CN106370551A - Method for fast measuring corn kernel water loss rate based on regression model and application - Google Patents
Method for fast measuring corn kernel water loss rate based on regression model and application Download PDFInfo
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- CN106370551A CN106370551A CN201610867685.9A CN201610867685A CN106370551A CN 106370551 A CN106370551 A CN 106370551A CN 201610867685 A CN201610867685 A CN 201610867685A CN 106370551 A CN106370551 A CN 106370551A
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- G—PHYSICS
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N5/00—Analysing materials by weighing, e.g. weighing small particles separated from a gas or liquid
- G01N5/04—Analysing materials by weighing, e.g. weighing small particles separated from a gas or liquid by removing a component, e.g. by evaporation, and weighing the remainder
- G01N5/045—Analysing materials by weighing, e.g. weighing small particles separated from a gas or liquid by removing a component, e.g. by evaporation, and weighing the remainder for determining moisture content
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
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Abstract
The invention belongs to the field of crop breeding, and relates to a method for fast measuring the corn kernel water loss rate based on a regression model and application. The method comprises the following steps of building a regression model of corn kernel water content yn; calculating the corn kernel water loss rate V=(yn-y1)/n; determining the correlation between the water content measured by an oven drying method and readings of a water measuring instrument through SPSS (statistic package for social science) software according to the regression model of the corn kernel water content yn; drawing a scatter diagram; building a regression model y=95.709-2.29x+0.02x<2>, wherein the x is the reading of the water measuring instrument on the corn kernels and bracteal leaves, and the y is the corn kernel water content. The method for fast measuring the corn kernel water loss rate provided by the invention has very important breeding values, and particularly in nowadays that mechanical harvest becomes the major trend of corn industry development; the importance of the method is increasingly shown.
Description
Technical field
The invention belongs to crop breeding field, it is related to a kind of quickly measure Kernel Dry-down in Maize based on regression model
Method and application.
Background technology
With the continuous propulsion of corn harvest mechanization process, the development of Maize Industry is aqueous when needing that dehydration is fast badly, harvesting
Measure low corn variety.The requirement to corn kernel moisture for the mechanized harvest is between 20%-24%, and China's major part Semen Maydiss
Physiological maturity grain water content 30% about, lead to machine to receive seed damage rate and be up to 13%-17%.Not only cause
Production loss, is reduced quality grade, has also significantly raised the production cost being brought by dry in the sun.
But when seed dewatering speed and results, the improvement of water content is not simple question, the measurement of conventional rate of water loss
Depend on traditional sampling drying method, one is that operation is cumbersome, and particularly in corn pollination early stage, seed is difficult to completely shell more
From；Two is with destructiveness, and the mensure of rate of water loss needs to be repeated several times, for early for breeding material, such experiment
It is unpractical；In addition, the change of rate of water loss is one linking up and lasting process, between different plant inevitably
Have differences, these all can produce impact to final result.
And the research for portable needle-inserted moisture test apparatus starts from kang etc. (1975), the grade using current intensity is commented
Valency Grain water.In decades, related research never has and stops, at present the existing determination of water dedicated for measurement Semen Maydiss
Instrument.Although accuracy could be improved, combine with traditional oven drying method, set up data model and be corrected, also can yet be regarded as one
Plant desirable field experiment fast appraisement method.
With regard to the research of corn dehydration speed, it is no lack of correlational study both at home and abroad, but is based primarily upon traditional oven drying method, and utilize
The correlational study that moisture test apparatus weigh rate of water loss is less.
Content of the invention
The present invention is the technical barrier solving to screen the superior corn seed of high rate of water loss, there is provided a kind of being based on returns
Model quickly measures method and the application of Kernel Dry-down in Maize.
For solving above-mentioned technical barrier, the present invention employs the following technical solutions:
A kind of method quickly measuring Kernel Dry-down in Maize based on regression model, sets up corn kernel moisture yn
Regression model, calculate corn kernel rate of water loss v=(yn-y1)/n, wherein v are rate of water loss, ynFor n-th day Corn Seeds
The water content of grain, y1For the water content of first day corn kernel, n is detection natural law；Described corn kernel moisture ynRecurrence
Model, using the determination of water to corn kernel+bract and corn kernel for the moisture test apparatus, is surveyed by spss software analysis moisture
Determine the dependency between instrument reading and oven method measuring water content, draw scatterplot, set up regression model: y=95.709-
2.29x+0.02x2, wherein x is the reading to corn kernel+bract for the moisture test apparatus, and y is the moisture of corn kernel.
The determination of water of described corn kernel+bract is that by bract, probe is inserted seed, and the moisture now measuring is read
Number is the water content of bracteal leaf of corn+seed.
