A method for generating an automated cultivation plan for greenhouse tomato planting management

Abstract

The present invention relates to the field of digital agricultural technology, and in particular to a method for generating an automated cultivation plan for greenhouse tomato planting management. The method provided by the present invention digitizes a complex modern greenhouse tomato planting system through big data collection and scientific algorithm processing, and provides an overall planting planning plan, which simplifies the management decision-making difficulty of greenhouse tomato planting managers and improves management efficiency. At the same time, it can also automatically generate a greenhouse environment setting plan, which can be connected to an Internet of Things device to realize automated greenhouse management.

Description

Technical Field

[0001] The present invention relates to the technical field of digital agriculture, and in particular to a method for generating an automated cultivation plan for greenhouse tomato planting management. Background Art

[0002] With the vigorous development of facility agriculture, the scale of greenhouse tomato cultivation is getting larger and larger, and the cultivation technology is becoming more and more complex, which puts higher requirements on the level of cultivation management. However, due to the relatively short history of modern greenhouse cultivation in China, the technical level and experience of managers are difficult to meet the requirements of efficient management of modern greenhouse cultivation.

[0003] At present, the greenhouse digital management platform system on the market is mainly aimed at solving the problem of automated monitoring and control. It lacks the function of planning the overall solution for greenhouse tomato cultivation and cannot truly meet the needs of domestic greenhouse tomato cultivation managers. Although there are related products abroad that formulate overall solutions, they are expensive and complicated to operate. The functions and solutions cannot be localized and are difficult to be widely promoted in China.

[0004] In summary, developing an automated cultivation plan generation method for greenhouse tomato planting management is still a key issue that needs to be urgently addressed in the field of digital agricultural technology. Summary of the invention

[0005] In order to solve the above problems, the present invention provides a method for generating an automated cultivation plan for greenhouse tomato planting management, which uses data collected by modern greenhouse sensors and obtains a scientific and feasible tomato planting plan through algorithm processing.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The present invention provides a method for generating an automated cultivation plan for greenhouse tomato planting management, comprising the following steps:

[0008] (1) Data collection: including greenhouse environment climate, crop data, and greenhouse hardware data;

[0009] (2) Database establishment: including the establishment of greenhouse environment and climate database, crop database and greenhouse hardware database;

[0010] (3) Planting planning: including greenhouse climate control plan and tomato farming operation plan. The greenhouse climate control plan includes the setting of average weekly temperature, supplementary light and CO2 concentration in the greenhouse. The tomato farming operation plan includes flower and fruit thinning decision and planting density decision.

[0011] (4) Implementing planting: Implementing planting according to the planting plan, and updating the greenhouse environment climate database and planting plan.

[0012] The present invention is further configured as follows: in step (1), the data collection of the greenhouse environment climate is to collect data on the average temperature inside the greenhouse, the average light radiation outside the greenhouse, and the average CO2 inside the greenhouse over the past ten years.

[0013] The present invention is further configured as follows: in step (2), the greenhouse environment climate database includes greenhouse environment climate data and effective photosynthetic radiation in the greenhouse, which is a database with the week sequence as the only index.

[0014] The present invention is further configured as follows: the greenhouse inner periphery effective photosynthetic radiation is composed of sunlight effective photosynthetic radiation and supplementary light effective photosynthetic radiation, and the calculation formula is:

[0015] Where, I is the effective photosynthetic radiation of sunlight in the greenhouse, I s is the sunlight effective photosynthetic radiation, I art is the effective photosynthetic radiation of the supplementary light, τ is the greenhouse transmittance, and U is the light-to-electricity conversion efficiency of the supplementary light.

[0016] The present invention is further configured as follows: in step (2), the crop database includes initial planting density, planting varieties, planting start time and planting end time.

[0017] The present invention is further configured as follows: in step (2), the greenhouse hardware database includes the types of fill light, the light-to-electricity conversion rate of the fill light, the power of the fill light and the light transmittance of the greenhouse.

