CN105512947A - Crop photo-temperature productivity analysis method - Google Patents
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- CN105512947A CN105512947A CN201510867645.XA CN201510867645A CN105512947A CN 105512947 A CN105512947 A CN 105512947A CN 201510867645 A CN201510867645 A CN 201510867645A CN 105512947 A CN105512947 A CN 105512947A
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- 238000004458 analytical method Methods 0.000 title claims abstract description 22
- 238000012937 correction Methods 0.000 claims abstract description 58
- 229920000742 Cotton Polymers 0.000 claims abstract description 45
- 238000000034 method Methods 0.000 claims abstract description 22
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 39
- PEDCQBHIVMGVHV-UHFFFAOYSA-N Glycerine Chemical compound OCC(O)CO PEDCQBHIVMGVHV-UHFFFAOYSA-N 0.000 claims description 37
- 230000000243 photosynthetic effect Effects 0.000 claims description 24
- 238000004519 manufacturing process Methods 0.000 claims description 22
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- 238000012271 agricultural production Methods 0.000 abstract description 7
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- 238000012986 modification Methods 0.000 description 2
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- 230000029553 photosynthesis Effects 0.000 description 2
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Abstract
The invention provides a crop photo-temperature productivity analysis method, and the method comprises the following steps: constructing a crop photo-temperature productivity analysis model; inputting starting time data and stopping time data to the crop photo-temperature productivity analysis model obtained at step 1 when the total photo-temperature productivity, corresponding to a specific time duration, of a growth period of cotton needs to be analyzed; and outputting the analyzed total photo-temperature productivity in the time duration. The method is advantageous in that the method enables a daily maximum temperature correction coefficient and a conventional daily temperature correction coefficient to be combined to form a new photo-temperature correction coefficient, and then calculates the daily photo-temperature productivity; finally the method enables the daily photo-temperature productivity to be accumulated, and obtains the daily photo-temperature productivity in a time period. Therefore, the method can describe the forming process of the photo-temperature productivity of crops and the final productivity, and is of great significance to the crop productivity monitoring, agricultural production resource evaluation, resource evolution and early warning.
Description
Technical field
The invention belongs to agricultural resource studying technological domain, be specifically related to a kind of analytical approach making object light temperature 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 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 light temperature yield potentiality belongs to crucial.
Light temperature yield potentiality is on the basis of photosynthetic yield potentiality, consider the impact of temperature on photosynthesis of plant, corrected by temperature funtion, obtain light temperature yield potentiality, that is: under other conditions are all in optimum, the crop production amount jointly determined by illumination, temperature two kinds of factors is the output theoretical upper limit of agricultural production.
Visible, in light temperature yield potentiality calculates, need first to determine temperature correction coefficient, and in classic method, when determining temperature correction coefficient, the factor considered is less, not comprehensively, thus cause the accuracy of the light temperature yield potentiality finally calculated 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 making object light temperature yield potentiality, effectively can improve the accuracy and objectivity of analyzing the light temperature yield potentiality obtained.
The technical solution used in the present invention is as follows:
The invention provides a kind of analytical approach making object light temperature yield potentiality, comprise the following steps:
Step 1, build and make object light temperature Potential Production Analysis model, described object light temperature Potential Production Analysis model representation of doing is:
Y=∑y
i(1)
Wherein:
y
i=t
i·h
i(2)
t
i=0.3V
i+0.7F
i(3)
V
i=(1-l
i 2)
25-29l
i 2(4)
Wherein: Y-analyzes total light temperature yield potentiality in Period Length;
Y
isunlight yield potentiality in-analysis Period Length;
T
i-light temperature yield potentiality day correction factor;
H
ithe photosynthetic yield potentiality of-;
V
i-daily maximum temperature correction factor;
F
i-degree/day correction factor;
T
uthe highest real air temperature of-;
T
1the preference temperature of-cotton current period;
T
2the minimum temperature that-cotton current period can bear;
T
3the maximum temperature that-cotton current period can bear;
T
i-actual average temperature;
B=(T
3-T
1)/(T
1-T
2);
Step 2, when total light temperature yield potentiality in Water demand cotton development stage corresponding to fixed time length, build to step 1 in the light temperature Potential Production Analysis model obtained input start time data and closing time data;
Step 3, light temperature Potential Production Analysis model was designated as i-th day jth moon by initial time to the time period of closing time any one day, then after receiving start time data and closing time data, read the base point temperature of the analyzed moon three of pre-stored, be 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 4, by T
1, T
2, T
3and T
isubstitute into formula (6), calculate degree/day correction factor F
i;
Step 5, 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 (5), calculate l
i, then by l
isubstitute into formula (4), calculate daily maximum temperature correction factor V
i;
Step 6, by daily maximum temperature correction factor V
iwith degree/day correction factor F
isubstitute into formula (3), calculate light temperature yield potentiality day correction factor t
i:
Step 7, reads the day photosynthetic yield potentiality h of pre-stored
i, by t
iand h
isubstitute into formula (2), calculate sunlight yield potentiality y
i;
Step 8, repeats step 3-step 7, calculates the sunlight yield potentiality of every day in the analyzed time period, then, based on formula (1), the sunlight yield potentiality in each sky calculated is done summation operation, namely obtain the total light temperature yield potentiality in the analyzed time period;
Step 9, the total light temperature yield potentiality in the analyzed time period that output step 8 obtains.