A kind of method quickly measuring Kernel Dry-down in Maize based on regression model, for predicting live body corn ear seed
Grain this economical character of water content, the fast excellent material of screening rate of water loss, as the application of corn breeding.
The beneficial effects of the present invention is:
1. the present invention passes through set up determination of water master pattern, calculates live body fruit ear moisture content of kernels, records same
The moisture content of kernels dynamic changing process of fruit ear, the method as evaluating, screen fast dewatering Semen Maydiss, and built using the present invention
Nearly 300 parts of Semen Maydiss mid-term combined materials have been carried out the assessment of fruit ear water content, have therefrom filtered out rate of water loss fast by vertical master pattern
Excellent material, for corn breeding.
2. the method for rapid evaluation corn dehydration speed provided by the present invention, has more important Breeding value, special
It it is not the today already becoming Corn Industrialization major trend in mechanized harvest, the importance of the present invention also will be increasingly convex
Aobvious.
Brief description
Fig. 1 is moisture content of kernels to seed+bract moisture readings quadratic term curve model.
Fig. 2 is different times seed, bract, cob change of moisture content after pollination.
Specific embodiment
1 materials and methods
1.1 test materials and field design
This test in beautiful No. 8 of selection bridge in 2014, dredge single 20, Zheng Dan 958 is as test kind, and increases moral in 2015
U.S. sub- No. 3,101 two kinds of agriculture China.Planting experiment material in Hebi City Academy of Agricultural Sciences garden experimental plot, using random area
Group design, 3 repetitions, duplicate rows area, long 5 meters of row, spacing in the rows 22cm, line-spacing 60cm.Administrative standard is identical with conventional corn production field.
The mensure of 1.2 rate of water loss
Before female fringe is not spun, the consistent plant of growth selection is manually covered female fringe to every cell, after filigree is extracted out, one
Secondary property removes covered female fringe bag, is allowed to unified and accepts extraneous pollination, and listing mark pollination date.After self-pollination 30d about open
Beginning investigation and sampling, each cell takes 3-4 unified pollination fringe at random, investigates 1 time within every 5 days, to end in latter 65 days about of pollinating, altogether
8 field samplings of meter.
1.2.1 Instrument measuring
Show according to previous investigation (nelson and lawrence, 1991), be optimum determining position in the middle part of fruit ear,
Therefore be measured in the middle part of selection fruit ear.Measure using in the middle part of Shenzhen Ai Gerui sh-2 type moisture test apparatus insertion fruit ear, often
Individual fruit ear repeated measure 2 times, is numbered to fruit ear immediately after record, samples, packs, and takes back indoor preparation and dry and measure.
Used by the present invention, moisture test apparatus probe is about 1cm, for most fruit ears, is generally only capable of inserting seed, not
And cob is it is impossible to measure full fringe water content.
Seed+bract determination of water: insert a probe into bract and seed, the moisture readings now measuring are: bract+seed
Grain.
Grain water measures: inserts a probe into seed after divesting bract, now measure is only corn kernel moisture readings.
1.2.2 traditional oven drying method measures
Moisture content of kernels and rate of water loss measure: every fringe takes middle part about 3cm length, band girdle corn kernel, weighs fresh weight (wFresh),
Load in gauze bag, be placed in 85 DEG C of baking ovens and dry 7 days to constant weight, weigh dry weight (wDry).
Bract, cob water content and rate of water loss: weigh bract fresh weight (wFresh), after band girdle seed, weigh the long fruit ear of about 3cm
Middle part cob fresh weight (wFresh), load gauze bag, prior to 105 DEG C of 30min that complete, dry 7 days to constant weight for 85 DEG C, weigh dry weight
(wDry).
According to continuous 2 sub-sampling moistures, calculate seed, bract, cob day rate of water loss.
Water content (%)=(wFresh-wDry)/wFresh×100；
Rate of water loss v=(yn-y1)/n, wherein ynFor the water content of n-th day corn kernel, y1For first day corn kernel
Water content, n be detection natural law；
Rate of water loss is taken the mean and is obtained average dehydration speed.
1.3 regression models are set up
Using the dependency between spss analysis moisture analyzer reading and oven method measuring water content, draw scatterplot,
Set up regression model.
1.4 field selfing line harvest time moisture measurements
Treat harvest time, carry out determination of water, record measurement using moisture test apparatus 200 parts of selfing based materials nearly to field
Value, and calculated using set up model.
1.5 harvest time water content and ssr labelling association analysiss
167 parts of field selfing line blade dna in 2015 are extracted using paramagnetic particle method, knot is studied according to Liu Xianjun etc. (2010)
Really, choose and 4 electrophoresis detection is carried out to ssr primer, and by testing result and harvest time moisture test apparatus measurement result, physiological maturity
Natural-dehydration speed combines afterwards, is associated analyzing using the glm function of tassel2.0.