[0018] The present invention is further configured as follows: in step (3), the method for constructing the greenhouse climate control scheme comprises: constructing a crop growth period model, constructing a crop growth model and constructing a reproductive nutrition balance module, wherein:

[0019] Growth period model construction: According to the accumulated temperature of tomato varieties, combined with the average weekly temperature, the tomato development rate is calculated, and the time from flowering to maturity is calculated. The calculation formula is:

[0020] In the formula, TT is the accumulated temperature of tomatoes, t is the average daily temperature, and t b is the minimum effective temperature, i is the number of days after flowering, i harvet is the time of maturity, i.e. the time of harvest;

[0021] Construction of crop growth model: The dry matter accumulation of tomato crops is calculated by the photosynthesis formula, and the dry matter is converted into leaves, stems, roots and other nutritional organs and fruit reproductive organs through internal distribution. The formula is:

[0022] In the formula, are the weekly changes in the total dry matter of tomato plants, the weekly changes in the dry matter of fruits and the weekly changes in the dry matter of leaves, RUE is the coefficient of photosynthetic efficiency, [co2] and [co2] opt are CO2 concentration and optimal concentration, k is the extinction coefficient, LAI is the leaf area index, o is the initial leaf area index, SLA is the leaf area per unit mass, α, β, δ are coupling coefficients;

[0023] Construction of reproductive nutrition balance module: Through the energy comparison between the growth period model and the crop growth model, the parameters of each module are balanced to achieve nutritional and reproductive balance. The corresponding temperature, light, and CO2 after balancing are the environmental control indicators of weekly temperature setting point, supplementary light duration, and CO2 supplement amount, respectively, to generate an environmental control plan on a weekly basis.

[0024] The present invention is further configured as follows: in step (3), by controlling the number of fruits per tomato ear and the planting density in the balance each week, the final number of fruits harvested is controlled to achieve the purpose of energy balancing, and the number of fruits per ear and the planting density obtained after balancing are used as the tomato planting agricultural operation plan.

[0025] The present invention is further configured as follows: in step (4), the greenhouse environmental climate database is updated and run once a week. The real environmental data measured since the beginning of planting, including the weekly average greenhouse temperature, the weekly average greenhouse effective photosynthetic radiation and the weekly average greenhouse CO2 concentration, are inserted into the greenhouse environmental climate database, covering the data of the corresponding week.

[0026] The present invention is further configured as follows: in step (4), the planting planning scheme is updated according to the updated greenhouse environment climate database.

[0027] Beneficial Effects

[0028] Compared with the known public technology, the technical solution provided by the present invention has the following beneficial effects:

[0029] The method provided by the present invention, through big data collection and combined with scientific algorithm processing, digitizes the complex modern greenhouse tomato planting system, provides an overall planting planning solution, simplifies the management decision-making difficulty of greenhouse tomato planting managers, improves management efficiency, and at the same time, can automatically generate a greenhouse environment setting plan, which can be connected to the Internet of Things devices to realize greenhouse automated management. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 The present invention is a flow chart of the method for generating an automated cultivation plan for indoor tomato planting management. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention; it is obvious that the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments, and all other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making creative work are within the scope of protection of the present invention.

[0032] Example:

[0033] like Figure 1 As shown, the present invention provides a method for generating an automated cultivation plan for greenhouse tomato planting management, comprising the following steps:

[0034] (1) Data collection: including greenhouse environment climate, crop data and greenhouse hardware data.

[0035] Furthermore, the greenhouse climate data collection includes the average temperature in the greenhouse (℃), the average light radiation outside the greenhouse (J / m 2 ) and the average CO2 (ppm) in the greenhouse.

[0036] (2) Database establishment: including the establishment of greenhouse environment and climate database, crop database and greenhouse hardware database.

[0037] Furthermore, the greenhouse environment and climate database includes greenhouse environment and climate data and effective photosynthetic radiation in the greenhouse, which is a database with the week sequence as the only index.

[0038] Furthermore, the average effective photosynthetic radiation in the greenhouse is composed of the effective photosynthetic radiation of sunlight and the effective photosynthetic radiation of supplementary light, and its calculation formula is:

[0039] Where, I is the effective photosynthetic radiation of sunlight in the greenhouse, I s is the sunlight effective photosynthetic radiation, I art is the effective photosynthetic radiation of the supplementary light, τ is the greenhouse transmittance, and U is the light-to-electricity conversion efficiency of the supplementary light.

[0040] Furthermore, the crop database includes initial planting density, planting varieties, planting start time, and planting end time.

[0041] Furthermore, the greenhouse hardware database includes the types of fill lights, the light-to-electricity conversion rate of the fill lights (W / umol), the power of the fill lights (W), and the light transmittance of the greenhouse (%).