Preferably, in step 3, pre-stored each moon three base point temperature value in table 1:
Table 1 Developmental of Cotton each moon three base point temperature, unit DEG C
。
Preferably, in step 7, the day read photosynthetic yield potentiality h
iobtain by the following method:
Step 7.1, sets up each first day moon weight coefficient table in breeding time;
Step 7.2, 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 (7), calculate a day weight v
i:
Wherein, n be in the moon day sequence, n=i;
Step 7.3, reads the day radiation G of pre-stored, by day radiation G and day weight v
isubstitute into formula (8), calculate day photosynthetic yield potentiality h
i:
h
i=v
i·G(8)。
Preferably, step 7.1, 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.
Preferably, after step 7, also comprise:
Step 10, based on the sunlight yield potentiality that step 7 calculates, calculates day climate yields potentiality.
Preferably, step 10 specifically comprises:
Step 10.1, reads 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 (9), calculate a day water requirement w
i; Wherein, n=i;
Step 10.2, 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 (10), 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;
p
i=0.6p
i-1-w
i+d
i
(10)
Step 10.3, by day moisture supply and demand unspent amount p
isubstitute into formula (11), calculate daily precipitation correction coefficient r
i;
Step 10.4, the sunlight yield potentiality y that read step 7 calculates
i, by sunlight yield potentiality y
iwith daily precipitation correction coefficient r
isubstitute into formula (12), calculate a day climate yields potentiality Y
wi;
Y
wi=r
i·y
i(12)。
Preferably, in step 10.1, the value of each first day moon water requirement of pre-stored is in table 3:
Table 3 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.
The analytical approach making object light temperature yield potentiality provided by the invention has the following advantages:
Daily maximum temperature correction factor and traditional degree/day correction factor are combined, forms new light temperature correction factor, then calculate the sunlight yield potentiality of every day; Finally sunlight yield potentiality is added up, obtain total light temperature yield potentiality of a period of time.Therefore, the forming process and ultimate capacity potentiality of making object light temperature output can be described in real time, all significant in crop yield monitoring, agricultural production resources assessment, Resources Evolution and early warning etc.
Accompanying drawing explanation
Fig. 1 be classic method and the inventive method formed light temperature yield potentiality day correction factor correlation curve figure;
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.
Because crop is at different growthdevelopmental stages, maximum temperature that it can bear is different, and therefore, the actual highest temperature will have a strong impact on crop Dry Matter Production and accumulation on the same day, and its influence and the same day the actual highest temperature be certain curved line relation.But traditional light temperature yield potentiality computing method do not consider the impact of the actual highest temperature on the same day, cause result of calculation and objective reality situation deviation serious.
In order to address this problem, the invention provides a kind of analytical approach making object light temperature yield potentiality, daily maximum temperature correction factor and traditional degree/day correction factor are combined, forms new light temperature correction factor, then calculate the sunlight yield potentiality of every day; Finally sunlight yield potentiality is added up, obtain total light temperature yield potentiality of a period of time.Therefore, the forming process and ultimate capacity potentiality of making object light temperature output can be described in real time, all significant in crop yield monitoring, agricultural production resources assessment, Resources Evolution and early warning etc.
