflection effect. Sieving to obtain proper and consistent rice powder fineness, reducing or removing the existence of solid particles in the rice powder, solving the problem of uneven distribution of the rice powder fineness and ensuring stable and repeated diffuse reflection effect.
Further, in the step (1), the milling rate of the polished rice to be detected is 86-91%.
The polished rice with different milling rates has different compositions. The relationship between the grinding precision and the polished rice property is generally divided into three categories: a is refined rice with only rice bran on two sides of the rice grains completely removed, and the grinding rate is generally 96 percent; b, except two sides, the bran layer at the belly of the rice grains is also completely removed, and the grinding rate is about 94 percent generally; c is polished rice from which bran layer on the longitudinal grooves of rice grains was almost completely removed, and the milling rate was about 91%. The milling rate of 86-91% is selected, the milled rice is completely milled, no bran layer and no embryo exist, the whiteness of the milled rice is basically consistent, and the problems of instable near-infrared diffuse reflection and inconsistent diffuse reflection degree caused by bran powder can be solved.
Compared with the prior art, the invention has the following advantages:
the method utilizes a near infrared analysis technology and a specific near infrared spectrum prediction model, can realize the synchronous determination of the content of the apparent amylose, the amylose and the amylopectin in the rice powder, has the advantages of simple determination process, short time and low cost, simultaneously has high accuracy, and has good application prospect for the rapid screening and breeding of rice test materials, the improvement of the rice quality or the genetic research of the rice quality.
Drawings
FIG. 1 shows the near-infrared predicted values and chemical values of three starch contents in 52 rice flour samples to be tested; wherein, the graph (A) is the near-infrared predicted value and the chemical value of the apparent amylose content, the graph (B) is the near-infrared predicted value and the chemical value of the amylose content, and the graph (C) is the near-infrared predicted value and the chemical value of the amylopectin content.
FIG. 2 is a chemical value distribution frequency chart of apparent amylose content in 52 rice flour samples to be tested;
FIG. 3 is a graph showing the frequency of chemical value distribution of amylose content in 52 rice flour samples to be tested;
FIG. 4 is a graph showing the frequency of chemical value distribution of amylopectin content in 52 rice flour samples to be tested.
Detailed Description
The present invention will be further described with reference to the following examples.
Example 1
A method for rapidly and synchronously measuring the apparent amylose, amylose and amylopectin contents of rice flour comprises the following steps:
(1) and grinding the polished rice with the grinding rate of 90%, and sieving to obtain the polished rice powder with the fineness of 0.150mm to be detected.
(2) The rice flour sample with the concentrated external verification sample was scanned with an XM-1000 near infrared analyzer (FOSS corporation, sweden), and a near infrared diffuse reflectance spectrum was recorded, and the collected diffuse reflectance spectrum was converted into an absorbance value a for storage. The scanning wavelength range is 1300-2300 nm, the average scanning frequency is 64, and the acquisition interval is 16 nm; the inner diameter of the scanning disk is 38mm, the depth is 10mm, and the powder loading is about 3.0 g. Each sample was repeated three times and averaged.
