1. A construction method of mango large and small year regional forecast model based on meteorological conditions is characterized by comprising the following steps: the construction method comprises the following steps:

s1, preparing mango big and small year type data, wherein the mango big and small year type data are obtained by monitoring or other modes of a model user; the method is characterized in that the method comprises the steps of continuously monitoring data of mango orchards with the area of at least 1000 mu for more than 10 years in the same area, assigning values of 5, 4, 3, 2 and 1 to yield annual types of big, flat, small and small 5;

s2, further preparing meteorological data;

s3, further determining a regional forecast conceptual model;

and S4, finally determining the regional forecast analytic model.

2. The method for constructing the mango large and small year region forecasting model based on meteorological conditions as claimed in claim 1, wherein: in the step S2, the weather data uses daily weather data freely published about the near-country weather station, and generally, the weather stations are all provided within 100 kilometers, one weather station covers 3-4 counties on average, and the historical weather data can be traced back to decades ago; the weather data indexes include daily maximum temperature, average temperature, minimum temperature, average relative humidity, minimum relative humidity, precipitation and sunshine hours.

3. The method for constructing the mango large and small year region forecasting model based on meteorological conditions as claimed in claim 1, wherein: the area forecast conceptual model in step S3 is P_i＝f(X₁；X₂) (ii) a Wherein: x₁、X₂The minimum temperature of the solar terms of heavy snow and the average humidity of the solar terms of valley rain. The time period of the big snow and the rainy day is about 15 days on average from the day of the big snow or the rainy day to the day before the next solar term comes.

4. The method for constructing the mango large and small year region forecasting model based on meteorological conditions as claimed in claim 1, wherein: the area forecast analysis model in step S4 is P_i＝a₀+a₁*X₁+a₂*X₂Wherein a is₀～a₂Model parameters obtained for statistical methods.

Background

China is the second leading country of mango in the world, mango planting history is long, development is rapid in the last half century, and mango planting becomes an important characteristic agricultural industry in tropical regions. At present, the domestic mango mainly has three large production areas, namely Hainan, Guangxi Baise and Sichuan Panzhihua. Hainan is the largest mango producing area in China, and is mainly used for out-of-season cultivation at present, and the yield is not obvious in large and small years. In the city of Panzhihua, the planting area of the mango in 2018 reaches 57 ten thousand mu. The dry and hot valley of the Yangtze river in Baise City is a Guangxi mango producing area, is mainly distributed in the Yangtze river, Tianyang county, Dong county and Tianlin county, and the mango planting area is over 120 ten thousand mu in 2017. The yield of the three mango producing areas of Hainan, Guangxi Baicai and Sichuan Panzhihua in 2017 is 48 ten thousand tons, 42 ten thousand tons and 20 ten thousand tons respectively. The mango is the second largest tropical fruit next to bananas in China, and is also a tropical fruit variety with a small import quantity and export of a large number of tropical fruits, and domestic production and consumption can be basically kept balanced.

The phenomenon of fruit production in the year and before the year is the biggest uncertainty for restricting fruit development in China and even the world. The great fluctuation of the yield in the year and year is a common phenomenon of fruit production and also a long-standing difficulty which always troubles the fruit industry and fruit growers. The method has the advantages that annual fluctuation of yield and income is not simply brought about in the big year and the small year, and damage and risks to trees are brought about, and the method mainly shows that the damage risk caused by disease and insect pest outbreak is aggravated, the capability of the trees for resisting meteorological disasters is reduced, and the like, so that the long-term damage and even the irrecoverable damage of fruit production are caused.

The phenomena of big and small years of mango are mainly limited by winter and spring climate, meteorological conditions of flowering phase and young fruit phase, proper and balanced supply of soil nutrients, nutrient allocation in plants, endogenous hormone production and allocation for controlling plant vegetative growth and reproductive growth, manual management technology intervention and other factors, and the factors influence and determine big, small or flat years and peak-valley fluctuation and amplitude thereof. The above influencing factors are various in number, complicated and complex, vector influence exists among some factors, and the influencing factors play a role along with the key growth period and the whole growth period sequence, so that the dilemma of years and years is not practical to solve by single measures and technologies, and the practice also proves to be infeasible. In addition, effective regulation and control management measures for different annual scenes, namely the types of the years, the plots in different regions, the ages of different trees and the growth vigor are different and different. These may also be the root causes that the elderly often talk about the intractable disease of the old and the young.

At present, research results aiming at mango chronological cause are not yet discussed, and methods capable of regulating and controlling the youth to a certain extent appear in production, but a general technology or a technical system cannot be formed, so that a construction method of a mango chronological region forecasting model based on meteorological conditions is urgently needed to be designed.

Disclosure of Invention

The invention aims to provide a construction method of a mango major and minor region forecasting model based on meteorological conditions, so as to solve the problems in the background technology.

In order to achieve the purpose, the invention provides the following technical scheme:

a construction method of a mango major and minor region forecasting model based on meteorological conditions comprises the following steps:

s1, preparing mango big and small year type data, wherein the mango big and small year type data are obtained by monitoring or other modes of a model user; the method is characterized in that the mangrove orchard monitoring data of at least more than 1000 mu in the same area is continuously monitored for more than 10 years, the annual output is divided into big year, flat year, small year 5 and the like, and numerical values of 5, 4, 3, 2 and 1 are assigned respectively.

S2, further preparing meteorological data;

s3, further determining a regional forecast conceptual model;

and S4, finally determining the regional forecast analytic model.

