A method and system for regulating water and fertilizer in orchard

Abstract

The present invention provides an orchard water and fertilizer control method and system, and relates to the technical field of agricultural water and fertilizer control. The orchard water and fertilizer control method includes: combining the current soil moisture, nutrient concentration, suitable soil moisture interval and suitable nutrient concentration interval of the fruit tree to be water and fertilizer controlled, determining the soil moisture difference value and the nutrient concentration difference value; when the absolute value of the soil moisture difference value is greater than a preset threshold, determining the water control strategy based on environmental data, soil moisture difference value and irrigation amount control model; when the absolute value of the nutrient concentration difference value is greater than the preset threshold, determining the nutrient control strategy based on environmental data, nutrient concentration difference value and nutrient content control model. When determining the water control strategy and the nutrient control strategy, the present invention fully considers environmental factors to adjust the irrigation watering amount and the fertilization amount, so that the water and fertilizer control is more accurate and reliable, and has the advantages of high water and fertilizer utilization efficiency and good economic benefits.

Description

Technical Field

[0001] The invention relates to the technical field of agricultural water and fertilizer regulation, and in particular to an orchard water and fertilizer regulation method and system. Background Art

[0002] With the development of agricultural modernization, the importance of irrigation and fertilization systems in the development of facility agriculture, water-saving agriculture and ecological agriculture has become increasingly prominent. In the process of growing fruits and vegetables, farmers usually determine the amount of irrigation and fertilization based on experience, which often results in a "high input and low output" situation, leading to serious waste of water resources and fertilizers. At present, there are many studies on irrigation and fertilization of fruits and vegetables, but they are mainly focused on the water-fertilizer coupling research with the goal of fruit and vegetable yield and quality. Most of them are still based on crop empirical models, that is, water and fertilizer formulas are given according to experience, and the relationship between water, fertilizer and yield is monitored at the same time. However, the existing technology lacks consideration of the impact of dynamic changes in growth environment factors on crop irrigation and fertilization. The existing water and fertilizer regulation technology has low water and fertilizer utilization efficiency, and the economic benefits cannot be maximized.

[0003] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0004] The object of the present invention is to provide a method and system for regulating water and fertilizer in an orchard to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method for regulating water and fertilizer in an orchard, comprising the following steps:

[0007] S1, taking fruit yield as the evaluation benchmark, determine the suitable soil moisture range and suitable nutrient concentration range for fruit trees in each growth period;

[0008] S2, determining the growth period of the fruit tree to be regulated by water and fertilizer based on the real-time morphological image, and determining the suitable soil moisture range and suitable nutrient concentration range of the fruit tree to be regulated by water and fertilizer based on the growth period;

[0009] S3, constructing an irrigation quantity control model and a nutrient content control model based on historical data, the historical data including irrigation water quantity, nutrient content of fertilizers used for fertilization, soil moisture, nutrient concentration, daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall data;

[0010] S4, collecting the current soil moisture and nutrient concentration data of the fruit trees to be regulated by water and fertilizer, and determining the soil moisture difference value and the nutrient concentration difference value in combination with the suitable soil moisture interval and the suitable nutrient concentration interval in step S2;

[0011] S5, when the absolute value of the soil moisture difference value and the absolute value of the nutrient concentration difference value are not greater than the preset threshold value, water and fertilizer regulation is not performed, otherwise the daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall of the fruit trees to be watered and fertilized are collected from the current day to the next week, and when the absolute value of the soil moisture difference value is greater than the preset threshold value, step S6 is entered, and when the absolute value of the nutrient concentration difference value is greater than the preset threshold value, step S7 is entered;

[0012] S6, determining a water control strategy based on the data collected in step S5, the soil moisture difference value and the irrigation amount control model;

[0013] S7, determining a nutrient control strategy based on the data collected in the above step S5, the nutrient concentration difference value and the nutrient content control model.

[0014] Furthermore, the growth period includes the budding period, the flowering period, the fruit expansion period and the fruit ripening period, and the nutrient concentration includes the nitrogen concentration, the phosphorus concentration and the potassium concentration.

[0015] Furthermore, the step S1 includes the following steps:

[0016] S11, obtaining the soil moisture time series data, nutrient concentration time series data and fruit yield of each fruit tree in the orchard in previous years;

[0017] S12, using the fruit yield being in the top column as a screening condition, screening out the fruit trees with the fruit yield being in the top column, and extracting the soil moisture time series data and the nutrient concentration time series data of the fruit trees;

[0018] S13, using the budding period, flowering period, fruit expansion period and fruit maturity period as screening conditions, screening all the soil moisture time series data and nutrient concentration time series data extracted in step S12 to obtain a soil moisture data set and a nutrient concentration data set corresponding to the budding period, flowering period, fruit expansion period and fruit maturity period;

[0019] S14, determining suitable soil moisture ranges and suitable nutrient concentration ranges in each growth period based on the soil moisture data set and the nutrient concentration data set.