Concrete, the analytical approach making object light temperature yield potentiality provided by the invention, comprises the following steps:
Step 1, build and make object light temperature Potential Production Analysis model, described object light temperature Potential Production Analysis model representation of doing is:
Y=∑y
i(1)
Wherein:
y
i=t
i·h
i(2)
t
i=0.3V
i+0.7F
i(3)
V
i=(1-l
i 2)
25-29l
i 2(4)
Wherein: Y-analyzes total light temperature yield potentiality in Period Length;
Y
isunlight yield potentiality in-analysis Period Length;
T
i-light temperature yield potentiality day correction factor;
H
ithe photosynthetic yield potentiality of-;
V
i-daily maximum temperature correction factor;
F
i-degree/day correction factor;
T
uthe highest real air temperature of-;
T
1the preference temperature of-cotton current period;
T
2the minimum temperature that-cotton current period can bear;
T
3the maximum temperature that-cotton current period can bear;
T
i-actual average temperature;
B=(T
3-T
1)/(T
1-T
2);
Step 2, when total light temperature yield potentiality in Water demand cotton development stage corresponding to fixed time length, build to step 1 in the light temperature Potential Production Analysis model obtained input start time data and closing time data;
Step 3, light temperature Potential Production Analysis model was designated as i-th day jth moon by initial time to the time period of closing time any one day, then after receiving start time data and closing time data, read the base point temperature of the analyzed moon three of pre-stored, be 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;
In this step, pre-stored each moon three base point temperature value in table 1:
Table 1 Developmental of Cotton each moon three base point temperature, unit DEG C
。
Step 4, by T
1, T
2, T
3and T
isubstitute into formula (6), calculate degree/day correction factor F
i;
Step 5, 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 (5), calculate l
i, then by l
isubstitute into formula (4), calculate daily maximum temperature correction factor V
i;
Step 6, by daily maximum temperature correction factor V
iwith degree/day correction factor F
isubstitute into formula (3), calculate light temperature yield potentiality day correction factor t
i:
Step 7, reads the day photosynthetic yield potentiality h of pre-stored
i, by t
iand h
isubstitute into formula (2), calculate sunlight yield potentiality y
i;
Step 8, repeats step 3-step 7, calculates the sunlight yield potentiality of every day in the analyzed time period, then, based on formula (1), the sunlight yield potentiality in each sky calculated is done summation operation, namely obtain the total light temperature yield potentiality in the analyzed time period;
Step 9, the total light temperature yield potentiality in the analyzed time period that output step 8 obtains.
Such as, when needing the total light temperature yield potentiality adding up a certain area in this time period of 2015.5.1 to 2015.9.1, only needing to making object light temperature Potential Production Analysis mode input initial time is 2015.5.1, closing time is these two data of 2015.9.1, makes total light temperature yield potentiality that object light temperature Potential Production Analysis model can calculate this interval automatically.Circular is:
(1) for any one day, as 2015.8.3, first degree/day correction factor is calculated by formula 6.
The degree/day correction factor of 8.3 these days is the preference temperature T of cotton current period
1, the cotton current period minimum temperature T that can bear
2, the cotton current period maximum temperature T that can bear
3with day actual average temperature T
ifunction, and T
1t
2t
3t
ibe given value, can table look-up and directly ask.
(2) read the day the highest real air temperature of 8.3 these days, then according to formula 4 and formula 5, daily maximum temperature correction factor can be obtained.
(3) daily maximum temperature correction factor and degree/day correction factor are substituted into formula 3, calculate light temperature yield potentiality day correction factor:
(4) read the day photosynthetic yield potentiality of 8.3 these days, then remain mutually with light temperature yield potentiality day correction factor, namely obtain sunlight yield potentiality.
(5) for this time period of 2015.5.1 to 2015.9.1, adopt said method to calculate the sunlight yield potentiality of every day, then sue for peace, namely obtain total light temperature yield potentiality of this time period.
The analytical approach making object light temperature yield potentiality provided by the invention, innovative point is as follows:
(1) daily maximum temperature correction factor and traditional degree/day correction factor are combined, form new light temperature correction factor, then the sunlight yield potentiality of every day is calculated, owing to considering daily maximum temperature to the impact making object light temperature yield potentiality, and improve the accuracy of light temperature yield potentiality;
(2) obtain total light temperature yield potentiality by the accumulation of sunlight yield potentiality, the forming process making object light temperature yield potentiality can be reflected, accurately reflect crop dry-matter accumulation state, improve accuracy and the objectivity of light temperature yield potentiality.
