CN114742324A - Fruit yield estimation method and application thereof - Google Patents
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Abstract
The application relates to the technical field of agriculture, and particularly discloses a fruit yield estimation method and application thereof. The fruit yield estimation method comprises the following steps: calculating a color conversion rate V, calculating the quantity N of fruits which can be ripe on a single cluster of fruit ears according to the color conversion rate V, counting the quantity M of the fruits which can be ripe in a single compartment, calculating the average weight W of the single fruit and the total number U of the fruits on the single cluster of fruit ears, counting the number A of the compartments of a single row and the number B of planted rows, and estimating the fruit yield; and the application of the fruit yield estimation method in the aspect of fruit yield estimation. The fruit yield estimation method can simply, quickly and accurately estimate the yield of the fruits.
Description
Technical Field
The application relates to the technical field of agriculture, in particular to a fruit yield estimation method and application thereof.
Background
With the rapid development of agricultural technology, the multi-span glass greenhouse is a novel plant cultivation facility and is favored by the planting industry. Because the temperature control equipment is arranged in the multi-span glass greenhouse, the plants can be always kept in a specific temperature range, and the plants can be further ensured to grow normally in a whole year. Therefore, farmers use the multi-span glass greenhouse to plant the warm-favored plants in low-temperature seasons which are not suitable for the growth of the plants, thereby obtaining out-of-season fruits and vegetables and leading people to eat fresh fruits and vegetables all the year round.
In recent years, the most plants planted in a greenhouse are tomatoes, the planting range of the plants is wider and wider, and the yield is higher and higher, so in order to plan the sale of the tomatoes better, farmers need to predict the yield of the tomatoes and further adjust the sale strategy of the tomatoes. At present, the main method for estimating the tomato yield is to count and calculate the number of tomatoes collected by each worker every day, and the yield estimation method has the disadvantages of large workload, low accuracy and large error of yield prediction.
Therefore, it is highly desirable to provide a fruit yield estimation method to estimate the fruit yield simply, rapidly and accurately.
Disclosure of Invention
In order to estimate the yield of the fruit simply, quickly and accurately, the application provides a fruit yield estimation method and application thereof.
In a first aspect, the present application provides a fruit yield estimation method, which adopts the following technical scheme:
a fruit yield estimation method comprises the following steps:
(1) calculating a color conversion rate V;
(2) calculating the quantity N of the fruits which can be ripened on the single cluster of fruit ears according to the color conversion rate V;
(3) counting the number M of fruit clusters which can be ripened in a single division;
(4) calculating the average weight W of the single fruit and the total fruit number U on the single cluster of fruit ears;
(5) counting the interval A of the single row and the planting row B;
(6) and (4) estimating the fruit yield.
The fruit yield pre-estimation method comprises the steps, the fruit yield can be quickly and accurately pre-estimated by adopting the steps, so that farmers can obtain yield information as early as possible, and preparation is made for follow-up harvesting, storage, transportation, marketing, processing and the like in advance. The method has high accuracy of fruit yield estimation, less artificial statistics, can reduce the workload of workers, can avoid error rate caused in the artificial statistics process, and has good application value.
Further, the formula for calculating the color conversion rate V is: the color change speed V is equal to the number Y of fruits on a single cluster of fruit ears/color change days T;
wherein, the color change days T is the time from the beginning to the complete color change of the fruits on the single cluster of fruit ears.
According to the method, before the fruit yield is estimated, a large amount of data are acquired and counted, the time T from the color change of the fruits on the single cluster of fruit ears to the complete color change and the number Y of the fruits on the single cluster of fruit ears are obtained, and the color change speed V in the process that the fruits are changed from the white ripe period to the red ripe period can be rapidly and accurately calculated through the data.
The white ripe period is the period when the fruit begins to turn color, the fruit is enlarged and the bottom is slightly white, namely the fruit turns red, and the red indicates that the fruit is ripe and can be harvested.