[0020] Furthermore, the step S141 includes the following steps:

[0021] S141, based on the mean and standard deviation of the soil moisture data set, determine the upper and lower limits of the suitable soil moisture range for the corresponding growing period, and the calculation formula is as follows:

[0022]

[0023] Among them, μ RH , σ RH are the mean and standard deviation of the soil moisture data set, RHmax and RHmin are the upper and lower limits of the suitable soil moisture range for the corresponding growing period, and γ is a preset proportional coefficient greater than zero;

[0024] S142, based on the mean and standard deviation of the nutrient concentration data set, determine the upper and lower limits of the appropriate nutrient concentration range for the corresponding growth period, and the calculation formula is as follows:

[0025]

[0026] Among them, μ C (i), σ C (i) are the mean and standard deviation of the nutrient concentration of the i-th nutrient in the nutrient concentration data set, i = 1, 2, 3, corresponding to nitrogen, phosphorus and potassium, respectively, C max (i) C min (i) are the upper and lower limits of the ith suitable nutrient concentration interval corresponding to the growth period, and δ is a preset proportional coefficient greater than zero.

[0027] Furthermore, step S2 includes the following steps:

[0028] S21, collecting a plurality of morphological images of fruit trees at different growth stages as a data set, and randomly dividing the data set into a training set and a test set, and marking the corresponding growth stage on each morphological image of the training set as a label;

[0029] S22, constructing a fruit tree growth period judgment model based on a convolutional neural network, training the fruit tree growth period judgment model using a training set, and testing the fruit tree growth period judgment model using a test set to obtain a fruit tree growth period judgment model that passes the test;

[0030] S23, taking real-time morphological images of the fruit trees to be regulated with water and fertilizer, and inputting the real-time morphological images into a growth period judgment model for fruit trees that have passed the test, so as to determine the growth period of the fruit trees to be regulated with water and fertilizer, and then determining the suitable soil moisture range and the suitable nutrient concentration range corresponding to this growth period.

[0031] Furthermore, step S3 includes the following steps:

[0032] S31, multiple fruit trees in the orchard are used as experimental fruit trees, and the data on irrigation watering amount, nutrient content of fertilizers used for fertilization, soil moisture, nutrient concentration, daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall of the experimental fruit trees are collected daily during each growth period in previous years;

[0033] S32, using the same growth period as the fruit tree to be regulated by water and fertilizer as a screening condition, filtering out corresponding data from the data of step S31 to form a data set;

[0034] S33, establishing an irrigation quantity control model based on a deep learning neural network, taking the soil moisture difference between the day after irrigation and the day of irrigation in the data set, as well as the daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall on the day of irrigation and the day after irrigation as input, taking the irrigation quantity on the day of irrigation as a label, training and testing the irrigation quantity control model to obtain an irrigation quantity control model that passes the test;

[0035] S34, a nutrient content control model is established based on a deep learning neural network, and the difference in nutrient concentration between one week after fertilization and the day of fertilization, the soil moisture on the day of fertilization, and the daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall from the day of fertilization to one week after fertilization are used as inputs, and the nutrient content of the fertilizer on the day of fertilization is used as a label to train and test the nutrient content control model to obtain a nutrient content control model that passes the test.

[0036] Furthermore, the calculation formulas for the soil moisture difference value and the nutrient concentration difference value are as follows:

[0037]

[0038] Among them, RH s , C s (i) are the current soil moisture of the fruit trees to be regulated by water and fertilizer, the concentration of the i-th nutrient, RH' max RH' min , C' max (i) C' min (i) are the upper limit of the suitable soil moisture range, the lower limit of the suitable soil moisture range, the upper limit of the i-th suitable nutrient concentration range, and the lower limit of the i-th suitable nutrient concentration range corresponding to the fruit trees to be regulated by water and fertilizer, respectively. ΔRH and ΔC(i) are the soil moisture difference value and the i-th nutrient concentration difference value of the fruit trees to be regulated by water and fertilizer, respectively.

[0039] Furthermore, step S6 includes the following steps:

[0040] S61, when the soil moisture difference value of the fruit tree to be regulated by water and fertilizer is less than 0, digging ditches and draining water for the fruit tree to be regulated by water and fertilizer, and when the soil moisture difference value of the fruit tree to be regulated by water and fertilizer is greater than 0, entering step S62;

[0041] S62, input the soil moisture difference value and the current and next day's average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall of the fruit tree to be regulated by water and fertilizer into the irrigation quantity regulation model to obtain the irrigation watering quantity. When the irrigation watering quantity is not greater than 0, no irrigation is performed. When the irrigation watering quantity is greater than 0, enter step S63;

[0042] S63, based on the daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall of the fruit trees to be regulated by water and fertilizer from the current day to the next week, the irrigation watering amount is corrected to generate an irrigation watering correction amount, and the calculation formula is as follows:

[0043]

[0044] Among them, κ2 is the second irrigation adjustment coefficient, are the average daily temperature, average daily light intensity, average daily air humidity, average daily wind speed and average daily rainfall of the fruit trees to be regulated by water and fertilizer from the current to the next week, ω1, ω2, ω3, ω4 are all preset proportional coefficients, and ω1+ω2+ω3+ω4=1, and 0<ω3<ω2<ω4≤ω1<1, l is the irrigation amount generated by the irrigation amount regulation model, κ1 is the preset first irrigation regulation coefficient, and the first irrigation regulation coefficient κ1>1, l' is the irrigation correction amount;

[0045] S64: when the irrigation and watering correction amount is not greater than 0, irrigation and watering are not performed; and when the irrigation and watering correction amount is greater than 0, irrigation and watering are performed based on the irrigation and watering correction amount.