(3) And substituting the near-infrared diffuse reflection spectrum value into a near-infrared spectrum prediction model of the content of the apparent amylose, the amylose and the amylopectin to obtain the content of the apparent amylose, the amylose and the amylopectin in the polished rice flour to be detected. The near infrared spectrum prediction model of the apparent amylose, amylose and amylopectin content is as follows:
YAAC＝-14.6+385.7X1-1327X2-5740.7X3-3246.4X4+579.9X5-444.5X6-2964.2X7+642.0X8+358.0X9+495.3X10-554.8X11-7841.9X12-2228.2X13+48.9X14+904.6X15+25192.9X16+4194.8X17-4028.8X18+4273.5X19+19272.0X20-1317.8X21-3854.7X22+29185.9X23+2716.4X24-3854.0X25+3668.7X26-1525.9X27+6873.7X28+2262.0X29+3351.0X30-531.7X31-3829.7X32+17739.7X33-1501.1X34-1243.8X35+1260.6X36-1059.5X37-51.8X38+532.8X39+117.6X40+330.4X41-976.2X42-481.0X43+1511.5X44+475.8X45+387.2X46-7619.4X47+75.5X48+1102.1X49+4276.4X50+698.1X51+2065.3X52-1891.5X53+974.6X54+9648.1X55+3715.5X56+4197.8X57+1217.5X58+1983.5X59-2184.2X60+457.9X61+1191.4X62-312.2X63，
YAC＝-71.9+1715.1X1-964.1X2-6396.3X3-6938.2X4-1796.9X5+3030.7X6+21.9X7+525.0X8+324.2X9+1117.8X10+1920.9X11-4347.3X12-206.9X13-5358.2X14-1166.4X15+40372.8X16+5280.6X17-6727.9X18-3762.3X19+15294.3X20-302.3X21-7017.0X22+1583.9X23+2378.3X24-4171.7X25+3844.9X26-1020.7X27+2882.7X28+2549.8X29+2318.9X30-3650.4X31-1178.9X32+20222.2X33-4188.7X34+314.1X35+713.4X36-958.4X37-251.7X38+769.4X39-739.8X40-883.8X41-1843.9X42+2527.5X43+3736.7X44+86.8X45-1003.7X46-15207.3X47-62.5X48+2034.2X49+10420.7X50+309.2X51+4020.0X52-2694.7X53-2594.2X54+6062.6X55+6176.7X56+3794.4X57-331.1X58+1338.9X59-2184.2X60+457.9X61+1191.4X62-4690.8X63，
YAP＝113.7-2071.3X1+684.7X2+5779.0X3+5225.6X4-2868.2X5-2165.2X6+1257.0X7-1043.4X8-1586.7X9+750.9X10+3137.2X11+2118.3X12+3117.6X13+6795.3X14+4407.7X15-29828.6X16-11311.1X17+3921.9X18-1886.9X19-14290.1X20+3044.6X21-331.8X22-10775.6X23-351.3X24+3080.3X25-3500.2X26+1004.3X27-1271.4X28-1506.5X29-2971.1X30+3560.6X31-2696.8X32-18816.5X33+3296.9X34-2213.7X35-1150.7X36+175.7X37+67.1X38-518.0X39+677.6X40+1559.8X41+431.7X42-3451.5X43-1755.5X44+992.3X45+1403.3X46+21511.2X47+362.0X48+100.3X49-2812.4X50-706.3X51-3794.9X52+5325.0X53+3839.7X54-3180.2X55-4430.9X56-2511.7X57+2047.2X58+60.1X59-286.6X60+987.6X61-427.7X62+4271.8X63，
wherein, YAAC、YAC、YAPRespectively the apparent amylose, amylose and amylopectin contents, X1,X2,X3,……,X63Respectively 1300nm,1316nm,1332nm,1348nm,1364nm,1380nm,1396nm,1412nm,1428nm,1444nm,1460nm,1476nm,1492nm,1508nm,1524nm,1540nm,1556nm,1572nm,1588nm,1604nm,1620nm,1636nm and 1652nm in the near-infrared diffuse reflection spectrum of the rice flour to be detected,1668nm,1684nm,1700nm,1716nm,1732nm,1748nm,1764nm,1780nm,1796nm,1812nm,1828nm,1844nm,1860nm,1876nm,1892nm,1908nm,1924nm,1940nm,1956nm,1972nm,1988nm,2004nm,2020nm,2036nm,2052nm,2068nm,2084nm,2100nm,2116nm,2132nm,2148nm,2164nm,2180nm,2196nm,2212nm,2228nm,2244nm,2260nm,2276nm,2292 nm.
Example 2
The present example is different from example 1 only in that the rice polished rice has a milling precision of 86% and a sieving fineness of 0.16mm in step (1).
Example 3
The present example is different from example 1 only in that, in step (1), the polished rice has a milling precision of 91% and a sieving fineness of 0.18 mm.
Test example
The method in example 1 is adopted to measure the apparent amylose, amylose and amylopectin contents in 52 rice flour samples to be tested and verified, and the near-infrared predicted values of the three starch contents are obtained.