Further, the formula for calculating the number N of ripe fruits on a single cluster of ears is as follows: the quantity N of the fruits which can be ripened on a single cluster of fruit ears is equal to the number of the future days P multiplied by the color conversion rate V.
Further, the statistical method of the number M of the fruit clusters which can be ripened in a single bay is as follows: and comparing the number of the fruits which are not discolored on all the ears in a single division with N, if the number of the fruits which are not discolored on a single cluster of the ears is less than N, the ears can be ripe in the future days P, and counting the number of all the ears in the single division to obtain the number M of the ripe ears in the single division.
According to the method, the number N of ripe fruits on a single cluster of fruit clusters in the future days P is estimated through the color conversion rate, and then the number of fruits which are not subjected to color conversion on all fruit clusters in a single bay is compared with the number N, so that the number M of all ripe fruit clusters in the single bay is obtained. The calculation and statistics method is simple to operate, high in accuracy and high in speed, and can quickly obtain the number M of the fruit clusters which can be ripe in a single division in a short time.
Further, the fruit yield is related to illumination, so that a database of weather coefficients a under different illumination is also required to be established before fruit yield estimation.
Through analysis of influence factors on fruit yield, the fruit yield is found to have a great relationship with illumination, so that a plurality of lines of data of the fruit yield under different illumination are collected, the daily average illumination amount is taken as a horizontal coordinate, the yield is taken as a vertical coordinate, a relationship curve between the daily average illumination amount and the yield is established, the relationship curve is found to present a curve similar to a logarithmic function, and the slope of the curve is defined as a weather coefficient a. In order to further improve the accuracy of fruit yield estimation, the inventor of the application collects a large amount of daily average illumination and yield data, so that the relation between illumination and yield, namely the weather coefficient a, is more accurate, and finally establishes a weather coefficient a database with higher accuracy.
Preferably, the value of the weather coefficient a is 1-1.3.
Further, the fruit yield estimation method also comprises the steps of calculating a yield increase amount H; the method for calculating the yield increase H comprises the following steps: yield increase H is weather factor a × illumination increase J.
According to the method and the device, the database of the weather coefficient a is established in the early stage, so that in the subsequent yield estimation process, the yield increase H in the future days P can be calculated only by acquiring the illumination increase J of the average day weather in the future days P.
Preferably, the calculation formula of the fruit yield estimation is as follows: the fruit yield Q ═ W × U × M × a × B × (1+ H).
The method comprises the steps of firstly, calculating the quantity N of fruits which can be ripe on a single cluster of fruit ears in the next P days by calculating a color conversion rate V; then counting the number M of fruit clusters which can be ripe in a single cutting room, the average weight W of single fruit, the total fruit number U of a single cluster of fruit clusters, the single-row cutting number A, the planting row number B and the yield increase H in a future P days; and finally, calculating the fruit yield which can be harvested in the future P days by using a fruit yield estimation calculation formula. The method considers the influence of weather factors on the estimated yield, has less data in the statistical process, high statistical speed and small human error, and therefore, the method for estimating the yield of the fruits has the characteristics of simplicity, rapidness and high accuracy.
Further, the fruit is tomato.
Preferably, the error between the estimated yield and the actual yield obtained by the fruit yield estimation method is less than 5%.
In a second aspect, the application of the fruit yield estimation method provided by the application in fruit yield estimation is provided.
Furthermore, the fruit yield estimation method provided by the application is applied to the estimation of the yield of the fruits around the fruit week, the number of the fruits which can be harvested within 1-3 weeks in the future can be obtained by counting the internal and external serial data in the fruit growing process and calculating, and the yield of the fruits can be accurately predicted, so that the fruit yield estimation method has good application value and popularization significance.