[0046] Furthermore, the step S7 includes the following steps:

[0047] S71, when the nutrient concentration difference value of the fruit tree to be regulated by water and fertilizer is less than 0, irrigate and water the fruit tree to be regulated by water and fertilizer, and when the nutrient concentration of the fruit tree to be regulated by water and fertilizer is greater than 0, enter step S72;

[0048] S72, inputting the nutrient concentration difference value, the current soil moisture of the fruit tree to be water-fertilizer regulated, the daily average temperature, the daily average light intensity, the daily average air humidity, the daily average wind speed and the daily average rainfall from the current day to the next week into the nutrient content regulation model to obtain the nutrient content of the fertilizer for fertilization;

[0049] S73, correcting the nutrient content of the fertilizer for fertilization to obtain a corrected amount of the nutrient content of the fertilizer for fertilization, and configuring fertilizers based on the corrected amount of the nutrient content of the fertilizer for fertilization for fertilization, wherein the calculation formula of the corrected amount of the nutrient content of the fertilizer for fertilization is as follows:

[0050] m'(i)=m(i)*η(i)

[0051] Among them, m'(i) is the correction amount of the i-th nutrient content of the fertilizer used for fertilization, m(i) represents the i-th nutrient content of the fertilizer used for fertilization, η(i) is the fertilization adjustment coefficient corresponding to m(i), and the fertilization adjustment coefficient η(i)>1.

[0052] An orchard water and fertilizer control system, used to execute the orchard water and fertilizer control method, comprising:

[0053] The suitable interval generation module is used to determine the suitable soil moisture interval and suitable nutrient concentration interval of the fruit trees in each growth period based on the fruit yield as the evaluation benchmark;

[0054] A suitable interval selection module is used to determine the growth period of the fruit tree to be regulated by water and fertilizer based on the real-time morphological image, and to determine the suitable soil moisture interval and suitable nutrient concentration interval of the fruit tree to be regulated by water and fertilizer based on the growth period;

[0055] The control model building module is used to build an irrigation quantity control model and a nutrient content control model based on historical data. The historical data includes irrigation water quantity, nutrient content of fertilizers used for fertilization, soil moisture, nutrient concentration, daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall data;

[0056] The difference value judgment module is used to collect the current soil moisture and nutrient concentration data of the fruit trees to be regulated by water and fertilizer, and determine the soil moisture difference value and the nutrient concentration difference value in combination with the suitable soil moisture interval and the suitable nutrient concentration interval in step S2;

[0057] The control judgment module is used for not performing water and fertilizer control when the absolute value of the soil moisture difference value and the absolute value of the nutrient concentration difference value are both not greater than the preset threshold value, otherwise the daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall of the fruit trees to be watered and fertilized are collected from the current day to the next week, and the step is entered into step S6 when the absolute value of the soil moisture difference value is greater than the preset threshold value, and the step is entered into step S7 when the absolute value of the nutrient concentration difference value is greater than the preset threshold value;

[0058] A water control strategy generation module, used to determine the water control strategy based on the data collected in step S5, the soil moisture difference value and the irrigation amount control model;

[0059] The nutrient control strategy generation module is used to determine the nutrient control strategy based on the data collected in the above step S5, the nutrient concentration difference value and the nutrient content control model.

[0060] Compared with the prior art, the present invention has the following beneficial effects:

[0061] The orchard water and fertilizer control method and system of the present invention first determines the suitable soil moisture range and the suitable nutrient concentration range of the fruit trees in each growth period based on the fruit tree yield, and then determines the soil moisture difference value and the nutrient concentration difference value in combination with the current soil moisture and nutrient concentration of the fruit trees to be water and fertilizer controlled. Finally, the above-mentioned difference values, environmental data and related models are combined to determine the water control strategy and the nutrient control strategy. In this process, environmental factors are fully considered to adjust the irrigation watering amount and the fertilization amount, so that the water and fertilizer control is more accurate and reliable, and has the advantages of high water and fertilizer utilization efficiency and good economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 It is a schematic diagram of the process of the water and fertilizer regulation method for an orchard in the present invention;

[0063] Figure 2 This is a module unit diagram of the orchard water and fertilizer control system in the present invention. DETAILED DESCRIPTION

[0064] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0065] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0066] Embodiment 1:

[0067] See also Figure 1 The present invention provides a method for regulating water and fertilizer in an orchard, comprising the following steps:

[0068] S1, taking fruit yield as the evaluation benchmark, determine the suitable soil moisture range and suitable nutrient concentration range for fruit trees in each growth period:

[0069] Among them, the growth period includes the budding period, flowering period, fruit expansion period and fruit maturity period. The budding period, flowering period, fruit expansion period and fruit maturity period all adopt the existing judgment and classification standards, which will not be elaborated here;

[0070] The nutrient concentration includes nitrogen concentration, phosphorus concentration and potassium concentration. The method for obtaining the nutrient concentration is as follows: soil at the root of the fruit tree is collected as a sample, and then the sample is sent to a portable soil tester for testing, so as to measure the nitrogen concentration, phosphorus concentration and potassium concentration in the soil. In addition, when sampling, since the roots of fruit trees are mostly concentrated in the area of ​​10-30 depth, the soil with a depth of 10-30 cm is selected as the sample, so that the measured nutrient concentration is more representative.

[0071] Step S1 includes the following steps:

[0072] S11, obtaining the soil moisture time series data, nutrient concentration time series data and fruit yield of each fruit tree in the orchard in previous years;

[0073] It should be noted that the soil moisture time series data and nutrient concentration time series data can be collected daily, every other day or regularly, which is set by the staff according to the actual situation and is not limited here. The soil moisture can be measured by a soil moisture sensor buried in the soil at the root of the fruit tree, and the soil moisture sensor is also buried in the soil at a depth of 10-30 cm;

[0074] S12, using the fruit yield being in the top column as a screening condition, screening out the fruit trees with the fruit yield being in the top column, and extracting the soil moisture time series data and the nutrient concentration time series data of the fruit trees;

[0075] It should be noted that the higher the fruit yield of a fruit tree, the better the growth condition of the fruit tree, and the more scientific and reasonable the soil moisture and nutrient concentration corresponding to the fruit tree. The screening condition can be that the fruit yield is in the top 30%, 40% or 50%, which is set by the staff according to the actual situation and is not limited here;

[0076] S13, using the budding period, flowering period, fruit expansion period and fruit maturity period as screening conditions, screening all the soil moisture time series data and nutrient concentration time series data extracted in step S12 to obtain a soil moisture data set and a nutrient concentration data set corresponding to the budding period, flowering period, fruit expansion period and fruit maturity period;

[0077] S14, based on the soil moisture data set and the nutrient concentration data set, determining the suitable soil moisture range and the suitable nutrient concentration range in each growth period, as follows:

[0078] S141, based on the mean and standard deviation of the soil moisture data set, determine the upper and lower limits of the suitable soil moisture range for the corresponding growing period, and the calculation formula is as follows:

[0079]

[0080] It should be noted that μ RH , σ RH are the mean and standard deviation of the soil moisture data set, respectively. The calculation process is common knowledge and will not be elaborated here. RHmax and RHmin are the upper and lower limits of the suitable soil moisture interval for the corresponding growth period, respectively. γ is a preset proportional coefficient greater than zero. The larger the value of γ, the larger the range of the suitable soil moisture interval, and the less accurate the suitable soil moisture interval is. However, it is more convenient to adjust the irrigation amount according to the suitable soil moisture interval later. Similarly, the smaller the value of γ, the smaller the range of the suitable soil moisture interval, and the more accurate the suitable soil moisture interval is. However, it is more difficult to adjust the irrigation amount according to the suitable soil moisture interval later. The specific value of γ is set by the staff according to the actual situation. For example, the value can be 0.5, 1, 1.5, 2, etc., which is not limited here.

[0081] S142, based on the mean and standard deviation of the nutrient concentration data set, determine the upper and lower limits of the appropriate nutrient concentration range for the corresponding growth period, and the calculation formula is as follows:

[0082]

[0083] It should be noted that μ C (i), σ C (i) are the mean and standard deviation of the ith nutrient concentration in the nutrient concentration data set. The calculation process is common knowledge and will not be described here. i = 1, 2, 3, corresponding to nitrogen, phosphorus and potassium, respectively. C max (i) C min (i) are the upper and lower limits of the i-th suitable nutrient concentration interval corresponding to the growth period, δ is a preset proportional coefficient greater than zero. The larger the value of δ, the larger the range of the suitable nutrient concentration interval, and the less accurate the suitable nutrient concentration interval is. However, it is more convenient to adjust the amount of fertilizer according to the suitable nutrient concentration interval later. Similarly, the smaller the value of δ, the smaller the range of the suitable nutrient concentration interval, and the more accurate the suitable nutrient concentration interval is. However, it is more difficult to adjust the amount of fertilizer according to the suitable nutrient concentration interval later. The specific value of δ is set by the staff according to the actual situation. For example, the possible values ​​are 0.5, 1, 1.5, 2, etc., which are not limited here.