(3) due to the sunlight yield potentiality of every day can be calculated, be convenient to calculate the automation application such as monitoring in real time every day;
(4) fields such as crop yield monitoring, agricultural production resources assessment, Resources Evolution and early warning are applicable to.
Fig. 1 be classic method and the inventive method formed light temperature yield potentiality day correction factor correlation curve figure.Observe Fig. 1, in classic method, owing to giving no thought to the impact of the highest temperature, only used temperature on average, be therefore equivalent to revise by fixed coefficient, be the straight line in Fig. 1.But crop has optimum growth temperature, temperature is too high too lowly all brings adverse effect, and in production, high temperature and chilling damage occur often.So, when adopt modification method of the present invention time, light temperature yield potentiality day correction factor be parabolic in Fig. 1, more truly can reflect the change of the yield potentiality that temperature Change is brought.
In addition, the present invention has following two innovations greatly:
Innovation one: day photosynthetic yield potentiality
The day read photosynthetic yield potentiality h
iobtain by the following method:
Step 7.1, sets up each first day moon weight coefficient table in breeding time;
Step 7.1, 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 7.2, 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 (7), calculate a day weight v
i:
Wherein, n be in the moon day sequence, n=i;
Step 7.3, reads the day radiation G of pre-stored, by day radiation G and day weight v
isubstitute into formula (8), calculate day photosynthetic yield potentiality h
i:
h
i=v
i·G(8)。
Innovation two: day climate yields potentiality
Computing method are:
Step 10.1, reads 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 (9), calculate a day water requirement w
i; Wherein, n=i;
The value of each first day moon water requirement of pre-stored is in table 3:
Table 3 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 10.2, 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 (10), 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;
p
i=0.6p
i-1-w
i+d
i
(10)
Step 10.3, by day moisture supply and demand unspent amount p
isubstitute into formula (11), calculate daily precipitation correction coefficient r
i;
Step 10.4, the sunlight yield potentiality y that read step 7 calculates
i, by sunlight yield potentiality y
iwith daily precipitation correction coefficient r
isubstitute into formula (12), calculate a day climate yields potentiality Y
wi;
Y
wi=r
i·y
i(12)。
Such as:
(1) for any one day, as 2015.8.3, first day water requirement is calculated by formula 9.
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 11 is adopted to calculate the daily precipitation correction coefficient of this day of 2015.8.3.
(4) the sunlight yield potentiality of this day of 2015.8.3 and daily precipitation correction coefficient are substituted into formula 12, calculate the day climate yields potentiality of this day of 2015.8.3.
Therefore, the analytical approach of crop climate yield potentiality, 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.
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 light temperature Potential Production Analysis 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 (7)
1. make an analytical approach for object light temperature yield potentiality, it is characterized in that, comprise the following steps:
Step 1, build and make object light temperature Potential Production Analysis model, described object light temperature Potential Production Analysis model representation of doing is:
Y=Σy
i(1)
Wherein:
y
i=t
i·h
i(2)
t
i=0.3V
i+0.7F
i(3)
V
i=(1-l
i 2)
25-29l
i 2(4)
Wherein: Y-analyzes total light temperature yield potentiality in Period Length;
Y
isunlight yield potentiality in-analysis Period Length;
T
i-light temperature yield potentiality day correction factor;
H
ithe photosynthetic yield potentiality of-;
V
i-daily maximum temperature correction factor;
F
i-degree/day correction factor;
T
uthe highest real air temperature of-;
T
1the preference temperature of-cotton current period;
T
2the minimum temperature that-cotton current period can bear;
T
3the maximum temperature that-cotton current period can bear;
T
i-actual average temperature;
B=(T
3-T
1)/(T
1-T
2);
Step 2, when total light temperature yield potentiality in Water demand cotton development stage corresponding to fixed time length, build to step 1 in the light temperature Potential Production Analysis model obtained input start time data and closing time data;
Step 3, light temperature Potential Production Analysis model was designated as i-th day jth moon by initial time to the time period of closing time any one day, then after receiving start time data and closing time data, read the base point temperature of the analyzed moon three of pre-stored, be 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 4, by T
1, T
2, T
3and T
isubstitute into formula (6), calculate degree/day correction factor F
i;
Step 5, 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 (5), calculate l
i, then by l
isubstitute into formula (4), calculate daily maximum temperature correction factor V
i;
Step 6, by daily maximum temperature correction factor V
iwith degree/day correction factor F
isubstitute into formula (3), calculate light temperature yield potentiality day correction factor t
i:
Step 7, reads the day photosynthetic yield potentiality h of pre-stored
i, by t
iand h
isubstitute into formula (2), calculate sunlight yield potentiality y
i;
Step 8, repeats step 3-step 7, calculates the sunlight yield potentiality of every day in the analyzed time period, then, based on formula (1), the sunlight yield potentiality in each sky calculated is done summation operation, namely obtain the total light temperature yield potentiality in the analyzed time period;
Step 9, the total light temperature yield potentiality in the analyzed time period that output step 8 obtains.