In summary, the present application has the following beneficial effects:
1. the fruit yield estimation method can quickly and accurately estimate the fruit yield within 1-3 weeks in the future, so that farmers can obtain yield information as early as possible, and preparation is made for subsequent harvesting, storage, transportation and marketing, processing and the like in advance. And the estimation method has less artificial statistics, reduces the error rate in the statistical process to a great extent, and has good application value.
2. The method comprises the steps of firstly, calculating the quantity N of fruits which can be ripe on a single cluster of fruit ears in the next P days by calculating a color conversion rate V; then counting the number M of fruit clusters which can be ripe in a single cutting room, the average weight W of single fruit, the total fruit number U of a single cluster of fruit clusters, the single-row cutting number A, the planting row number B and the yield increase H in a future P days; and finally, through a fruit yield estimation calculation formula: the fruit yield Q ═ W × U × M × a × B × (1+ H), the fruit yield that could be harvested in the next P days was calculated. The method considers the influence of weather factors on the estimated yield, has less data in the statistical process, high statistical speed and small human error, and therefore, the method for estimating the yield of the fruits has the characteristics of simplicity, rapidness and high accuracy.
3. The error between the estimated yield and the actual yield obtained by the fruit yield estimation method provided by the application is less than 5%.
Drawings
FIG. 1 is a flow chart of a fruit yield estimation method provided by the present application.
Detailed Description
The application provides a fruit yield pre-estimation method, which comprises the following steps:
(1) calculating the color conversion rate V: firstly, establishing an illumination detection device, detecting the cumulative amount of daily average illumination radiation received before and after fruit color conversion, obtaining the time required by fruit color conversion in different seasons, and then calculating the color conversion rate V; the formula for calculating the color conversion rate V is as follows: and the color change speed V is equal to the number of fruits on a single cluster of fruit ears Y/color change days T.
(2) Calculating the quantity N of fruits which can be ripened on a single cluster of clusters in the future days P according to the color conversion rate; the formula for calculating the number N of fruits which can be ripened on a single cluster of fruit ears is as follows: the quantity N of the fruits which can be ripened on a single cluster of fruit ears is equal to the number of the future days P multiplied by the color conversion rate V.
(3) Counting the number M of the ripe fruit ears in a single bay: and comparing the number of the fruits which are not discolored on all the ears in a single division with N, if the number of the fruits which are not discolored on a single cluster of the ears is less than N, the ears can be ripe in the future days P, and counting the number of all the ears in the single division to obtain the number M of the ripe ears in the single division.
(4) Calculating the average weight W of the single fruit and the total fruit number U on the single cluster of fruit ears: randomly selecting a certain amount of fruit ears, weighing the total weight, and then calculating the average fruit number on a single cluster of fruit ears and the average weight of a single fruit.
(5) Counting the interval A of the single row and the planting row B.
(6) Establishing a weather coefficient a database: collecting the yield data of the fruits of the specific variety under different daily average illumination amounts, establishing a relation curve between the daily average illumination amount and the yield of the fruits, and defining the slope of the curve as a weather coefficient a, thereby establishing a weather coefficient a database of the fruits of the variety.
(7) Calculating yield increase H: acquiring a weather coefficient a from the database established in the step (6), acquiring the average daily illumination in the future days P according to weather forecast, calculating the illumination increment J between the average daily illumination in the current day and the future days P, and finally calculating the yield increment H by using the following formula: yield increase H is weather factor a × illumination increase J.
(8) Estimating the fruit yield: acquiring relevant data in the step (1-7), and then estimating the fruit yield; the fruit yield estimation calculation formula is as follows: the fruit yield Q ═ W × U × M × a × B × (1+ H).
The fruits adopted in the fruit yield estimation method provided by the application are red tandem small tomatoes.
The present application will be described in further detail with reference to the following examples and drawings.