[0084] S2, determining the growth period of the fruit tree to be regulated by water and fertilizer based on the real-time morphological image, and determining the suitable soil moisture range and suitable nutrient concentration range of the fruit tree to be regulated by water and fertilizer based on the growth period, including the following steps;

[0085] S21, collecting a plurality of morphological images of fruit trees at different growth stages as a data set, and randomly dividing the data set into a training set and a test set, and marking the corresponding growth stage on each morphological image of the training set as a label;

[0086] It should be noted that the ratio of the training set to the test set can be 70:30 or 80:20, which is set by the staff according to the actual situation and is not limited here. The collected morphological images can be taken on-site of the fruit trees in the orchard, or crawled from a public website, which is not limited here. Photoshop or GIMP software technology can be used to mark labels on the morphological images, which is a prior art and will not be described in detail here.

[0087] S22, constructing a fruit tree growth period judgment model based on a convolutional neural network, training the fruit tree growth period judgment model using a training set, and testing the fruit tree growth period judgment model using a test set to obtain a fruit tree growth period judgment model that passes the test;

[0088] It should be noted that the fruit tree growth period judgment model includes an input layer, a convolution layer, a pooling layer, a fully connected layer, an activation function and an input layer, and a cross entropy loss function is used as a loss function. The SGD (stochastic gradient descent) optimizer is selected to update the network parameters, and the training set is input into the fruit tree growth period judgment model for training to update the network parameters. After reaching the predetermined iteration conditions, the test set is input into the fruit tree growth period judgment model for testing, and the fruit tree growth period judgment model is evaluated with evaluation indicators such as F1 score, accuracy or recall rate. When the test is qualified, the fruit tree growth period judgment model is saved, and when the test is unqualified, the training set is used again for training. This is a prior art and will not be described in detail here;

[0089] S23, taking real-time morphological images of the fruit trees to be regulated with water and fertilizer, and inputting the real-time morphological images into a growth period judgment model for fruit trees that have passed the test, so as to determine the growth period of the fruit trees to be regulated with water and fertilizer, and then determining the suitable soil moisture range and the suitable nutrient concentration range corresponding to this growth period.

[0090] S3, constructing an irrigation quantity control model and a nutrient content control model based on historical data, the historical data including irrigation water quantity, nutrient content of fertilizers used for fertilization, soil moisture, nutrient concentration, daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall data, including the following steps:

[0091] S31, multiple fruit trees in the orchard are used as experimental fruit trees, and the data on irrigation watering amount, nutrient content of fertilizers used for fertilization, soil moisture, nutrient concentration, daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall of the experimental fruit trees are collected daily during each growth period in previous years;

[0092] It should be noted that the daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall can all be obtained through the meteorological data released by the local meteorological bureau, which will not be elaborated here. The nutrient content of fertilizers for fertilization includes nitrogen content, phosphorus content and potassium content;

[0093] S32, using the same growth period as the fruit tree to be regulated by water and fertilizer as a screening condition, filtering out corresponding data from the data of step S31 to form a data set;

[0094] Furthermore, the daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall data of the data set are normalized. The normalization process can specifically adopt the maximum-minimum normalization process method. For example, for the daily average temperature, the maximum and minimum values ​​of the daily average temperature in the data set are first determined, and then the maximum-minimum normalization process is performed on each daily average temperature in the data set based on the maximum and minimum values ​​of the daily average temperature. The maximum-minimum normalization process makes the daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall within the same scale range, which provides convenience for subsequent training models;

[0095] S33, establishing an irrigation quantity control model based on a deep learning neural network, taking the soil moisture difference between the day after irrigation and the day of irrigation in the data set, as well as the daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall on the day of irrigation and the day after irrigation as input, taking the irrigation quantity on the day of irrigation as a label, training and testing the irrigation quantity control model to obtain an irrigation quantity control model that passes the test;

[0096] It should be noted that temperature, light, air humidity, wind speed and rainfall are all important factors affecting soil moisture changes. Therefore, the settings of daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall are introduced to enable the irrigation quantity control model to simulate the soil moisture changes caused by irrigation in the real environment;

[0097] It should be noted that the irrigation quantity control model constructed based on the deep learning neural network includes an input layer for receiving input data, multiple hidden layers for extracting and learning input data features, and an output layer for outputting irrigation watering amount. The hidden layer is composed of a fully connected layer and an activation function layer. The fully connected layer is used to combine the data features input to the hidden layer to extract higher-level features. The activation function layer is used to reference nonlinear changes so that the deep learning neural network can learn and represent complex linear relationships. The irrigation quantity control model uses a mean square error loss function as a loss function, and updates the network parameters based on the back propagation algorithm until the set number of training rounds is reached or the loss function value reaches a predetermined minimum value. The training is considered to be completed, and then the irrigation quantity control model is tested. The accuracy rate is used as an evaluation indicator to determine whether the irrigation quantity control model is qualified. If the test is qualified, the irrigation quantity control model is saved, and if the test is unqualified, the model is retrained.

