CN105447317A - Analysis method for crop climate yield potential - Google Patents

Abstract

The invention provides an analysis method for crop climate yield potential. The method comprises: constructing a crop climate yield potential analysis model; when total climate yield potential corresponding to a specified time length in a cotton growth period needs to be analyzed, inputting start time data and end time data into the climate yield potential analysis model obtained in the step 1; and outputting the total climate yield potential in the analyzed time period. The method has the advantages that (1) a daily water demand, a daily water supply and demand balance amount and a daily precipitation correction coefficient obtained through calculation by functional approximation better meet actual conditions of a daily water demand in a crop growth process; and (2) the total climate yield potential is obtained by accumulating the daily climate yield potential, so that a forming process of the crop climate yield potential can be reflected, a crop dry matter accumulation state can be accurately reflected, and the accuracy and objectivity of the climate yield potential can be improved.

Description

The analytical approach of crop climate yield potentiality

Technical field

The invention belongs to agricultural resource studying technological domain, be specifically related to a kind of analytical approach of crop climate yield potentiality.

Background technology

Crop climate yield potentiality refers to fully and light, heat, the water climate resources of Appropriate application locality, and other conditions, as the highest biological yield that unit area soil when soil, nutrient etc. are in optimum situation obtains or farm output.Therefore, solar radiation energy, crop photosynthesis characteristic, temperature condition become the Fundamentals that crop yield is formed.Climate yields potentiality reflect the basic potentiality that somewhere agricultural production under specific Climatic possesses, can the configuration of quantitatively characterizing regional climate resource situation and climatic elements thereof, be one of the important indicator that science weighs region grain-production power, agricultural development and population bearing capacity.

The computing method of tradition climate yields potentiality are:

Y _w＝Y _T*f(W)；

Wherein, Y _wfor climate yields potentiality total in Crop growing stage; Y _tfor light temperature yield potentiality total in Crop growing stage; F (W) is moisture correction factor.

Visible, when calculating climate yields potentiality, the determination of moisture correction factor belongs to crucial.And conventional aqueous correction factor f (W) determines by the following method:

$f\left(W\right)=\left\{\begin{array}{cc}R/E_0& R\&le;E_0\\ 1-(R-E_0)/3E_0& E_0<R<4E_0\\ 0& R\&GreaterEqual;4E_0\end{array}\right.$

Wherein, R is gross precipitation in Crop growing stage, and unit is mm, E ₀for total evaporation in Crop growing stage, unit is mm.

As can be seen here, in the calculating of conventional aqueous correction factor, because the parameter considered is total evaporation in gross precipitation and Crop growing stage in Crop growing stage, therefore, the moisture correction factor calculated is actually the total correction factor of Crop growing stage, the Affected By Gradual Change process to climate yields potentiality because service position every day develops cannot be reflected, be not inconsistent with crop Dry Matter Production accumulative process, so, the accuracy of the climate yields potentiality adopting classic method to obtain is very limited, usually serious with actual conditions deviation.

Summary of the invention

For the defect that prior art exists, the invention provides a kind of analytical approach of crop climate yield potentiality, effectively can improve the accuracy and objectivity of analyzing the climate yields potentiality obtained.

The technical solution used in the present invention is as follows:

The invention provides a kind of analytical approach of crop climate yield potentiality, comprise the following steps:

Step 1, build crop climate Potential Production Analysis model, described crop climate Potential Production Analysis model representation is:

Y _w＝ΣY _wi(1)

Wherein:

Y _wi＝r _i·y _i(2)

$r_i=1-{\log }_{25}^{(1+|p_i\left|\right)}---\left(3\right)$

p _i＝0.6p _i-1-w _i+d _i（4）

$w_i=w_m+(w_{m+1}-w_m)\&CenterDot;{\log }_{31}^n---\left(5\right)$

Wherein: Y _w-analyze total climate yields potentiality in Period Length;

Y _widay climate yields potentiality in-analysis Period Length;

R _i-daily precipitation correction coefficient;

Y _i-sunlight yield potentiality;

P _i-moisture supply and demand unspent amount;

P _i-1moisture supply and demand-yesterday unspent amount;

