CN110068299A - A kind of calculation method of chamber crop leaf area index - Google Patents

Abstract

The invention relates to the field of greenhouse crops, in particular to a method for calculating the leaf area index of greenhouse crops. Each crop is divided into a top layer, a middle layer and a bottom layer according to the height from top to bottom, and the total number of leaves of each layer is respectively recorded in each measurement; Select the largest leaf and the smallest leaf in each layer to measure the characteristic length respectively, calculate the leaf area of the largest leaf and the leaf area of the smallest leaf in each layer, so as to obtain the average leaf area, and average the leaf area. The value is used as the representative leaf area of the leaf characteristics of the layer; the product value of the representative leaf area of each layer and the total number of leaves of the layer can be accumulated to obtain the total leaf area of a single crop, and the leaf area index of the crop can be obtained. The fitting value of the leaf area obtained by the invention has a very high fitting with the actual value, the obtained leaf area index has high accuracy, the measurement process is simple to operate, and the use of instruments and labor costs are low.

Description

A Calculation Method of Greenhouse Crop Leaf Area Index

technical field

The invention relates to the technical field of greenhouse crop research, in particular to a method for calculating the leaf area index of greenhouse crops.

Background technique

Leaf area index, also known as leaf area coefficient. Refers to the ratio of the total area of plant leaves to the land area. It is related to the density, structure (single or multi-layer) of vegetation, biological characteristics of trees (branch angle, leaf placement angle, shade tolerance, etc.) and environmental conditions (light, water, soil nutrient status), is It is a comprehensive indicator of vegetation utilization of light energy and canopy structure. However, due to the diversity of crops, the leaves of many crops grow rapidly during the growth period, and the direct measurement of leaf area requires a lot of work and requires high measuring instruments and methods. In order to find a more simple and effective method to calculate the leaf area index, I have studied the calculation method of the leaf area index of the main crops in the greenhouse through experimental research.

The specific method is as follows: select several representative plants in the experimental plot of the greenhouse, and measure their growth and development status at regular intervals on average. The measurement contents include: crop height, number of leaves, characteristic length of leaves, leaf area, etc. However, due to the increasing number of leaves during the growth and development of crops, the difficulty and workload of leaf area measurement will continue to increase, so the cost of input instruments and labor costs are too high, and the measurement process is too cumbersome.

SUMMARY OF THE INVENTION

Aiming at the defects and problems existing in the prior art, the present invention provides a method for calculating the leaf area index of greenhouse crops. High accuracy, simple measurement process, low instrument use and labor costs.

The scheme adopted by the present invention to solve its technical problem is:

A method for calculating the leaf area index of greenhouse crops. First, each crop is divided into three levels from top to bottom: top layer, middle layer and bottom layer, and the total number of leaves in each layer is recorded for each measurement; The characteristic lengths of the largest and smallest leaves in each layer are measured respectively, and the leaf area of the largest leaf and the smallest leaf in each layer are calculated respectively, so as to obtain the average leaf area, and the average leaf area is calculated. As the representative leaf area of the leaf characteristics of this layer; finally, the product value of the representative leaf area of each layer and the total number of leaves in this layer can be accumulated to obtain the total leaf area of a single crop; that is, the leaf area index of a crop can be calculated by the following formula to calculate:

where:

LAI - the leaf area index of the crop;

S _o - the area of the plot where the tested plant is located;

- the average leaf area per plant of representative crops;

m——the total number of plants in the plot;

in,

which is,

where:

j——number of representative crop sequences;

i——Number of layers of tested crops; among them, i=1 represents the top layer, i=2 represents the middle layer, and i=3 represents the bottom layer;

n _i — the total number of leaves on the i-th layer of the crop;

S _{max,ij ——the} maximum leaf area on the ith layer of the jth crop;

S _{min,ij ——the} minimum leaf area on the ith layer of the jth crop.

In the above-mentioned calculation method of the leaf area index of a greenhouse crop, the characteristic length of the leaf includes the maximum length in the radial direction of the leaf and the maximum width in the transverse direction of the leaf.

The calculation method of above-mentioned a kind of greenhouse crop leaf area index, the calculation method of the leaf area of the largest leaf and the smallest leaf in each layer is: at first, randomly pick 20-50 leaves in the mature stage of greenhouse crops, measure The maximum radial length and transverse width of each leaf, and the actual leaf area of each leaf was measured with a scanning leaf area meter; then, the correlation between the actual leaf area and the maximum radial length and transverse width of the leaf was established. Finally, calculate the leaf area of the largest blade and the smallest blade in each layer by solving the obtained correlation equation; where the product of the maximum radial length of the blade and the maximum width of the blade in the lateral direction is used as the independent variable Establish a single factor regression model, namely:

S=k·ab+c

where:

S - the actual leaf area of each leaf;

a——the maximum radial length of the blade;

b——the maximum lateral width of the leaf;

Using the values of the actual leaf area, the maximum radial length of the leaf and the maximum width of the leaf in the lateral direction of the randomly picked 20-50 leaves, the mathematical statistics software is used for analysis, the constant k and the constant c are obtained, and the leaf area calculation is obtained. equation.