[0042] (3) Planting planning plan: including greenhouse climate control plan and tomato farming operation plan. The greenhouse climate control plan includes the setting of average weekly temperature, supplementary lighting and CO2 concentration in the greenhouse, and the tomato farming operation plan includes flower and fruit thinning decisions and planting density decisions.

[0043] Furthermore, the greenhouse climate control scheme is constructed by: constructing a crop growth period model, a crop growth model and a reproductive nutrition balance module, wherein:

[0044] Growth period model construction: According to the accumulated temperature of tomato varieties, combined with the average weekly temperature, the tomato development rate is calculated, and the time from flowering to maturity is calculated. The calculation formula is:

[0045] In the formula, TT is the accumulated temperature of tomatoes, t is the average daily temperature, and t b is the minimum effective temperature, i is the number of days after flowering, i harvet is the time of maturity, i.e. the time of harvest;

[0046] In addition, tomato fruits are harvested after they are ripe, and the harvest quantity calculation formula is:

[0047] Harvested fruits = mature fruit bunch × number of fruits per bunch × planting density;

[0048] The criterion for determining mature fruit clusters is the above-mentioned accumulated temperature formula, and the number of fruits per cluster and the planting density are settable variables.

[0049] Construction of crop growth model: The dry matter accumulation of tomato crops is calculated by the photosynthesis formula, and the dry matter is converted into leaves, stems, roots and other nutritional organs and fruit reproductive organs through internal distribution. The formula is:

[0050] In the formula, are the weekly changes in the total dry matter of tomato plants, the weekly changes in the dry matter of fruits and the weekly changes in the dry matter of leaves, RUE is the coefficient of photosynthetic efficiency, [co2] and [co2] opt are CO2 concentration and optimal concentration, k is the extinction coefficient (0.5-0.9), LAI is the leaf area index, o is the initial leaf area index, SLA is the leaf area per unit mass (30-50m 2 / kg), α, β, δ are coupling coefficients that can be optimized iteratively through practice;

[0051] Construction of reproductive nutrition balance module: Through the energy comparison between the growth period model and the crop growth model, the parameters of each module are balanced to achieve nutritional and reproductive balance. The corresponding temperature, light, and CO2 after balancing are the environmental control indicators of weekly temperature setting point, supplementary light duration, and CO2 supplement amount, respectively, to generate an environmental control plan on a weekly basis.

[0052] In addition, the energy required for growth is calculated based on the number of fruits harvested per week and the fruit energy coefficient (50-100), and the energy corresponding to the crop model is calculated using the energy dry matter energy coefficient (14-20), and the growth period model and crop growth model are balanced by adjustment.

[0053] Energy requirement = number of fruits harvested × fruit energy coefficient

[0054] , after balancing, the corresponding weekly temperature, energy supply = energy demand

[0055] Light and CO2 environmental control indicators are used as weekly environmental control plans.

[0056] Furthermore, by controlling the weekly number of tomato fruits per bunch and the planting density in balance, the final number of fruits harvested can be controlled to achieve the purpose of energy balancing. The number of fruits per bunch and the planting density obtained after balancing are used as the agricultural operation plan for tomato planting.

[0057] (4) Implementing planting: Implementing planting according to the planting plan, and updating the greenhouse environment climate database and planting plan.

[0058] Furthermore, the greenhouse environmental climate database is updated once a week. The real environmental data measured since the beginning of planting include the weekly average greenhouse temperature (℃), the weekly average greenhouse effective photosynthetic radiation (J / m 2 ) and the weekly average greenhouse CO2 concentration (ppm) are inserted into the greenhouse environmental climate database, covering the data of the corresponding week.

[0059] Furthermore, the planting plan is updated according to the updated greenhouse environment climate database.

[0060] The method provided by the present invention utilizes the data collected by modern greenhouse sensors and obtains a scientific and feasible tomato planting plan through algorithm processing.