[0098] S34, establishing a nutrient content control model based on a deep learning neural network, taking the difference in nutrient concentration between one week after fertilization and the day of fertilization, the soil moisture on the day of fertilization, and the daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall from the day of fertilization to one week after fertilization as input, taking the nutrient content of the fertilizer on the day of fertilization as a label, training and testing the nutrient content control model to obtain a nutrient content control model that passes the test;

[0099] It should be noted that temperature, light, air humidity, wind speed and rainfall are all important factors affecting the growth of fruit trees, that is, temperature, light, air humidity, wind speed and rainfall will affect the absorption of soil nutrients by the fruit tree roots, which will lead to changes in the nutrient concentration of the soil. Therefore, the settings of daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall are introduced to make the nutrient content control model simulate the changes in nutrient concentration caused by fertilization in the real environment. And because it takes a certain time (such as 3-5 days) for fertilizer nutrients to be absorbed by the soil after fertilization, the nutrient concentrations one week after fertilization and on the day of fertilization are selected when training the model to ensure the accuracy of the model output results;

[0100] It should be noted that there are three nutrient content control models constructed based on deep learning neural networks, namely nitrogen content control model, phosphorus content control model and potassium content control model. Any nutrient content control model includes an input layer for receiving input data, multiple hidden layers for extracting and learning input data features, and an output layer for outputting the nutrient content of fertilizer for fertilization. The hidden layer is composed of a fully connected layer and an activation function layer. The fully connected layer is used to combine the data features input to the hidden layer to extract higher-level features. The activation function layer is used to reference nonlinear changes so that the deep learning neural network learns and represents complex linear relationships. The nutrient content control model uses a mean square error loss function as the loss function, and updates the network parameters based on the back propagation algorithm until the set number of training rounds is reached or the loss function value reaches a predetermined minimum value. The training is considered to be completed, and then the nutrient content control model is tested. The nutrient content control model is determined to be qualified based on the accuracy evaluation index. If the test is qualified, the nutrient content control model is saved, and if the test is unqualified, it is retrained.

[0101] S4, collecting the current soil moisture and nutrient concentration data of the fruit trees to be regulated by water and fertilizer, and combining the suitable soil moisture range and the suitable nutrient concentration range in step S2 to determine the soil moisture difference value and the nutrient concentration difference value, the formula based on which is as follows:

[0102]

[0103] It should be noted that RH s , C s (i) are the current soil moisture of the fruit trees to be regulated by water and fertilizer, the concentration of the i-th nutrient, RH' max RH' min , C' max (i) C' min (i) are the upper limit of the suitable soil moisture interval, the lower limit of the suitable soil moisture interval, the upper limit of the i-th suitable nutrient concentration interval, and the lower limit of the i-th suitable nutrient concentration interval corresponding to the fruit trees to be regulated by water and fertilizer, respectively; ΔRH and ΔC(i) are the soil moisture difference value and the i-th nutrient concentration difference value of the fruit trees to be regulated by water and fertilizer, respectively;

[0104] It should be noted that when the soil moisture difference value is 0, it means that the current soil moisture of the fruit tree to be regulated by water and fertilizer is within the appropriate soil moisture range, that is, the current moisture of the fruit tree to be regulated by water and fertilizer is appropriate and no irrigation or water replenishment is required. When the soil moisture difference value is greater than 0, it means that the current soil moisture of the fruit tree to be regulated by water and fertilizer is low, that is, the fruit tree to be regulated by water and fertilizer is currently in a drought state and irrigation or water replenishment is required. When the soil moisture difference value is less than 0, it means that the current soil moisture of the fruit tree to be regulated by water and fertilizer is high, that is, the fruit tree to be regulated by water and fertilizer is currently in a waterlogged state and drainage is required.

[0105] It should be noted that when the nutrient concentration difference value is 0, it means that the current nutrient concentration of the fruit trees waiting for water and fertilizer regulation is within the appropriate nutrient concentration range, that is, the current nutrient concentration of the fruit trees waiting for water and fertilizer regulation is appropriate and no fertilization is needed. When the nutrient concentration difference value is greater than 0, it means that the current nutrient concentration of the fruit trees waiting for water and fertilizer regulation is on the low side, that is, the fruit trees waiting for water and fertilizer regulation are currently in a fertilizer-deficient state and fertilization is needed. When the nutrient concentration difference value is less than 0, it means that the current nutrient concentration of the fruit trees waiting for water and fertilizer regulation is on the high side, that is, the fruit trees waiting for water and fertilizer regulation are currently in a fertilizer-rich state and the nutrient content needs to be reduced.

[0106] S5, when the absolute value of the soil moisture difference value and the absolute value of the nutrient concentration difference value are not greater than the preset threshold value, water and fertilizer regulation is not performed, otherwise the daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall of the fruit trees to be watered and fertilized are collected from the current day to the next week, and when the absolute value of the soil moisture difference value is greater than the preset threshold value, step S6 is entered, and when the absolute value of the nutrient concentration difference value is greater than the preset threshold value, step S7 is entered;

[0107] It should be noted that when the absolute value of the soil moisture difference and the absolute value of the nutrient concentration difference are not greater than the preset threshold values, it means that the soil moisture and nutrient concentration of the fruit trees to be water-fertilizer regulated are within a reasonable range, so no water and fertilizer regulation is needed. When the absolute value of the soil moisture difference is greater than the preset threshold value, it means that the fruit trees to be water-fertilizer regulated have problems of drought or excessive water, and water regulation needs to be performed through step S6. When the absolute value of the nutrient concentration difference is greater than the preset threshold value, it means that the fruit trees to be water-fertilizer regulated have problems of insufficient or excessive fertility, and nutrient content regulation needs to be performed through step S7. The preset thresholds corresponding to the absolute values ​​of the soil moisture difference and the absolute values ​​of the nutrient concentration difference are specifically set by the staff according to actual conditions, such as both taking values ​​of 0.