W _i-water requirement;

W _m-of that month first day water requirement;

W _m+1the first day-next month water requirement;

In the n-month day sequence, its value is maximum is no more than 31;

D _i-the same day actual quantity of precipitation;

Step 2, when total climate yields potentiality in Water demand cotton development stage corresponding to fixed time length, build to step 1 in the climate yields Potentials model obtained input start time data and closing time data;

Step 3, climate yields Potentials model was designated as i-th day jth moon by initial time to the time period of closing time any one day after receiving start time data and closing time data, then, read the of that month first day water requirement w of pre-stored _mwith first day next month water requirement w _m+1value, and to substitute in formula (5), calculate a day water requirement w _i; Wherein, n=i;

Step 4, reads actual quantity of precipitation d on the same day _iwith moisture supply and demand yesterday unspent amount p _i-1, by day water requirement w _i, the same day actual quantity of precipitation d _iwith moisture supply and demand yesterday unspent amount p _i-1substitute into formula (4), calculate a day moisture supply and demand unspent amount p _i; Herein, for the 1st day of the analyzed time period, moisture supply and demand yesterday unspent amount is made to be 0;

Step 5, by day moisture supply and demand unspent amount p _isubstitute into formula (3), calculate daily precipitation correction coefficient r _i;

Step 6, reads the sunlight yield potentiality y of pre-stored _i, by sunlight yield potentiality y _iwith daily precipitation correction coefficient r _isubstitute into formula (2), calculate a day climate yields potentiality Y _wi;

Step 7, repeats step 3-step 6, calculates the day climate yields potentiality of every day in the analyzed time period, then, based on formula (1), the day climate yields potentiality in each sky calculated are done summation operation, namely obtain the total climate yields potentiality in the analyzed time period;

Step 8, the total climate yields potentiality in the analyzed time period that output step 7 obtains.

Preferably, in step 3, the value of each first day moon water requirement of pre-stored is in table 1:

Table 1 cotton each first day moon water requirement

Wherein, the breeding time due to cotton is the 5-9 month, so table 1 stores each first day moon water requirement in the 5-9 month.

Preferably, in step 3, the sunlight yield potentiality y read _iobtain by the following method:

Step 3.1, reads the base point temperature of the analyzed moon three of pre-stored, is respectively the preference temperature T of cotton at current period ₁, the minimum temperature T that can bear ₂and the maximum temperature T that can bear ₃; Read a day actual average temperature T again _i;

Step 3.2, by T _1,t ₂, T ₃and T _isubstitute into formula (6), calculate degree/day correction factor F _i;

$F_i=\frac{(T_i-T_2){(T_3-T_i)}^B}{(T_1-T_2){(T_3-T_1)}^B}---\left(6\right)$

Wherein, B=(T ₃-T ₁)/(T ₁-T ₂);

Step 3.3, reads the day the highest real air temperature T of pre-stored _u, by the highest for day real air temperature T _usubstitute into formula (7), calculate daily maximum temperature correction factor V _i;

V _i＝(1-l _i ²) ²⁵-29l _i ²

Wherein:

$l_i={\log }_{26}^{T_u}(1-{\log }_{26}^{T_u})---\left(7\right)$

Step 3.4, by daily maximum temperature correction factor V _iwith degree/day correction factor F _isubstitute into formula (8), calculate light temperature yield potentiality day correction factor t _i;

t _i＝0.3V _i+0.7F _i(8)

Step 3.5, reads the day photosynthetic yield potentiality h of pre-stored _i, by t _iand h _isubstitute into formula (9), calculate sunlight yield potentiality y _i;

y _i＝t _i·h _i(9)。

Preferably, in step 3.5, the day read photosynthetic yield potentiality h _iobtain by the following method:

Step 3.5.1, sets up each first day moon weight coefficient table in breeding time;

Step 3.5.2, reads described each first day moon weight coefficient table, obtains of that month first day weight v _mwith first day next month weight v _m+1, then by the first day in this month weight v _mwith first day next month weight v _m+1substitute into formula (10), calculate a day weight v _i:

$v_i=v_m+(v_{m+1}-v_m)\&CenterDot;{\log }_{31}^n---\left(10\right)$

Wherein, n be in the moon day sequence, n=i;

