CN104089922B - A kind of method estimating fresh leaves dry matter weight - Google Patents
A kind of method estimating fresh leaves dry matter weight Download PDFInfo
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- CN104089922B CN104089922B CN201410314497.4A CN201410314497A CN104089922B CN 104089922 B CN104089922 B CN 104089922B CN 201410314497 A CN201410314497 A CN 201410314497A CN 104089922 B CN104089922 B CN 104089922B
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Abstract
A kind of method that the invention discloses estimation fresh leaves dry matter weight that can improve field survey efficiency.The method only need to record fresh leaves spectral absorption x of any wave band in the range of spectral band 760 900nm, then carries it in formula y=A1*exp (x/t1)+y0, can record corresponding dry matter weight of leaf weight.The method is simple to operate, can quickly estimate dry matter weight value in blade, overcomes the shortcomings such as traditional measurement dry matter weight of leaf weight is loaded down with trivial details, waste time and energy, thus improves field measurement efficiency；The method can carry out field survey in the case of not changing blade biochemical component and not destroying blade construction simultaneously, avoid tradition to carry out sampling and dry the variation the measuring Leaf biochemical component impact on measurement result, improve the degree of accuracy measured, be suitable in blade biochemical component assay technical field popularization and application.
Description
Technical field
The present invention relates to blade biochemical component assay technical field, be specifically related to a kind of side estimating fresh leaves dry matter weight
Method.
Background technology
Forest fire is a kind of to have sudden big, the natural disaster of relief more difficulty strong, destructive.Ended for the end of the year 2010,
There are 7723 forest fires (fire disaster 22, wildfire 4) in China, the scene of a fire gross area 116.2 thousand hectares within the border,
Burned areas 45.8 thousand hectares, loss is grown into forest and is accumulated 740099.36 cubic metres, young growth strain number 29227.5 ten thousand strain, because of calamity
Cause 65 people's death, 43 people injured.
The moisture content of vegetation blade is to affect the key factor that forest fire occurs, and its computing formula is unit area lobes water content
Divided by dry matter weight.Vegetation dry matter weight of leaf weight, is briefly the weight removing leaf water rear blade unit are
(g/cm2).Evaluation forest fire, for indirectly calculating the propagation rate after vegetation lights probability and fire generation, is sent out by this parameter
Raw potential risk has important practical significance.The step of traditional measurement vegetation dry matter weight of leaf weight is: first-selected measurement vegetation leaf
Sheet area, dries and measures its weight the most in an oven, finally with this weight divided by leaf area obtain dry matter weight of leaf weight this
One parameter.As can be seen here, this measuring method need to carry out blade sampling, destroys blade construction, relatively complicated and waste time and energy, and adds
One side actual measure during the measurement error of blade area and dry weight inevitable, on the other hand sample experiment from the spot
During room is measured, blade biochemistry group branch changes, and finally affects the certainty of measurement of dry matter weight of leaf weight.
Summary of the invention
The technical problem to be solved is to provide a kind of estimation fresh leaves dry matter weight that can improve field survey efficiency
Method.
The present invention solves the method that above-mentioned technical problem be the technical scheme is that this estimation fresh leaves dry matter weight, including
Following steps: first, record fresh leaves spectral absorption x of any wave band in the range of spectral band 760-900nm, then
Bringing the blade absorbance x recorded into following formula and can record fresh leaves dry matter weight y, described formula is:
Y=A1*exp (-x/t1)+y0, wherein A1 value is 0.0989～0.02498, and t1 value is-2.40432～-0.33885,
Y0 value is-0.278～-0.0281.
Further, described spectral absorption x is to record at 830nm at spectral band.
Further, described A1 value is 0.02919.
Further, described t1 value is-0.37279.
Further, described y0 value is-0.03276.
Beneficial effects of the present invention: the method for estimation fresh leaves dry matter weight of the present invention and traditional measurement dry matter weight of leaf
Weight is loaded down with trivial details, waste time and energy and be easily generated the method for measurement error compares, and method of the present invention only need to record fresh leaves
In the range of spectral band 760-900nm, spectral absorption x of any wave band, then carries it into formula
In y=A1*exp (-x/t1)+y0, can record corresponding dry matter weight of leaf weight, the method is simple to operate, can quickly estimate
Dry matter weight value in blade, overcomes the shortcomings such as traditional measurement dry matter weight of leaf weight is loaded down with trivial details, waste time and energy, thus improves
Field measurement efficiency；And the method can carry out reality in the case of not changing blade biochemical component and not destroying blade construction
Ground is measured, it is to avoid tradition carries out the impact drying the variation measuring Leaf biochemical component to measurement result of sampling, and improves measurement
Degree of accuracy.
Detailed description of the invention
At present, in order to record vegetation dry matter weight of leaf weight, it is all first to measure vegetation blade area, dries the most in an oven also
Measure its weight, finally obtain this parameter of dry matter weight of leaf weight by this weight divided by leaf area.This measuring method need to carry out leaf
Sheet is sampled, and destroys blade construction, and toasts the needs substantial amounts of time, weighs and the most more bother, waste time and energy.Meanwhile, this
Planting measuring method measurement error of blade area and dry weight during measuring inevitable, measurement effect is poor；Additionally, from reality
Sample laboratory measurement during, blade biochemistry group branch changes, and the measurement finally affect dry matter weight of leaf weight is smart
Degree, it is impossible to accomplishing field survey, measurement result degree of accuracy is relatively low.In order to solve the problems referred to above, the invention provides one can
The method improving fresh leaves dry matter weight field survey efficiency.Specifically, the method for this estimation fresh leaves dry matter weight,
Comprise the following steps: first, record fresh leaves spectral absorption x of any wave band in the range of spectral band 760-900nm,
Then bringing the blade absorbance x recorded into following formula and can record fresh leaves dry matter weight y, described formula is:
Y=A1*exp (-x/t1)+y0, wherein A1 value is 0.0989～0.02498, and t1 value is-2.40432～-0.33885,
Y0 value is-0.278～-0.0281.