Preparation example
Preparation example 1
Establishing a weather coefficient a database
The application establishes a weather coefficient a database, and the specific method is as follows:
(1) taking red bunch harvesting small tomato plants as an example, collecting yield data of tomatoes under different daily average illumination quantities; setting the daily average basic illumination quantity of tomato plants to be 1000J/cm2；
(2) And establishing a relation curve between the average daily illumination quantity and the tomato yield by taking the average daily illumination quantity as an abscissa and the tomato yield as an ordinate, and defining the slope of the curve as a weather coefficient a.
In order to describe the variation trend of the weather coefficient a, the preparation example selects part of representative data from the database of the weather coefficient a (the illumination coefficients are 1000J/cm respectively)2、1100J/cm2、1300J/cm2、1500J/cm2、800J/cm2、600J/cm2、500J/cm2The tomato yield at time and weather coefficient a) are shown in table 1.
TABLE 1 fruit yield and weather coefficient a at different daily average light exposure
The experimental data of the table 1 are collected and sorted, and the relation curve between the daily average illumination quantity and the tomato yield presents a curve of an approximate logarithmic function, the slope of the curve is a weather coefficient a, and the value range of the weather coefficient a is 1-1.3 through calculation.
Further comparison shows that the daily average illumination quantity is 1000J/cm2The daily average illumination amount is more than 1000J/cm2When the daily average illumination quantity is increased, the yield is gradually increased, but the slope of the curve is gradually reduced, and the weather coefficient a is gradually reduced, which shows that when the daily average illumination quantity is more than 1000J/cm2The larger the daily average illumination, the smaller the effect of increasing the tomato yield; average daily illumination amount is less than 1000J/cm2When the daily average illumination quantity is reduced, the yield is gradually reduced, but the slope of the curve is larger and larger, and the weather coefficient a is larger and larger, which shows that when the daily average illumination quantity is less than 1000J/cm2In time, the lower the light exposure, the greater the reduction in tomato yield.
Examples
Examples 1 to 4
Examples 1-4 each provide an estimate of fruit yield. In the fruit yield estimation method, the fruits are red small tomatoes which are stringed and harvested.
The above embodiments differ in that: the predicted season (month) of tomato production is shown in Table 2.
(1) Calculating the color conversion rate V: firstly, establishing an illumination detection device, detecting the cumulative quantity of the daily average illumination radiation received before and after color conversion of the tomatoes, obtaining the time required by color conversion of the tomatoes in different seasons (months), and then calculating the color conversion rate V; the formula for calculating the color conversion rate V is as follows: and the color conversion rate V is equal to the number Y of the tomatoes on a single cluster of ears/color conversion days T.
(2) Calculating the number N of tomatoes which can be cooked on a single cluster of clusters in the future days P according to the color conversion rate V; the formula for calculating the number N of tomatoes that can be cooked on a single cluster of ears is: the number of tomatoes which can be cooked on a single cluster of ears is N which is the number of days in the future P multiplied by the color conversion rate V.
(3) Counting the number M of the ripe fruit clusters in a single division: and comparing the number of the tomatoes which are not discolored on all the clusters in a single shed with N, if the number of the tomatoes which are not discolored on a single cluster of clusters is less than N, the clusters can be ripe in the future days P, and counting the number of all the clusters in the single shed to obtain the number M of the ripe clusters in the single shed.
(4) Calculating the average weight W of the single fruit and the total fruit number U on the single cluster of fruit ears: throughout the greenhouse, 20 mature tomato ears were randomly selected and the total weight was taken, and then the average number of tomatoes on a single cluster of ears and the average weight of individual tomatoes were calculated.
(5) Counting the spacing A of the single row and the planting row B.
(6) Establishing a database of weather coefficients a: as shown in preparation example 1, a weather coefficient a database was created.
(7) Calculating yield increase H: firstly, acquiring the daily average illumination quantity within the future days P according to weather forecast, and calculating the illumination increase quantity J between the current day and the daily average illumination within the future days P; then acquiring a weather coefficient a from the weather coefficient a database established in the step (6); finally, the yield increase H is calculated by using the following formula: yield increase H is weather factor a × illumination increase J.