The above-mentioned calculation method of the leaf area index of a greenhouse crop can also establish a binary linear regression model by using the product of the maximum radial length of the leaf and the maximum lateral width of the leaf as an independent variable, namely:

S=k ₁ ·a+k ₂ ·b+k ₃

where:

S - the actual leaf area of each leaf;

a——the maximum radial length of the blade;

b——the maximum lateral width of the leaf;

Using the values of the actual leaf area, the maximum radial length of the leaf and the maximum width of the leaf in the lateral direction of 20-50 randomly picked leaves, and using mathematical statistics software to analyze, obtain the constant k ₁ , constant k ₂ , and constant k ₃ , and obtain the leaf area calculation equation.

Beneficial effects of the present invention: a method for calculating the leaf area index of a greenhouse crop of the present invention is to establish an equation between the leaf characteristic length and the leaf area by sampling plants in layers, and calculate the leaf area index of the crop through the relevant equation formula. It can reduce the workload required for leaf area calculation as much as possible on the premise of using as little high-precision measuring instruments as possible, and at the same time effectively reduce the use of measuring instruments, simplifies the experimental process, and is conducive to different The research is carried out on the greenhouse test crops in the region. The calculation method is simple, the fitting data is reliable, and the fitting results between the calculated data and the actual measurement data are highly correlated and accurate.

Description of drawings

Figure 1 shows the correlation analysis of the fitting results using the binary linear regression model in the first scheme.

Figure 2 shows the correlation analysis of fitting results using a single factor regression model in Scheme 2.

Figure 3 is an analysis of the fitting results between the actual leaf area of the tomato and the calculated leaf area in Scheme 2.

Detailed ways

The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

Embodiment 1: a kind of calculation method of greenhouse crop leaf area index, concrete method is as follows:

Select 3 representative plants in the experimental plot of the greenhouse, and measure their growth and development status every 10 days on average. The measurement time is on the 1st, 11th, and 21st of each month. The measurement contents include: Crop height, number of leaves, characteristic length of leaves, leaf area, etc. Considering that during the growth and development of crops, as the number of leaves gradually increases, the difficulty and workload of leaf area measurement will continue to increase. Combined with the actual situation of our own experiments, the following methods are proposed to be measured:

First, each crop is divided into 3 levels from top to bottom according to height: top layer, middle layer, and bottom layer. In each measurement, the total number of leaves in each layer shall be recorded, and the largest and smallest leaves in each layer shall be selected to measure the characteristic length respectively, and then the average of the leaf areas of the two shall be taken as the representative leaf area of the leaf characteristics of this layer. Finally, the multiplication of the representative leaf area of each layer and the total number of leaves can be added up to obtain the total leaf area of a single crop.

So the leaf area index of the crop can be calculated by the following formula:

In the formula,

LAI - the leaf area index of the crop;

S _o - the area of the plot where the plant to be tested is located, mm ² ;

- the average leaf area per plant of representative crops, mm ² ;

m—the total number of plants in the plot.

in,

which is,

In the formula,

j——number of representative crop sequences;

i——Number of layers of tested crops (i=1 represents the top layer, i=2 represents the middle layer, and i=3 represents the bottom layer);

n _i — the total number of leaves on the i-th layer of the crop;

S _{max,ij ——the} maximum leaf area on the ith layer of the jth crop, mm ² ;

S _{min,ij ——the} minimum leaf area on the i-th layer of the j-th crop, mm ² ;

According to the above formula, the correctness of LAI calculation mainly depends on the measurement of leaf area. Taking greenhouse tomato as an example, firstly, 30 leaves were randomly picked at the tomato maturity stage, and their characteristic lengths (including: the maximum radial length of leaves and the maximum lateral width of leaves, hereinafter referred to as length and width) were measured, and a scanning leaf area meter was used. Determination of leaf area. Then, 20 groups of data were selected and analyzed by mathematical statistics software to establish a correlation equation between actual leaf area and leaf characteristic length, and the correlation equation was used to calculate the actual leaf area of tomato plants. In order to ensure the accuracy of the fitted value and the measured value, the remaining 10 groups of data were used as test samples in this experiment to analyze the fitting results.

In this paper, two schemes are used for regression analysis, and the results are compared:

Option 1: Establish a binary linear regression model using the maximum radial length of the leaf and the maximum lateral width of the leaf as independent influencing factors:

S=k ₁ ·a+k ₂ ·b+k ₃

Option 2: Use the product of the maximum radial length of the leaf and the maximum width of the leaf as an independent variable to establish a single-factor regression model:

S=k·ab+c

Both of these two schemes use the internal function regress of matlab to complete. The result obtained after the fitting of scheme 1 is shown in Figure 1, and the result obtained after fitting of scheme 2 is shown in Figure 2.

Through the regression analysis of 20 groups of measured data, it is obtained that the square of the correlation coefficient of the regression equation of the scheme one is R ² =0.9072, and the average relative error is RE = 0.1167; the square of the correlation coefficient of the regression equation of the scheme two is R ² =0.9144, The average relative error is RE=0.0965, as shown in Table 1.