2. the analytical approach making object light temperature yield potentiality according to claim 1, is characterized in that, in step 3, pre-stored each moon three base point temperature value in table 1:
Table 1 Developmental of Cotton each moon three base point temperature, unit DEG C
。
3. the analytical approach making object light temperature yield potentiality according to claim 1, is characterized in that, in step 7, and the day read photosynthetic yield potentiality h
iobtain by the following method:
Step 7.1, sets up each first day moon weight coefficient table in breeding time;
Step 7.2, 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 (7), calculate a day weight v
i:
Wherein, n be in the moon day sequence, n=i;
Step 7.3, reads the day radiation G of pre-stored, by day radiation G and day weight v
isubstitute into formula (8), calculate day photosynthetic yield potentiality h
i:
h
i=v
i·G(8)。
4. the analytical approach making object light temperature yield potentiality according to claim 3, is characterized in that, step 7.1, 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.
5. the analytical approach making object light temperature yield potentiality according to claim 1, is characterized in that, after step 7, also comprises:
Step 10, based on the sunlight yield potentiality that step 7 calculates, calculates day climate yields potentiality.
6. the analytical approach making object light temperature yield potentiality according to claim 5, it is characterized in that, step 10 specifically comprises:
Step 10.1, reads 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 (9), calculate a day water requirement w
i; Wherein, n=i;
Step 10.2, 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 (10), 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;
p
i=0.6p
i-1-w
i+d
i(10)
Step 10.3, by day moisture supply and demand unspent amount p
isubstitute into formula (11), calculate daily precipitation correction coefficient r
i;
Step 10.4, the sunlight yield potentiality y that read step 7 calculates
i, by sunlight yield potentiality y
iwith daily precipitation correction coefficient r
isubstitute into formula (12), calculate a day climate yields potentiality Y
wi;
Y
wi=r
i·y
i(12)。
7. the analytical approach making object light temperature yield potentiality according to claim 6, is characterized in that, in step 10.1, the value of each first day moon water requirement of pre-stored is in table 3:
Table 3 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.
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CN101861811A (en) * | 2009-04-15 | 2010-10-20 | 杨春起 | Sunlight greenhouse heating and light supplementing method |
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RU2013129655A (en) * | 2013-06-27 | 2015-01-10 | Государственное научное учреждение Всероссийский научно-исследовательский институт сои Российской академии сельскохозяйственных наук | METHOD FOR DETERMINING THE PRODUCTIVITY OF THE PHOTOSYNTHETIC POTENTIAL OF SOYA VARIETIES |
CN104472273A (en) * | 2014-12-18 | 2015-04-01 | 江苏大学 | Mobile light supplementing method |
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CN101861811A (en) * | 2009-04-15 | 2010-10-20 | 杨春起 | Sunlight greenhouse heating and light supplementing method |
CN101916337A (en) * | 2010-08-23 | 2010-12-15 | 湖南大学 | Method for dynamically predicting potential productivity of paddy rice based on geographical information system |
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RU2013129655A (en) * | 2013-06-27 | 2015-01-10 | Государственное научное учреждение Всероссийский научно-исследовательский институт сои Российской академии сельскохозяйственных наук | METHOD FOR DETERMINING THE PRODUCTIVITY OF THE PHOTOSYNTHETIC POTENTIAL OF SOYA VARIETIES |
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CN116701859A (en) * | 2023-05-29 | 2023-09-05 | 河北省科学院地理科学研究所 | Plant activity accumulated temperature estimation method based on full remote sensing data |
CN116701859B (en) * | 2023-05-29 | 2024-01-30 | 河北省科学院地理科学研究所 | Plant activity accumulated temperature estimation method based on full remote sensing data |
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