Step 3.5.3, reads the day radiation G of pre-stored, by day radiation G and day weight v _isubstitute into formula (11), calculate day photosynthetic yield potentiality h _i:

h _i＝v _i·G(11)。

Preferably, step 3.5.1, each first day moon weight coefficient table set up is in table 2:

The table 2 cotton photosynthetic potentiality moon first day weight

Wherein, v ₄, v ₅, v ₆, v ₇, v ₈, v ₉and v ₁₀be respectively the first day in April weight, the first day in May weight, the first day in June weight, the first day in July weight, the first day in August weight, the first day in September weight and the first day in October weight.

The analytical approach of crop climate yield potentiality provided by the invention has the following advantages:

(1) the day water requirement adopting approximation of function to calculate, day moisture supply and demand unspent amount and daily precipitation correction coefficient, more meet the actual conditions of the Sino-Japan water requirement of process of crop growth;

(2) by day climate yields potentiality accumulation obtain total climate yields potentiality, the forming process of crop climate yield potentiality can be reflected, accurately reflect crop dry-matter accumulation state, improve accuracy and the objectivity of climate yields potentiality.

Accompanying drawing explanation

Fig. 1 is the correlation curve figure of the moisture update the system that classic method and the inventive method are formed;

Fig. 2 is Cotton climatic output potentiality zoning map provided by the invention;

Fig. 3 is cotton light temperature yield potentiality zoning map provided by the invention;

Fig. 4 is cotton photosynthetic yield potentiality zoning map provided by the invention;

Fig. 5 is the variation diagram of 1971-1975 Cotton climatic output potentiality provided by the invention;

Fig. 6 is the variation diagram of 2002-2006 Cotton climatic output potentiality provided by the invention.

Embodiment

In order to make technical matters solved by the invention, technical scheme and beneficial effect clearly understand, below in conjunction with drawings and Examples, the present invention is further elaborated.Should be appreciated that specific embodiment described herein only in order to explain the present invention, be not intended to limit the present invention.

The invention provides a kind of analytical approach of crop climate yield potentiality, comprise the following steps:

Step 1, build crop climate Potential Production Analysis model, described crop climate Potential Production Analysis model representation is:

Y _w＝ΣY _wi(1)

Wherein:

Y _wi＝r _i·y _i(2)

$r_i=1-{\log }_{25}^{(1+|p_i\left|\right)}---\left(3\right)$

p _i＝0.6p _i-1-w _i+d _i(4)

$w_i=w_m+(w_{m+1}-w_m)\&CenterDot;{\log }_{31}^n---\left(5\right)$

Wherein: Y _w-analyze total climate yields potentiality in Period Length;

Y _widay climate yields potentiality in-analysis Period Length;

R _i-daily precipitation correction coefficient;

Y _i-sunlight yield potentiality;

P _i-moisture supply and demand unspent amount;

P _i-1moisture supply and demand-yesterday unspent amount;

W _i-water requirement;

W _m-of that month first day water requirement;

W _m+1the first day-next month water requirement;

In the n-month day sequence, its value is maximum is no more than 31;

D _i-the same day actual quantity of precipitation;

Step 2, when total climate yields potentiality in Water demand cotton development stage corresponding to fixed time length, build to step 1 in the climate yields Potentials model obtained input start time data and closing time data;

Step 3, climate yields Potentials model was designated as i-th day jth moon by initial time to the time period of closing time any one day after receiving start time data and closing time data, then, read the of that month first day water requirement w of pre-stored _mwith first day next month water requirement w _m+1value, and to substitute in formula (5), calculate a day water requirement w _i; Wherein, n=i;

In this step, the value of each first day moon water requirement of pre-stored is in table 1:

Table 1 cotton each first day moon water requirement

Wherein, the breeding time due to cotton is the 5-9 month, so table 1 stores each first day moon water requirement in the 5-9 month.