2 results and analysis
2.1 numeratio and the correlation analysiss of oven method measuring water content
This research and utilization moisture test apparatus are measured, and utilize to Grain water reading and seed+bract moisture readings
Oven Method is measured to seed, bract, cob water content.Each characteristic index collects the data of continuous 2 years, using spss
Statistics19 is analyzed to its dependency, finds that cob water content is all very low with other characteristic index correlation coefficienies, and
Moisture content of kernels and bract water content correlation coefficient highest.
Table 1 moisture test apparatus reading measures the correlation coefficient of moisture with baking oven
The regression model of 2.2 seeds+bract reading and moisture content of kernels is set up
Using ibm spss statistics, the seed+bract moisture readings of 5 seeds of single cross are carried out with moisture content of kernels
Curve estimation, and establish regression model, though finding that material to be tested is different, the degree of fitting of quadratic term model is highest.Comprehensive
Close all test datas over 2 years, set up regression model: y=95.709-2.29x+0.02x2, r2For 0.774.
But when seed+cob reading is less than 60%, both true moisture content of kernels low 30% when, contained with this model prediction seed
The water yield but rises against the tendency, as shown in figure 1, there is certain deviation.Trace it to its cause, one is that physiology gives birth to the time ripe phase to harvest time relatively
Short, gathered experimental data is relatively fewer；Second, there is different degrees of senilism between later stage kind, lead to part fruit ear seed
Loose, also have impact on the accuracy of Instrument measuring to a certain extent.
25 seed of single cross seed+bract moisture readings of table and the regression model of moisture content of kernels
2.3 bract water content and its impact to moisture content of kernels
Kang (1977) etc. analyzes the relation of bract water content and moisture content of kernels, finds that both are positive correlation (p=
0.05).This comprehensive study experimental result of 2 years, finds that correlation coefficient between the two reaches 0.887 (in p=0.01 level
Significantly correlated), this is consistent with (1986) results such as kang.In addition, comprehensive 5 seed of single cross test datas, as shown in Fig. 2 originally grinding
Study carefully discovery, after pollination, early stage bract water content is higher than moisture content of kernels, and after pollination between 45d-50d, bract water content
There is more significantly downward trend, that is, in this time period, about when water content is 40% about, bract is aqueous
Amount begins lower than moisture content of kernels.
With being continually changing of bract water content, it also has different impacts: early stage after pollination to seed+bract reading,
Bract water content is higher, and seed+bract moisture readings are above Grain water reading, and some erratic ripples in stage
Dynamic.And show to certain herbaceous plants with big flowers (2011) paper, when bract water content is more than or equal to 60%, full fringe moisture readings contain with bract
The raising of the water yield and increase；Both conclusions are basically identical.
The impact to moisture content of kernels for the 2.4 cob water content
Seed, cob, bract change of moisture content situation after 35 seed of single cross pollinations of table
The present invention has carried out surveying record using oven drying method to cob water content, such as Fig. 2, finds the fringe of same material to be tested
Axle water content, from dough stage to all no larger change of results；And between different cultivars, cob water content difference is larger, such as table
3, sub- No. 3 of dolantin is early-maturing variety, and cob water content is significantly lower than other experimental cultivars.Comprehensive all data, cob water content
It is 0.228 (significantly correlated in p=0.05 level) with moisture content of kernels correlation coefficient, but correlation coefficient is less, and different product
Interspecific correlation difference is larger.
2.5 seeds, cob, bract rate of water loss
It is a discovery of the invention that 30 days after self-pollination start, no matter bract average dehydration speed is all big sooner or later the material to be tested ripe phase
In 2, arrive earliest in the peak of the particularly No. 3 bract rate of water loss in dolantin Asia, and the rate of water loss of seed is hovered 1 about, and
The rate of water loss of cob is minimum, and whole experimental stage change is less.
Table 4 is pollinated latter 30 days seed, cob, bract average dehydration speed
2.6 Markers for Detection and Instrumental results association analysiss
The present invention, on Liu Xianjun etc. (2012) Research foundation, selects 4 to the ssr labelling related to rate of water loss, to 167
Part selfing based material is detected, and combines water consumpation survey meter measurement result, as shown in table 5.
It is associated analyzing using the glm function of tassel 2.0 software, find 4 to primer pair field harvest time water content
Explanation rate is relatively low, and relatedness is all little.