(8) Estimating the tomato yield: acquiring relevant data in the step (1-7), and estimating the tomato yield; the calculation formula for estimating the tomato yield is as follows: tomato yield Q ═ W × U × M × a × B × (1+ H).
Table 2 season for prediction of tomato yield in fruit yield prediction methods provided in examples 1-4
| Examples | Month (moon) |
| 1 | 1 |
| 2 | 4 |
| 3 | 7 |
| 4 | 10 |
Examples 5 to 6
Examples 5-6 provide an estimate of fruit yield.
The above embodiment is different from embodiment 3 in that: the estimated time of the tomato yield; i.e. days P in the future, as shown in table 3.
Table 3 tomato yield prediction time in fruit yield prediction methods provided in examples 3, 5-6
In the fruit yield estimation method provided in examples 5 to 6, the specific step of counting the number M of ripe fruit ears within a single division in step (3) is as follows: when tomato yield is estimated for 14 days P or 21 days P, the number of ears that can be ripened M in a single blooming period in combination with 7 days P or 14 days P is estimated.
When the future day P is 7 days, the number of the tomatoes which are not discolored on a single cluster of ears is less than N, the single cluster of ears can be ripe within the future day 7, and the number of the ripe ears is marked as M.
When the future day P is 14 days, on a single tomato plant, N is less than the number of the tomatoes which are not discolored on the two clusters and is less than 2N, the two clusters are shown to be ripe in the future day 14, and the number is marked as 2 ripe clusters M; the number of the un-colored tomatoes on the two clusters is more than 2N, and the number is recorded as 1 ripe cluster number M.
When the future days P are 21 days, the number of the tomatoes which are not discolored on the single tomato plant and are more than 2N and less than three clusters of ears is less than 3N, the number of the tomatoes which are not discolored on the single tomato plant and three clusters of ears is recorded as the number M of the ripe ears, and the number of the tomatoes which are not discolored on the three clusters is more than 3N, the number of the tomatoes which are not discolored on the single tomato plant and three clusters is recorded as the number M of the ripe ears.
The method is utilized to count the number of all the clusters in a single compartment, namely the number M of the clusters which can be ripened in the single compartment.
It should be noted that, in general, there are 8 clusters on a single tomato plant, each cluster generally retains 14-18 fruits, and the estimated target of tomato yield is generally the ripe green fruit to be color-changed, and the number of ripe clusters to be color-changed on a single tomato plant is usually 1-3 clusters.
Statistical results of data
The statistics and calculations of the data from steps (1) to (7) in the fruit yield estimation method provided in examples 1 to 4 are shown in Table 4.
Table 4 statistics of fruit yield estimation methods provided in examples 1-4
In the fruit yield estimation methods provided in examples 3 and 5 to 6, the data in steps (1) to (7) were counted and calculated, and the results are shown in table 5.
TABLE 5 statistics of fruit yield estimation methods provided in examples 3 and 5-6
| Examples | 3 | 5 | 6 |
| V (person/d) | 1.2 | 1.2 | 1.2 |
| N (one) | 8.4 | 16.8 | 25.2 |
| M (string) | 38 | 70 | 103 |
| W(kg) | 0.0115 | 0.0115 | 0.0115 |
| U (one) | 11.3 | 11.3 | 11.3 |
| A (one) | 18 | 18 | 18 |
| B (line) | 168 | 168 | 168 |
| Weather coefficient a | 1 | 1 | 1 |
| Day average illumination (J/cm2/day) | 1520 | 1520 | 1520 |
| Illumination growth J (%) | 52 | 52 | 52 |
| Increase in yield H (%) | 52 | 52 | 52 |
Fruit yield estimation fruit yields from examples 1-6 were estimated, actual yields were obtained, and errors were calculated, with the results shown in table 6.