[0108] S6, based on the data collected in step S5, the soil moisture difference value and the irrigation amount control model, determining the water control strategy, including the following steps:

[0109] S61, when the soil moisture difference value of the fruit tree to be regulated by water and fertilizer is less than 0, digging ditches and draining water for the fruit tree to be regulated by water and fertilizer to reduce the soil moisture of the fruit tree to be regulated by water and fertilizer to avoid the problem of root rot of the fruit tree to be regulated by water and fertilizer due to excessive soil moisture, and when the soil moisture difference value of the fruit tree to be regulated by water and fertilizer is greater than 0, entering step S62;

[0110] S62, input the soil moisture difference value and the current and next day's average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall of the fruit tree to be regulated by water and fertilizer into the irrigation quantity regulation model to obtain the irrigation watering quantity. When the irrigation watering quantity is not greater than 0, no irrigation is performed. When the irrigation watering quantity is greater than 0, enter step S63;

[0111] It should be noted that the current and next day's average daily temperature, average daily light intensity, average daily air humidity, average daily wind speed and average daily rainfall of the fruit trees to be regulated by water and fertilizer can be obtained through the data released by the Meteorological Bureau. If the above step S32 performs maximum-minimum normalization processing on the corresponding data, step S62 also first uses the maximum and minimum values ​​in step S32 for normalization processing, and then inputs them into the irrigation quantity regulation model;

[0112] S63, based on the daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall of the fruit trees to be regulated by water and fertilizer from the current day to the next week, the irrigation watering amount is corrected to generate an irrigation watering correction amount, and the calculation formula is as follows:

[0113]

[0114] It should be noted that κ2 is the second irrigation adjustment coefficient. are the average daily temperature, average daily light intensity, average daily air humidity, average daily wind speed and average daily rainfall of the fruit trees to be regulated by water and fertilizer from the current to the next week, ω1, ω2, ω3 and ω4 are all preset proportional coefficients. The greater the temperature, light intensity and wind speed, the easier it is to aggravate the drought of the fruit trees, and the greater the air humidity and rainfall, the easier it is to alleviate the drought of the fruit trees. In addition, the influence of temperature, light intensity and rainfall on the soil humidity of the fruit trees is the most significant, the influence of wind speed on the soil humidity of the fruit trees is second, and the influence of air humidity on the soil humidity of the fruit trees is even less. Therefore, on the basis of ω1+ω2+ω3+ω4=1, let 0<ω3<ω2<ω4≤ω1<1. The specific values ​​of ω1, ω2, ω3 and ω4 are set by the staff according to the actual situation and are not restricted here.

[0115] It should be noted that l is the irrigation watering amount generated by the irrigation amount control model, κ1 is the preset first irrigation adjustment coefficient, and the first irrigation adjustment coefficient κ1>1, the specific value of κ1 is set by the staff according to the actual situation, such as 1.2, 1.3, 1.5, etc., l' is the irrigation watering correction amount, and the irrigation watering correction amount is generated by combining the irrigation watering amount l, the first irrigation adjustment coefficient κ1 and the second irrigation adjustment coefficient κ2 generated by various environmental factors, which fully considers the influence of external environmental factors on the irrigation watering correction amount, ensuring that the soil moisture can reach the purpose of the suitable soil moisture range when the water is regulated for the fruit trees subject to water and fertilizer regulation according to the irrigation watering correction amount in the future;

[0116] S64: when the irrigation and watering correction amount is not greater than 0, irrigation and watering are not performed; and when the irrigation and watering correction amount is greater than 0, irrigation and watering are performed based on the irrigation and watering correction amount.

[0117] S7, based on the data collected in step S5, the nutrient concentration difference value and the nutrient content control model, determining the nutrient control strategy, including the following steps:

[0118] S71, when the nutrient concentration difference value of the fruit tree to be regulated by water and fertilizer is less than 0, irrigate and water the fruit tree to be regulated by water and fertilizer to reduce the nutrient concentration of the fruit tree to be regulated by water and fertilizer, and avoid the problem that the nutrient concentration of the soil is too high and causes adverse effects on the fruit tree to be regulated by water and fertilizer. When the nutrient concentration of the fruit tree to be regulated by water and fertilizer is greater than 0, enter step S72;

[0119] S72, inputting the nutrient concentration difference value, the current soil moisture of the fruit tree to be water-fertilizer regulated, the daily average temperature, the daily average light intensity, the daily average air humidity, the daily average wind speed and the daily average rainfall from the current day to the next week into the nutrient content regulation model to obtain the nutrient content of the fertilizer for fertilization;