[0061] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for generating an automated cultivation plan for greenhouse tomato planting management, characterized in that: The following steps are involved: (1) Data collection: including greenhouse environment climate, crop data, and greenhouse hardware data; (2) Database establishment: including the establishment of greenhouse environment and climate database, crop database and greenhouse hardware database; (3) Planting planning: including greenhouse climate control plan and tomato farming operation plan. The greenhouse climate control plan includes the setting of average weekly temperature, supplementary light and CO2 concentration in the greenhouse. The tomato farming operation plan includes flower and fruit thinning decision and planting density decision. The method for constructing the greenhouse climate control scheme is as follows: constructing a crop growth period model, a crop growth model and a reproductive nutrition balance module, wherein: Growth period model construction: According to the accumulated temperature of tomato varieties, combined with the average weekly temperature, the tomato development rate is calculated, and the time from flowering to maturity is calculated. The calculation formula is: In the formula, TT is the accumulated temperature of tomatoes, t is the average daily temperature, and t b is the minimum effective temperature, i is the number of days after flowering, i harvet is the time of maturity, i.e. the time of harvest; Construction of crop growth model: The dry matter accumulation of tomato crops is calculated by the photosynthesis formula, and the dry matter is converted into leaves, stems, root vegetative organs and fruit reproductive organs through internal distribution. The formula is: In the formula, are the weekly changes in the total dry matter of tomato plants, the weekly changes in the dry matter of fruits and the weekly changes in the dry matter of leaves, RUE is the coefficient of photosynthetic efficiency, [co2] and [co2] opt are CO2 concentration and optimal concentration, k is the extinction coefficient, LAI is the leaf area index, o is the initial leaf area index, SLA is the leaf area per unit mass, α, β, δ are coupling coefficients; Reproductive nutrition balance module construction: Through the energy comparison between the growth period model and the crop growth model, the parameters of each module are balanced to achieve nutritional and reproductive balance. The corresponding temperature, light, and CO2 after balancing are the environmental control indicators of weekly temperature setting point, supplementary light duration, and CO2 supplement amount, respectively, to generate an environmental control plan in units of weeks; By controlling the number of tomato fruits per bunch and planting density in the balance each week, the final number of fruits harvested can be controlled to achieve the purpose of energy balancing. The number of fruits per bunch and planting density obtained after balancing are used as the farming operation plan for tomato planting. (4) Implementing planting: Implementing planting according to the planting plan, and updating the greenhouse environment climate database and planting plan.

2. The method for generating an automated cultivation plan for greenhouse tomato planting management according to claim 1, characterized in that: In step (1), the greenhouse environmental climate data is collected by collecting the data of the average temperature inside the greenhouse, the average light radiation outside the greenhouse, and the average CO2 inside the greenhouse over the past ten years.

3. The method for generating an automated cultivation plan for greenhouse tomato planting management according to claim 1, characterized in that: In step (2), the greenhouse environment climate database includes greenhouse environment climate data and effective photosynthetic radiation in the greenhouse, and is a database with the week sequence as the only index.

4. The method for generating an automated cultivation plan for greenhouse tomato planting management according to claim 3, characterized in that: The greenhouse inner perimeter effective photosynthetic radiation is composed of sunlight effective photosynthetic radiation and supplementary light effective photosynthetic radiation, and its calculation formula is: I=I s +I art I s =τ×R s ×0.5, where I is the effective photosynthetic radiation of sunlight in the greenhouse, I s For daylight I art =P light ×U×0.5 Effective photosynthetic radiation, I art is the effective photosynthetic radiation of the supplementary light, τ is the greenhouse transmittance, and U is the light-to-electricity conversion efficiency of the supplementary light.

5. The method for generating an automated cultivation plan for greenhouse tomato planting management according to claim 1, characterized in that: In step (2), the crop database includes initial planting density, planting varieties, planting start time and planting end time.

6. The method for generating an automated cultivation plan for greenhouse tomato planting management according to claim 1, characterized in that: In step (2), the greenhouse hardware database includes the types of fill light, the light-to-electricity conversion rate of the fill light, the power of the fill light and the light transmittance of the greenhouse.

7. The method for generating an automated cultivation plan for greenhouse tomato planting management according to claim 1, characterized in that: In step (4), the greenhouse environmental climate database is updated once a week. The real environmental data measured since the start of planting, including the weekly average greenhouse temperature, the weekly average greenhouse effective photosynthetic radiation and the weekly average greenhouse CO2 concentration, are inserted into the greenhouse environmental climate database, covering the data of the corresponding week.

8. The method for generating an automated cultivation plan for greenhouse tomato planting management according to claim 1, characterized in that: In step (4), the planting plan is updated according to the updated greenhouse environment climate database.

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