The apparent amylose content of the rice flour sample is determined according to the international standard ISO 6647-2 (method A) (2020), namely the chemical value of the apparent amylose content. The amylose content and amylopectin content of rice flour samples, i.e. the chemical values of amylose content and amylopectin content, were determined according to the high performance gel permeation chromatography method of international standard ISO-6647-1,2,2015. Chemical value distribution frequency diagrams of AAC, AC and AP in 52 samples are respectively shown in figures 2-4, the distribution ranges are respectively 1.5-26.4%, 0.0-25.2% and 74.8-100.0%, and the distribution frequency is basically close to normal distribution, which shows that 52 rice flour samples to be detected selected by the invention can better verify the accuracy of a near infrared spectrum prediction model.
The near-infrared predicted values and the chemical values of the three starch contents in 52 rice flour samples to be detected and the difference values of the near-infrared predicted values and the chemical values are shown in a graph 1 and a table 1, the prediction decision coefficients and the prediction standard deviations are calculated accordingly, the obtained prediction decision coefficients of the apparent amylose, amylose and amylopectin contents are respectively 0.9215, 0.879 and 0.895, and the prediction standard deviations are respectively 1.1024%, 1.599% and 1.479%, so that the near-infrared spectrum prediction model has good prediction capability (the predicted values and the chemical values have good consistency), and the near-infrared spectrum prediction model is adopted to synchronously predict the apparent amylose, amylose and amylopectin contents in rice flour, and has high accuracy.
TABLE 1
The raw materials and equipment used in the invention are common raw materials and equipment in the field if not specified; the methods used in the present invention are conventional in the art unless otherwise specified.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and all simple modifications, alterations and equivalents of the above embodiments according to the technical spirit of the present invention are still within the protection scope of the technical solution of the present invention.
Claims (9)
1. A method for rapidly and synchronously measuring the apparent amylose, amylose and amylopectin contents of rice flour is characterized by comprising the following steps:
(1) scanning the rice flour to be detected by using a near-infrared analyzer, and recording a near-infrared diffuse reflection spectrum;
(2) and substituting the near-infrared diffuse reflection spectrum numerical value into a near-infrared spectrum prediction model of the content of the apparent amylose, the amylose and the amylopectin to obtain the content of the apparent amylose, the amylose and the amylopectin in the rice flour to be detected.
2. The method of claim 1, wherein in step (1), the near infrared diffuse reflectance spectrum values are converted to absorbance values for storage.
3. The method of claim 1, wherein in step (2), the near infrared spectrum of the apparent amylose content is predicted by a model comprising:
YAAC=-14.6+385.7X1-1327X2-5740.7X3-3246.4X4+579.9X5-444.5X6-2964.2X7+642.0X8+358.0X9+495.3X10-554.8X11-7841.9X12-2228.2X13+48.9X14+904.6X15+25192.9X16+4194.8X17-4028.8X18+4273.5X19+19272.0X20-1317.8X21-3854.7X22+29185.9X23+2716.4X24-3854.0X25+3668.7X26-1525.9X27+6873.7X28+2262.0X29+3351.0X30-531.7X31-3829.7X32+17739.7X33-1501.1X34-1243.8X35+1260.6X36-1059.5X37-51.8X38+532.8X39+117.6X40+330.4X41-976.2X42-481.0X43+1511.5X44+475.8X45+387.2X46-7619.4X47+75.5X48+1102.1X49+4276.4X50+698.1X51+2065.3X52-1891.5X53+974.6X54+9648.1X55+3715.5X56+4197.8X57+1217.5X58+1983.5X59-2184.2X60+457.9X61+1191.4X62-312.2X63，
wherein, YAACTo the apparent amylose content, X1, X2, X3, ……, X63Respectively is the absorbance values under 63 characteristic wavelengths in the near infrared diffuse reflection spectrum of the rice flour to be detected.