As a still further scheme of the invention: in the step S2, the weather data uses daily weather data freely published about the near-country weather station, and generally, the weather stations are all provided within 100 kilometers, one weather station covers 3-4 counties on average, and the historical weather data can be traced back to decades ago; the weather data indexes include daily maximum temperature, average temperature, minimum temperature, average relative humidity, minimum relative humidity, precipitation and sunshine hours.

As a still further scheme of the invention: the area forecast conceptual model in step S3 is P_i＝f(X₁；X₂) (ii) a Wherein: x₁、X₂The minimum temperature of the solar terms of heavy snow and the average humidity of the solar terms of valley rain. The time period of the big snow and the rainy day is about 15 days on average from the day of the big snow or the rainy day to the day before the next solar term comes.

As a still further scheme of the invention: the area forecast analysis model in step S4 is P_i＝a₀+a₁*X₁+a₂*X₂Wherein a is₀～a₂Model parameters obtained for statistical methods.

Compared with the prior art, the invention has the beneficial effects that:

the mango tree forecasting method is established based on mango large and small year type monitoring results of more than 10 continuous years in the past of an area and meteorological data of nearby meteorological stations, is simple and practical in model, easy to obtain parameters and high in forecasting precision, and can represent the large and small year conditions of a mango producing area covered by one meteorological station;

the important significance of the regional forecast analytic model is as follows:

(a) the annual parameters of soil nutrients do not appear in the model, which indicates that the mango is mainly a cause of meteorological conditions in the big and small years;

(b) the mango big-and-small year regulation and control technology mainly aims at meteorological conditions, namely measures should be actively taken to avoid meeting of a flowering period and the unfavorable meteorological conditions in the season under the unfavorable meteorological year type, for example, artificial flower picking or plant growth regulators are adopted to control early flowering, irrigation is carried out to increase moisture or a rain-proof shed is built to control rainfall, the sunlight intensity is increased or reduced, and the like under the warm winter condition, and meanwhile, the occurrence of a young year or a small year can be avoided by regulating the microclimate in the field.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

In the embodiment of the invention, a construction method of a mango large and small year region forecasting model based on meteorological conditions comprises the following steps:

s1, preparing mango big and small year data;

s2, further preparing meteorological data;

s3, further determining a regional forecast conceptual model;

s4, finally determining an area forecast analysis model;

in the step S1, the data of the mango year and year are obtained by monitoring or other modes by a model user; the method is characterized in that the mangrove orchard monitoring data of at least more than 1000 mu in the same area is continuously monitored for more than 10 years, the annual output is divided into big year, flat year, small year 5 and the like, and numerical values of 5, 4, 3, 2 and 1 are assigned respectively.

In the step S2, the weather data uses daily weather data freely published about the near-country weather station, and generally, the weather stations are all provided within 100 kilometers, one weather station covers 3-4 counties on average, and the historical weather data can be traced back to decades ago; the meteorological data indexes comprise daily maximum temperature, average temperature, minimum temperature, average relative humidity, minimum relative humidity, precipitation and sunshine hours;

the area forecast conceptual model in step S3 is P_i＝f(X₁；X₂) (ii) a Wherein: x₁、X₂The minimum temperature of heavy snow solar terms (positive correlation, preferably 12.0-14.0 ℃) and the average humidity of grain rain solar terms (negative correlation, preferably 71.0-80.0%); the time period of the big snow and the rainy day is about 15 days on average from the day of the big snow or the rainy day to the day before the next solar term comes.

The area forecast analysis model in step S4 is P_i＝a₀+a₁*X₁+a₂*X₂Wherein a is₀～a₂Model parameters obtained for statistical methods.

The specific implementation and application examples are as follows:

(1) preparing mango year and year data:

according to investigation and data analysis of relevant departments, the year and year type of the yield of Guangxi Nanning mangoes in 29 years in 1991 and 2019 is determined, 5 grades are determined, namely, the values of 1, 2, 3, 4 and 5 are respectively assigned for a small year, a flat year, a large year and a large year.

(2) Preparation of meteorological data:

the weather data of Nanning city in 1990-2019 is from national weather stations, and comprises daily maximum temperature, average temperature, minimum temperature, average relative humidity, minimum relative humidity, precipitation and sunshine hours.

(3) The area forecast conceptual model is as follows:

P_i＝f(X₁；X₂) (ii) a Wherein: x₁、X₂The minimum temperature of heavy snow solar terms (positive correlation, preferably 12.0-14.0 ℃) and the average humidity of grain rain solar terms (negative correlation, preferably 71.0-80.0%); the time period of the big snow and the rainy day is about 15 days on average from the day of the big snow or the rainy day to the day before the next solar term comes.

(4) The area forecast analysis model is as follows:

P_i＝a₀+a₁*X₁+a₂*X₂wherein a is₀～a₂Model parameters obtained for statistical methods.

(5) The concrete forecasting model is as follows:

the mango big-and-small-year forecasting model in the same year: p_i＝9.8630+0.2044*X₁-0.1291*X₂，r＝0.883^**And n is 41, wherein n is year and the percent of pass is 100%. The forecast yield is defined as: compared with the actual year type in the current year, the result with the error within +/-1 year type is qualified for forecasting.

Although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that various changes in the embodiments and/or modifications of the invention can be made, and equivalents and modifications of some features of the invention can be made without departing from the spirit and scope of the invention.