Step 4, reads actual quantity of precipitation d on the same day _iwith moisture supply and demand yesterday unspent amount p _i-1, by day water requirement w _i, the same day actual quantity of precipitation d _iwith moisture supply and demand yesterday unspent amount p _i-1substitute into formula (4), calculate a day moisture supply and demand unspent amount p _i; Herein, for the 1st day of the analyzed time period, moisture supply and demand yesterday unspent amount is made to be 0;

Step 5, by day moisture supply and demand unspent amount p _isubstitute into formula (3), calculate daily precipitation correction coefficient r _i;

Step 6, reads the sunlight yield potentiality y of pre-stored _i, by sunlight yield potentiality y _iwith daily precipitation correction coefficient r _isubstitute into formula (2), calculate a day climate yields potentiality Y _wi;

Step 7, repeats step 3-step 6, calculates the day climate yields potentiality of every day in the analyzed time period, then, based on formula (1), the day climate yields potentiality in each sky calculated are done summation operation, namely obtain the total climate yields potentiality in the analyzed time period;

Step 8, the total climate yields potentiality in the analyzed time period that output step 7 obtains.

Such as, when needing total climate yields potentiality of adding up a certain area in this time period of 2015.5.1 to 2015.9.1, only needs are 2015.5.1 to crop climate Potential Production Analysis mode input initial time, closing time is these two data of 2015.9.1, and crop climate Potential Production Analysis model can calculate total climate yields potentiality in this interval automatically.Circular is:

(1) for any one day, as 2015.8.3, first day water requirement is calculated by formula 5.

Day water requirement=2015.8.1 water requirement+(the 2015.9.1 water requirement-2015.8.1 water requirement) of 8.3 these days

As can be seen from above-mentioned formula, adopt formula 5 when calculating day water requirement, for the day water requirement of the same moon each day, from the of that month first day, day water requirement increase gradually with function parabolic, and constantly approach the day water requirement of first day next month.Adopt this computing method, more meet the actual demand of cotton growth stage to water requirement.

(2) then, the day moisture supply and demand unspent amount of this day of 2015.8.3 is calculated, that is:

2015.8.3 the day actual quantity of precipitation of the day water requirement+2015.8.3 of day moisture supply and demand unspent amount=0.6 (the day moisture supply and demand unspent amount of this day of the 2015.8.2)-2015.8.3 of this day.

(3) formula 3 is adopted to calculate the daily precipitation correction coefficient of this day of 2015.8.3.

(4) by this day of 2015.8.3 sunlight yield potentiality and daily precipitation correction coefficient substitute into formula 2, calculate the day climate yields potentiality of this day of 2015.8.3.

(5) for this time period of 2015.5.1 to 2015.9.1, adopt said method to calculate the day climate yields potentiality of every day, then sue for peace, namely obtain total climate yields potentiality of this time period.

In same output situation, if adopt the computing method of traditional moisture correction factor, Fig. 1 middle polyline curve can be obtained; And if adopt method of the present invention, daily precipitation correction coefficient is parabolic in Fig. 1.Observe Fig. 1, can find out, classic method has 3 shortcomings: the first, adopt megastage quantity of precipitation, as monthly per ten days precipitation, instead of every day precipitation, thus blocked the possibility that real-time follow-up calculates yield potentiality; The second, megastage precipitation adds up, and is equivalent to use average precipitation, does not reflect the differentiation of service position completely, accumulates environment be not inconsistent with crop Dry Matter Production; Three, adopt threshold interval to divide fixing correction factor, outer unification as interval in interval internal fixtion value is 0, does not also meet the accumulation of crop Dry Matter Production actual.And of the present invention improving one's methods overcomes above-mentioned three defects completely, truly can reflect that moisture supply environment changes the change of the yield potentiality brought.

The analytical approach of crop climate yield potentiality provided by the invention, innovative point is as follows:

(1) the day water requirement adopting approximation of function to calculate, more meets the actual conditions of the Sino-Japan water requirement of process of crop growth;

(2) approximation computation day moisture supply and demand unspent amount, result of calculation more meets the actual conditions of process of crop growth Sino-Japan moisture supply and demand surplus;

(3) injury that causes of approximation computation moisture off-target state, namely truly calculates daily precipitation correction coefficient;

(4) by day climate yields potentiality accumulation obtain total climate yields potentiality, the forming process of crop climate yield potentiality can be reflected, accurately reflect crop dry-matter accumulation state, improve accuracy and the objectivity of climate yields potentiality.