The method of estimation fresh leaves dry matter weight of the present invention is loaded down with trivial details with traditional measurement dry matter weight of leaf weight, waste time and energy
And the method being easily generated measurement error compares, method of the present invention only need to record fresh leaves at spectral band 760-900nm
In the range of spectral absorption x of any wave band, then carry it in formula y=A1*exp (-x/t1)+y0, phase can be recorded
The dry matter weight of leaf weight answered, the method is simple to operate, can quickly estimate dry matter weight value in blade, overcome traditional measurement
The shortcomings such as dry matter weight of leaf weight is loaded down with trivial details, waste time and energy, thus improve field measurement efficiency；And the method can be not
Field survey is carried out, it is to avoid tradition carries out sampling dries in measurement in the case of changing blade biochemical component and not destroying blade construction
The variation of the blade biochemical component impact on measurement result, improves the degree of accuracy measured.
Above-mentioned formula can be by according to PROSPECT modeling dry matter weight of leaf weight blade in 760-900nm spectral region
Absorbance, draws substantial amounts of data, then carries out exponential fitting and forms.In order to improve estimation precision, described spectral absorption x
Being to record at 830nm at spectral band, further, described A1 value is preferably 0.02919, and described t1 value is preferred
For-0.37279, described y0 value is preferably-0.03276.The formula determined by above-mentioned parameter determines this formula after checking
Coefficient of determination R2 is 0.91, estimates precision ± 0.0034g/cm2, wherein, it is determined that coefficient is total in total sum of squares equal to regression sum of square
Shared ratio, i.e. regression equation the percentage ratio of construable dependent variable variability, it is determined that coefficient closer to 1, independent variable pair
The explanation degree of dependent variable is the highest, and the percentage ratio that the variation that independent variable causes accounts for total variation is high, and point of observation is got near regression straight line
Intensive；Estimation precision refers to the error between estimator and actual value, and from above-mentioned numerical value, the degree of accuracy of this formula is higher,
Estimation effect is preferable.
Claims (5)
1. the method estimating fresh leaves dry matter weight, it is characterised in that comprise the following steps: first, records fresh leaves and exists
Spectral absorption x of any wave band in the range of spectral band 760-900nm, then brings into following by the blade absorbance x recorded
Formula can record fresh leaves dry matter weight y, and described formula is: y=A1*exp (-x/t1)+y0, and wherein A1 value is
0.0989～0.02498, t1 value is-2.40432～-0.33885, and y0 value is-0.278～-0.0281.
2. the method estimating fresh leaves dry matter weight as claimed in claim 1, it is characterised in that: described spectral absorption x
It is to record at 830nm at spectral band.
3. the method estimating fresh leaves dry matter weight as claimed in claim 2, it is characterised in that: described A1 value is
0.02919。
4. the method estimating fresh leaves dry matter weight as claimed in claim 3, it is characterised in that: described t1 value is
-0.37279。
5. the method estimating fresh leaves dry matter weight as claimed in claim 4, it is characterised in that: described y0 value is
-0.03276。
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| CN201410314497.4A CN104089922B (en) | 2014-07-03 | 2014-07-03 | A kind of method estimating fresh leaves dry matter weight |
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| CN104089922A CN104089922A (en) | 2014-10-08 |
| CN104089922B true CN104089922B (en) | 2016-08-31 |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106124450A (en) * | 2016-06-16 | 2016-11-16 | 浙江大学 | The assay method of awns platymiscium dry matter weight of leaf |
| CN109856139B (en) * | 2019-01-07 | 2021-08-06 | 北京林业大学 | Tree leaf quantity estimation method and system |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102878957A (en) * | 2012-09-26 | 2013-01-16 | 安徽大学 | Leaf area index and chlorophyll content inversion method based on remote sensing image optimization PROSAIL model parameters |
| CN103592230A (en) * | 2013-10-30 | 2014-02-19 | 浙江大学 | Detection method of dry matter contents in tea |
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2014
- 2014-07-03 CN CN201410314497.4A patent/CN104089922B/en not_active Expired - Fee Related
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102878957A (en) * | 2012-09-26 | 2013-01-16 | 安徽大学 | Leaf area index and chlorophyll content inversion method based on remote sensing image optimization PROSAIL model parameters |
| CN103592230A (en) * | 2013-10-30 | 2014-02-19 | 浙江大学 | Detection method of dry matter contents in tea |
Non-Patent Citations (3)
| Title |
|---|
| 基于PROSPECT+SAIL模型的遥感叶面积指数反演;蔡博峰等;《国土资源遥感》;20070615(第72期);39-43 * |
| 基于光谱理论的作物营养诊断研究进展;王磊等;《植物营养与肥料学报》;20061231;第12卷(第6期);902-912 * |
| 干旱区草原地上植被生物量估算——以乌图美仁大草原芦苇植被为例;行敏锋等;《地球信息科学学报》;20140331;第16卷(第2期);335-340 * |
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