4. The method of claim 1, wherein in step (2), the near infrared spectrum prediction model for amylose content is:
YAC=-71.9+1715.1X1-964.1X2-6396.3X3-6938.2X4-1796.9X5+3030.7X6+21.9X7+525.0X8+324.2X9+1117.8X10+1920.9X11-4347.3X12-206.9X13-5358.2X14-1166.4X15+40372.8X16+5280.6X17-6727.9X18-3762.3X19+15294.3X20-302.3X21-7017.0X22+1583.9X23+2378.3X24-4171.7X25+3844.9X26-1020.7X27+2882.7X28+2549.8X29+2318.9X30-3650.4X31-1178.9X32+20222.2X33-4188.7X34+314.1X35+713.4X36-958.4X37-251.7X38+769.4X39-739.8X40-883.8X41-1843.9X42+2527.5X43+3736.7X44+86.8X45-1003.7X46-15207.3X47-62.5X48+2034.2X49+10420.7X50+309.2X51+4020.0X52-2694.7X53-2594.2X54+6062.6X55+6176.7X56+3794.4X57-331.1X58+1338.9X59-2184.2X60+457.9X61+1191.4X62-4690.8X63，
wherein, YACIs the amylose content, X1, X2, X3,……, X63Respectively is the absorbance values under 63 characteristic wavelengths in the near infrared diffuse reflection spectrum of the rice flour to be detected.
5. The method of claim 1, wherein in step (2), the near infrared spectrum prediction model for amylopectin content is:
YAP=113.7-2071.3X1+684.7X2+5779.0X3+5225.6X4-2868.2X5-2165.2X6+1257.0X7-1043.4X8-1586.7X9+750.9X10+3137.2X11+2118.3X12+3117.6X13+6795.3X14+4407.7X15-29828.6X16-11311.1X17+3921.9X18-1886.9X19-14290.1X20+3044.6X21-331.8X22-10775.6X23-351.3X24+3080.3X25-3500.2X26+1004.3X27-1271.4X28-1506.5X29-2971.1X30+3560.6X31-2696.8X32-18816.5X33+3296.9X34-2213.7X35-1150.7X36+175.7X37+67.1X38-518.0X39+677.6X40+1559.8X41+431.7X42-3451.5X43-1755.5X44+992.3X45+1403.3X46+21511.2X47+362.0X48+100.3X49-2812.4X50-706.3X51-3794.9X52+5325.0X53+3839.7X54-3180.2X55-4430.9X56-2511.7X57+2047.2X58+60.1X59-286.6X60+987.6X61-427.7X62+4271.8X63，
wherein, YAPIs the amylopectin content, X1, X2, X3,……, X63Respectively is the absorbance values under 63 characteristic wavelengths in the near infrared diffuse reflection spectrum of the rice flour to be detected.
6. The method according to any one of claims 3 to 5, wherein X is1, X2, X3,……, X63Respectively 1300nm,1316nm,1332nm,1348nm,1364nm,1380nm,1396nm,1412nm,1428nm,1444nm,1460nm,1476nm,1492nm,1508nm,1524nm,1540nm,1556nm,1572nm,1588nm,1604nm,1620nm,1636nm,1652nm,1668nm,1684nm,1700nm,1716nm,1732nm, 1768 nm,1764nm,1780nm,1796nm,1812nm,1828nm,1844nm,1860nm,1876nm,1892nm,1908nm,1924nm,1940nm,1956nm,1972nm,1988nm,2004nm,2020nm,2036nm,2052nm in the near infrared diffuse reflection spectrum of the rice flour to be detected, 2068nm,2084nm,2100nm,2116nm,2132nm,2Absorbance values at 148nm,2164nm,2180nm,2196nm,2212nm,2228nm,2244nm,2260nm,2276nm and 2292 nm.
7. The method of claim 6, wherein in step (1), the near infrared analyzer scans the wavelength range of 1300-2300 nm, the average number of scans is 64, and the acquisition interval is 16 nm.
8. The method according to claim 1, wherein in the step (1), the preparation method of the rice flour to be tested comprises the following steps: and grinding the polished rice to be detected, and sieving to obtain the rice powder to be detected with the fineness of 0.150-0.180 mm.
9. The method of claim 8, wherein in the step (1), the milled rice to be measured has a milling rate of 86-91%.
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