(5) due to the day climate yields potentiality of every day can be calculated, be convenient to calculate the automation application such as monitoring in real time every day;

(6) fields such as crop yield monitoring, agricultural production resources assessment, Resources Evolution and early warning are applicable to.

In addition, the present invention has following two innovations greatly:

Innovation one: sunlight yield potentiality

In above-mentioned steps 3, the sunlight yield potentiality y read _iobtain by the following method:

Step 3.1, reads the base point temperature of the analyzed moon three of pre-stored, is respectively the preference temperature T of cotton at current period ₁, the minimum temperature T that can bear ₂and the maximum temperature T that can bear ₃; Read a day actual average temperature T again _i;

Step 3.2, by T _1,t ₂, T ₃and T _isubstitute into formula (6), calculate degree/day correction factor F _i;

$F_i=\frac{(T_i-T_2){(T_3-T_i)}^B}{(T_1-T_2){(T_3-T_1)}^B}---\left(6\right)$

Wherein, B=(T ₃-T ₁)/(T ₁-T ₂);

Step 3.3, reads the day the highest real air temperature T of pre-stored _u, by the highest for day real air temperature T _usubstitute into formula (7), calculate daily maximum temperature correction factor V _i;

V _i＝(1-l _i ²) ²⁵-29l _i ²

Wherein:

$l_i={\log }_{26}^{T_u}(1-{\log }_{26}^{T_u})---\left(7\right)$

Step 3.4, by daily maximum temperature correction factor V _iwith degree/day correction factor F _isubstitute into formula (8), calculate light temperature yield potentiality day correction factor t _i;

t _i＝0.3V _i+0.7F _i(8)

Step 3.5, reads the day photosynthetic yield potentiality h of pre-stored _i, by t _iand h _isubstitute into formula (9), calculate sunlight yield potentiality y _i;

y _i＝t _i·h _i(9)。

Innovation two: day photosynthetic yield potentiality

In step 3.5, the day read photosynthetic yield potentiality h _iobtain by the following method:

Step 3.5.1, sets up each first day moon weight coefficient table in breeding time;

Step 3.5.1, each first day moon weight coefficient table set up is in table 2:

The table 2 cotton photosynthetic potentiality moon first day weight

Wherein, v ₄, v ₅, v ₆, v ₇, v ₈, v ₉and v ₁₀be respectively the first day in April weight, the first day in May weight, the first day in June weight, the first day in July weight, the first day in August weight, the first day in September weight and the first day in October weight.

Step 3.5.2, reads described each first day moon weight coefficient table, obtains of that month first day weight v _mwith first day next month weight v _m+1, then by the first day in this month weight v _mwith first day next month weight v _m+1substitute into formula (10), calculate a day weight v _i:

$v_i=v_m+(v_{m+1}-v_m)\&CenterDot;{\log }_{31}^n---\left(10\right)$

Wherein, n be in the moon day sequence, n=i;

Step 3.5.3, reads the day radiation G of pre-stored, by day radiation G and day weight v _isubstitute into formula (11), calculate day photosynthetic yield potentiality h _i:

h _i＝v _i·G(11)。

Test example 1

For Huang-Huai-Hai, day by day the climatological data of statistics 51 website 1971-2006, calculate the light temperature yield potentiality of each website, photosynthetic yield potentiality and weather yield potentiality respectively, then expand according to inverse distance and contiguous principle of similarity the light temperature yield potentiality, photosynthetic yield potentiality and the weather yield potentiality that calculate all the other level administrative areas, 383 counties and cities.Result of calculation ArcMap maps, and forms corresponding zoning map.The results are shown in Figure 2, Fig. 3 and Fig. 4, be respectively Cotton climatic output potentiality zoning map, cotton light temperature yield potentiality zoning map, cotton photosynthetic yield potentiality zoning map.