3. discuss
This research and utilization portable moisture analyzer and traditional oven drying method measure moisture content of kernels, and will the two result phase knot
Close, correlation analysiss are carried out by spss software, and sets up regression model: y=95.709-2.29x+0.02x2, r2For 0.774,
Can be used in field direct measurement corn kernel water content, calculate seed rate of water loss, quickly take off as a kind of evaluation, screening
The method of water breeding material, to accelerate to advance the selection-breeding that harvest time water content is low, corn variety received by suitable machine.Especially because Semen Maydiss
Seed rate of water loss is related to many economical characters, is affected by many minor effect qtl, so the developmental research work of related ssr labelling
Make to be in progress relatively slowly, there is no the ssr with actual application value to apply the tag to corn breeding work at present.So, institute of the present invention
The method of the rapid evaluation corn dehydration speed providing, has more important Breeding value, particularly in mechanized harvest
So become today of Corn Industrialization major trend, the importance of this method also will increasingly highlight.
Claims (3)
1. a kind of based on regression model quickly measure Kernel Dry-down in Maize method it is characterised in that: set up corn kernel
Moisture ynRegression model, calculate corn kernel rate of water loss v=(yn-y1)/n, wherein v are rate of water loss, ynFor n-th
The water content of its corn kernel, y1For the water content of first day corn kernel, n is detection natural law；Described corn kernel moisture contains
Amount ynRegression model, using the determination of water to corn kernel+bract and corn kernel for the moisture test apparatus, by spss software
Dependency between analysis moisture analyzer reading and oven method measuring water content, draws scatterplot, sets up regression model: y=
95.709-2.29x+0.02x2, wherein x is the reading to corn kernel+bract for the moisture test apparatus, and y is the moisture of corn kernel
Content.
2. the corn kernel water content based on regression model as claimed in claim 1 rapid assay methods it is characterised in that:
The determination of water of described corn kernel+bract is that by bract, probe is inserted seed, and the moisture readings now measuring are Semen Maydiss
The water content of bract+seed.
3. a kind of method quickly measuring Kernel Dry-down in Maize based on regression model, for predicting live body corn ear seed
This economical character of water content, the fast excellent material of screening rate of water loss, as the application of corn breeding.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108731965A (en) * | 2018-05-22 | 2018-11-02 | 中国科学院东北地理与农业生态研究所 | A kind of singling measures the popcorn later stage to the sampling method of seed physiological maturity Grain filling rate |
| CN108731966A (en) * | 2018-05-22 | 2018-11-02 | 中国科学院东北地理与农业生态研究所 | A kind of singling measurement dynamic sampling method of later growth period Desiccated velocity |
| CN109557268A (en) * | 2018-10-30 | 2019-04-02 | 张桂萍 | A kind of in-site detecting method of corn kernel dehydration research |
| CN109618921A (en) * | 2018-12-06 | 2019-04-16 | 河北省农林科学院农业资源环境研究所 | A kind of method and application of the stress critical-temperature of identification zasiokaurin high temperature resistant |
| CN110024686A (en) * | 2019-05-30 | 2019-07-19 | 湖南省作物研究所 | A method of the corn variety of screening seed later period fast dewatering |
| CN112881480A (en) * | 2021-01-14 | 2021-06-01 | 中国农业大学 | Corn moisture nondestructive testing method and device |
-
2016
- 2016-09-30 CN CN201610867685.9A patent/CN106370551A/en active Pending
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108731965A (en) * | 2018-05-22 | 2018-11-02 | 中国科学院东北地理与农业生态研究所 | A kind of singling measures the popcorn later stage to the sampling method of seed physiological maturity Grain filling rate |
| CN108731966A (en) * | 2018-05-22 | 2018-11-02 | 中国科学院东北地理与农业生态研究所 | A kind of singling measurement dynamic sampling method of later growth period Desiccated velocity |
| CN109557268A (en) * | 2018-10-30 | 2019-04-02 | 张桂萍 | A kind of in-site detecting method of corn kernel dehydration research |
| CN109557268B (en) * | 2018-10-30 | 2021-06-08 | 张桂萍 | In-situ determination method for corn kernel dehydration research |
| CN109618921A (en) * | 2018-12-06 | 2019-04-16 | 河北省农林科学院农业资源环境研究所 | A kind of method and application of the stress critical-temperature of identification zasiokaurin high temperature resistant |
| CN110024686A (en) * | 2019-05-30 | 2019-07-19 | 湖南省作物研究所 | A method of the corn variety of screening seed later period fast dewatering |
| CN110024686B (en) * | 2019-05-30 | 2021-03-23 | 湖南省作物研究所 | Method for screening corn varieties with grains quickly dehydrated in later period |
| CN112881480A (en) * | 2021-01-14 | 2021-06-01 | 中国农业大学 | Corn moisture nondestructive testing method and device |
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