The statistical results of the relevant data of the tomato yield estimation are shown in tables 3-4, and the calculation formula of the tomato yield estimation is as follows: tomato yield Q ═ W × U × M × a × B × (1+ H).
TABLE 6 estimated tomato yield and error in 7 days into the future are obtained by the method for estimating tomato yield as provided in examples 1-6
As can be seen from the detection results in tables 2 and 6, the fruit yield estimation methods provided in examples 1 to 6 can estimate the tomato yields in 7 days, 14 days and 21 days in the future in different seasons and the same season, and further comparison shows that the estimated error of the tomato yield in 7 days in the future is less than 4% in different seasons; in the same season, the estimated errors of the tomato yield of 7 days, 14 days and 21 days in the future are gradually increased, but the overall error is still less than 5%. Therefore, the fruit yield estimation method provided by the application can quickly and accurately realize the estimation of the fruit yield and can acquire accurate yield information as soon as possible for farmers. In addition, the method does not need a large amount of thought statistics, reduces the workload, reduces the estimation error and has good application prospect.
Although the invention has been described in detail hereinabove with respect to a general description and specific embodiments thereof, it will be apparent to those skilled in the art that modifications or improvements may be made thereto based on the invention. Accordingly, such modifications and improvements are intended to be within the scope of the invention as claimed.
Claims (10)
1. The fruit yield estimation method is characterized by comprising the following steps of:
(1) calculating a color conversion rate V;
(2) calculating the quantity N of the fruits which can be ripened on the single cluster of fruit ears according to the color conversion rate V;
(3) counting the number M of fruit clusters which can be ripened in a single division;
(4) calculating the average weight W of the single fruit and the total fruit number U on the single cluster of fruit ears;
(5) counting the spacing A of the single row and the planting row B;
(6) fruit yield is predicted.
2. Fruit yield estimation method according to claim 1, wherein the formula for calculating the color transition rate V is: color change rate V = number of fruits Y/number of color change days T on a single cluster of ears;
wherein, the color change days T is the time from the beginning to the complete color change of the fruits on the single cluster of fruit ears.
3. The fruit yield prediction method according to claim 1, wherein the formula for calculating the number N of fruits ripe on a single cluster of ears is as follows: the number of fruit that can be ripened on a single cluster of ears N = days in the future P × color change rate V.
4. The method for estimating fruit yield according to claim 3, wherein the statistical method of the number M of the ripe fruit clusters in a single bay is as follows: and comparing the number of fruits which are not subjected to color conversion on all the ears in a single bay with N, if the number of the fruits which are not subjected to color conversion on a single cluster of ears is less than N, the ears can be ripe in the future days P, and counting the number of all the ears in the single bay to obtain the number M of the ripe ears in the single bay.
5. Fruit yield prediction method according to claim 1, wherein the fruit yield is related to lighting, so that a database of weather coefficients a under different lighting conditions is also established before fruit yield prediction.
6. The fruit yield estimation method according to claim 5, wherein the weather coefficient a is 1-1.3.
7. The fruit yield prediction method according to claim 1, further comprising calculating a yield increase H; the method for calculating the yield increase H comprises the following steps: yield increase H = weather factor a × illumination increase J.
8. The fruit yield estimation method according to claim 1, wherein the fruit yield estimation is calculated by the following formula: fruit yield Q = W × U × M × a × B × (1+ H).
9. Fruit yield estimation method according to claim 1, wherein the fruit is tomato.
10. Use of the fruit yield estimation method according to any one of claims 1 to 9 for fruit yield estimation.
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| CN113191572A (en) * | 2021-05-27 | 2021-07-30 | 北京佳格天地科技有限公司 | Apple yield prediction method and device, storage medium and electronic equipment |
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| CN111985724A (en) * | 2020-08-28 | 2020-11-24 | 深圳前海微众银行股份有限公司 | Crop yield estimation method, device, equipment and storage medium |
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