Observe Fig. 2, Fig. 3 and Fig. 4, can find out, climate yields potentiality minimum value 1506kghm in district ^-2, maximal value 1874kghm ^-2, difference is little.The general trend of climate yields potential value be except Jiaodong Peninsula from southwest northeastward direction progressively increase, close with the variation tendency of light temperature yield potentiality zoning map and photosynthetic yield potentiality zoning map, and consistent with the climate yields variation tendency of reality, thus demonstrate the accuracy of climate yields Potentials method provided by the invention.

Test example 2

According to 5 years weather datas day by day before and after in the Huang-Huai-Hai 1971-2006 term, calculate climate yields potentiality in 1971-1975 and 2002-2006 two time period respectively, the differentiation situation of the climate yields potentiality of these two time periods of comparative analysis, as shown in Figure 5, be the variation diagram of 1971-1975 Cotton climatic output potentiality; As shown in Figure 6, be the variation diagram of 2002-2006 Cotton climatic output potentiality.

Comparison diagram 5 and Fig. 6 can see, the highest climate yields REGION OF WATER INJECTION OILFIELD, Huang-Huai-Hai is the transfer of northern direction eastwards.Optimum climate yield potentiality value is from the 2042kghm of 1971-1975 ^-2drop to the 1930kghm of 2002-2006 ^-2, meanwhile, minimum climate yields potentiality are from the 1479kghm of 1971-1975 ^-2drop to the 1328kghm of 2002-2006 ^-2, decline 5.5% and 10.2% respectively.Wherein terrestrial radiation maximal value declines 8.6%, and minimum value declines 12.8%; Photosynthetic yield value decline 7.6% with the largest potentiality, minimum value declines 17.2%; Light temperature yield potentiality maximal value declines 10.4%, and minimum value declines 13.4%.From the region change conditions of yield potentiality, itself and actual Cotton Production layout evolving trend are basically identical.

The research of Huang-Huai-Hai Cotton climatic output potentiality, effective evaluation can not only be carried out to regional Climate-Ecology Suitability, and deeply can disclose climatic factor from different places to the influence degree of producing, thus prospective evaluation is made to the development of region Cotton Production and the differentiation of production distribution, to National agricultural and Cotton Production, there is important guiding effect.

The above is only the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the premise without departing from the principles of the invention; can also make some improvements and modifications, these improvements and modifications also should look protection scope of the present invention.

Claims (5)

1. an analytical approach for crop climate yield potentiality, is characterized in that, comprises the following steps:

Step 1, build crop climate Potential Production Analysis model, described crop climate Potential Production Analysis model representation is:

Y _w＝ΣY _wi(1)

Wherein:

Y _wi＝r _i·y _i(2)

$r_i=1-{\log }_{25}^{\left(1+\left|p_i\right|\right)}---\left(3\right)$

p _i＝0.6p _i-1-w _i+d _i(4)

$w_i=w_m+(w_{m+1}-w_m)\&CenterDot;{\log }_{31}^n---\left(5\right)$

Wherein: Y _w-analyze total climate yields potentiality in Period Length;

Y _widay climate yields potentiality in-analysis Period Length;

R _i-daily precipitation correction coefficient;

Y _i-sunlight yield potentiality;

P _i-moisture supply and demand unspent amount;

P _i-1moisture supply and demand-yesterday unspent amount;

W _i-water requirement;

W _m-of that month first day water requirement;

W _m+1the first day-next month water requirement;

In the n-month day sequence, its value is maximum is no more than 31;

D _i-the same day actual quantity of precipitation;

Step 2, when total climate yields potentiality in Water demand cotton development stage corresponding to fixed time length, build to step 1 in the climate yields Potentials model obtained input start time data and closing time data;

Step 3, climate yields Potentials model was designated as i-th day jth moon by initial time to the time period of closing time any one day after receiving start time data and closing time data, then, read the of that month first day water requirement w of pre-stored _mwith first day next month water requirement w _m+1value, and to substitute in formula (5), calculate a day water requirement w _i; Wherein, n=i;

Step 4, reads actual quantity of precipitation d on the same day _iwith moisture supply and demand yesterday unspent amount p _i-1, by day water requirement w _i, the same day actual quantity of precipitation d _iwith moisture supply and demand yesterday unspent amount p _i-1substitute into formula (4), calculate a day moisture supply and demand unspent amount p _i; Herein, for the 1st day of the analyzed time period, moisture supply and demand yesterday unspent amount is made to be 0;