Table 1 Comparison of results of fitting equations for tomato leaf area

It can be seen from the above chart that the correlation between the fitting results of the two schemes is relatively high.

However, considering that the relative error of the second solution is smaller, this embodiment will finally use the fitting equation obtained by the second solution to calculate the tomato leaf area.

The other 10 groups of data are brought into the regression equation of Scheme 2 for testing, and the fitting results are shown in Figure 3:

After inspection, the relative error between the fitting value and the measured value is RE=4.54%, and the fitting accuracy is EA ₌ 94.20%. The fitting accuracy of scheme 2 is higher, as shown in Table 2:

Table 2 Fitting results of tomato leaf area

Among them, the fitting accuracy is:

In the formula: E _A is the estimation accuracy; rmse is the total mean square error; is the mean value of the test point data.

Using the same comparison method, the leaf area fitting formulas of greenhouse tomatoes, cucumbers and eggplants are finally obtained as follows:

Greenhouse Tomatoes:

S=0.809·(ab)+892.17 (5)

Greenhouse Cucumbers:

S=0.6739·(ab)-601.34 (6)

Greenhouse Eggplant:

S=1.1055·(ab)-2135.9 (7)

Substituting equations (5)-(7) into equation (3), the calculation formulas of leaf area index of greenhouse tomato, cucumber and eggplant can be obtained as follows:

Greenhouse Tomatoes:

Greenhouse Cucumbers:

Greenhouse Eggplant:

After calculation, it was obtained that the leaf area index of tomato during the experiment was 0.98 at the seedling stage, 3.25 at the flowering and fruit setting stage, and 4.81 at the fruit maturity stage. The average value was 2.36; the greenhouse cucumber was 0.46 at the seedling stage, 1.74 at the flowering and fruit setting stage, and 2.11 at the fruit ripening stage.

Claims (4)

1. a method for calculating the leaf area index of greenhouse crops, is characterized in that: at first, each plant is divided into 3 levels by height from top to bottom: top layer, middle layer and bottom layer, respectively record each layer during each measurement. The total number of leaves; then, select the largest leaf and the smallest leaf in each layer to measure the characteristic length, respectively calculate the leaf area of the largest leaf and the smallest leaf in each layer, so as to obtain the average leaf area. , the average leaf area is used as the representative leaf area of the leaf characteristics of this layer; finally, the product value of the representative leaf area of each layer and the total number of leaves in this layer can be accumulated to obtain the total leaf area of a single crop; The leaf area index can be calculated by the following formula: where: LAI - the leaf area index of the crop; S _o - the area of the plot where the tested plant is located; - the average leaf area per plant of representative crops; m——the total number of plants in the plot; in, which is, where: j——number of representative crop sequences; i——Number of layers of tested crops; among them, i=1 represents the top layer, i=2 represents the middle layer, and i=3 represents the bottom layer; n _i — the total number of leaves on the i-th layer of the crop; S _{max,ij ——the} maximum leaf area on the ith layer of the jth crop; S _{min,ij ——the} minimum leaf area on the ith layer of the jth crop. 2 . The method for calculating the leaf area index of a greenhouse crop according to claim 1 , wherein the characteristic length of the blade includes the maximum length in the radial direction of the blade and the maximum width in the transverse direction of the blade. 3 . 3. the calculation method of a kind of greenhouse crop leaf area index according to claim 1, is characterized in that: the calculation method of the leaf area of leaf maximum person and blade minimum person in each layer is: at first, in greenhouse crop development and maturity Randomly pick 20-50 leaves, measure the maximum radial length and transverse width of each leaf, and use a scanning leaf area meter to measure the actual leaf area of each leaf; then, establish the actual leaf area and leaf radial The correlation equation between the maximum length and the maximum lateral width of the blade; finally, the leaf area of the largest blade and the smallest blade in each layer is calculated by solving the obtained correlation equation; among them, the largest blade radial The product of the length and the maximum lateral width of the leaf is used as an independent variable to establish a single factor regression model, namely: S=k·ab+c where: S - the actual leaf area of each leaf; a——the maximum radial length of the blade; b——the maximum lateral width of the leaf; Using the values of the actual leaf area, the maximum radial length of the leaf and the maximum width of the leaf in the lateral direction of the randomly picked 20-50 leaves, the mathematical statistics software is used for analysis, the constant k and the constant c are obtained, and the leaf area calculation is obtained. equation. 4. the calculating method of a kind of greenhouse crop leaf area index according to claim 3, is characterized in that: the product of leaf radial maximum length and leaf lateral maximum width can also set up binary linear regression model as independent variable, i.e. : S=k ₁ ·a+k ₂ ·b+k ₃ where: S - the actual leaf area of each leaf; a——the maximum radial length of the blade; b——the maximum lateral width of the leaf; Using the values of the actual leaf area, the maximum radial length of the leaf and the maximum width of the leaf in the lateral direction of 20-50 randomly picked leaves, and using mathematical statistics software to analyze, obtain the constant k ₁ , constant k ₂ , and constant k ₃ , and obtain the leaf area calculation equation.