Step 5, by day moisture supply and demand unspent amount p _isubstitute into formula (3), calculate daily precipitation correction coefficient r _i;

Step 6, reads the sunlight yield potentiality y of pre-stored _i, by sunlight yield potentiality y _iwith daily precipitation correction coefficient r _isubstitute into formula (2), calculate a day climate yields potentiality Y _wi;

Step 7, repeats step 3-step 6, calculates the day climate yields potentiality of every day in the analyzed time period, then, based on formula (1), the day climate yields potentiality in each sky calculated are done summation operation, namely obtain the total climate yields potentiality in the analyzed time period;

Step 8, the total climate yields potentiality in the analyzed time period that output step 7 obtains.

2. the analytical approach of crop climate yield potentiality according to claim 1, is characterized in that, in step 3, the value of each first day moon water requirement of pre-stored is in table 1:

Table 1 cotton each first day moon water requirement

Wherein, the breeding time due to cotton is the 5-9 month, so table 1 stores each first day moon water requirement in the 5-9 month.

3. the analytical approach of crop climate yield potentiality according to claim 1, is characterized in that, in step 3, and the sunlight yield potentiality y read _iobtain by the following method:

Step 3.1, reads the base point temperature of the analyzed moon three of pre-stored, is respectively the preference temperature T of cotton at current period ₁, the minimum temperature T that can bear ₂and the maximum temperature T that can bear ₃; Read a day actual average temperature T again _i;

Step 3.2, by T _1,t ₂, T ₃and T _isubstitute into formula (6), calculate degree/day correction factor F _i;

$F_i=\frac{(T_i-T_2){(T_3-T_i)}^B}{(T_1-T_2){(T_3-T_1)}^B}---\left(6\right)$

Wherein, B=(T ₃-T ₁)/(T ₁-T ₂);

Step 3.3, reads the day the highest real air temperature T of pre-stored _u,by the highest for day real air temperature T _usubstitute into formula (7), calculate daily maximum temperature correction factor V _i;

V _i＝(1-l _i ²) ²⁵-29l _i ²

Wherein:

$l_i={\log }_{26}^{T_u}(1-{\log }_{26}^{T_u})---\left(7\right)$

Step 3.4, by daily maximum temperature correction factor V _iwith degree/day correction factor F _isubstitute into formula (8), calculate light temperature yield potentiality day correction factor t _i;

t _i＝0.3V _i+0.7F _i(8)

Step 3.5, reads the day photosynthetic yield potentiality h of pre-stored _i, by t _iand h _isubstitute into formula (9), calculate sunlight yield potentiality y _i;

y _i＝t _i·h _i(9)。

4. the analytical approach of crop climate yield potentiality according to claim 3, is characterized in that, in step 3.5, and the day read photosynthetic yield potentiality h _iobtain by the following method:

Step 3.5.1, sets up each first day moon weight coefficient table in breeding time;

Step 3.5.2, reads described each first day moon weight coefficient table, obtains of that month first day weight v _mwith first day next month weight v _m+1, then by the first day in this month weight v _mwith first day next month weight v _m+1substitute into formula (10), calculate a day weight v _i:

$v_i=v_m+(v_{m+1}-v_m)\&CenterDot;{\log }_{31}^n---\left(10\right)$

Wherein, n be in the moon day sequence, n=i;

Step 3.5.3, reads the day radiation G of pre-stored, by day radiation G and day weight v _isubstitute into formula (11), calculate day photosynthetic yield potentiality h _i:

h _i＝v _i·G(11)。

5. the analytical approach of crop climate yield potentiality according to claim 4, is characterized in that, step 3.5.1, and each first day moon weight coefficient table set up is in table 2:

The table 2 cotton photosynthetic potentiality moon first day weight

Wherein, v ₄, v ₅, v ₆, v ₇, v ₈, v ₉and v ₁₀be respectively the first day in April weight, the first day in May weight, the first day in June weight, the first day in July weight, the first day in August weight, the first day in September weight and the first day in October weight.