[0120] It should be noted that the daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall of the fruit trees to be regulated by water and fertilizer from the current to the next week can be obtained through the data released by the Meteorological Bureau. If the above step S32 performs maximum-minimum normalization processing on the corresponding data, step S72 also first uses the maximum and minimum values ​​in step S32 for normalization processing, and then inputs them into the nutrient content regulation model;

[0121] It should be noted that when calculating the nutrient content of fertilizer for fertilization, a nitrogen content control model, a phosphorus content control model and a potassium content control model are needed to respectively calculate the nitrogen content of the fertilizer for fertilization, the phosphorus content of the fertilizer for fertilization and the potassium content of the fertilizer for fertilization;

[0122] S73, correcting the nutrient content of the fertilizer for fertilization to obtain a corrected amount of the nutrient content of the fertilizer for fertilization, and configuring fertilizers based on the corrected amount of the nutrient content of the fertilizer for fertilization for fertilization, wherein the calculation formula of the corrected amount of the nutrient content of the fertilizer for fertilization is as follows:

[0123] m'(i)=m(i)*η(i)

[0124] It should be noted that m'(i) is the correction amount of the i-th nutrient content of the fertilizer for fertilization, m(i) represents the i-th nutrient content of the fertilizer for fertilization, η(i) is the fertilization adjustment coefficient corresponding to m(i), and the fertilization adjustment coefficient η(i)>1, and the specific value of η(i) is set by the staff according to the actual situation, such as 1.2, 1.3, 1.5, etc., the purpose is to avoid the problem that the nutrient concentration after fertilization is only the lower limit of the suitable nutrient concentration range, which leads to the need for frequent fertilization. It is an existing technology to configure fertilizers according to the nitrogen content, phosphorus content and potassium content of fertilizers for fertilization, which will not be elaborated here.

[0125] Embodiment 2:

[0126] See also Figure 2 The present invention provides an orchard water and fertilizer control system, which is used to execute the orchard water and fertilizer control method in the above-mentioned embodiment 1, comprising:

[0127] The suitable interval generation module is used to determine the suitable soil moisture interval and suitable nutrient concentration interval of the fruit trees in each growth period based on the fruit yield as the evaluation benchmark;

[0128] A suitable interval selection module is used to determine the growth period of the fruit tree to be regulated by water and fertilizer based on the real-time morphological image, and to determine the suitable soil moisture interval and suitable nutrient concentration interval of the fruit tree to be regulated by water and fertilizer based on the growth period;

[0129] The control model building module is used to build an irrigation quantity control model and a nutrient content control model based on historical data. The historical data includes irrigation water quantity, nutrient content of fertilizers used for fertilization, soil moisture, nutrient concentration, daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall data;

[0130] The difference value judgment module is used to collect the current soil moisture and nutrient concentration data of the fruit trees to be regulated by water and fertilizer, and determine the soil moisture difference value and the nutrient concentration difference value in combination with the suitable soil moisture interval and the suitable nutrient concentration interval in step S2;

[0131] The control judgment module is used for not performing water and fertilizer control when the absolute value of the soil moisture difference value and the absolute value of the nutrient concentration difference value are both not greater than the preset threshold value, otherwise the daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall of the fruit trees to be watered and fertilized are collected from the current day to the next week, and the step is entered into step S6 when the absolute value of the soil moisture difference value is greater than the preset threshold value, and the step is entered into step S7 when the absolute value of the nutrient concentration difference value is greater than the preset threshold value;

[0132] A water control strategy generation module, used to determine the water control strategy based on the data collected in step S5, the soil moisture difference value and the irrigation amount control model;

[0133] The nutrient control strategy generation module is used to determine the nutrient control strategy based on the data collected in the above step S5, the nutrient concentration difference value and the nutrient content control model.

[0134] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0135] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0136] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0137] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for regulating water and fertilizer in an orchard, characterized in that: The steps include: S1, taking fruit yield as the evaluation benchmark, determine the suitable soil moisture range and suitable nutrient concentration range for fruit trees in each growth period; S2, determining the growth period of the fruit tree to be regulated by water and fertilizer based on the real-time morphological image, and determining the suitable soil moisture range and suitable nutrient concentration range of the fruit tree to be regulated by water and fertilizer based on the growth period; S3, constructing an irrigation quantity control model and a nutrient content control model based on historical data, the historical data including irrigation water quantity, nutrient content of fertilizers used for fertilization, soil moisture, nutrient concentration, daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall data; The step S3 comprises the following steps: S31, multiple fruit trees in the orchard are used as experimental fruit trees, and the data on irrigation watering amount, nutrient content of fertilizers used for fertilization, soil moisture, nutrient concentration, daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall of the experimental fruit trees are collected daily during each growth period in previous years; S32, using the same growth period as the fruit tree to be regulated by water and fertilizer as a screening condition, filtering out corresponding data from the data of step S31 to form a data set; S33, establishing an irrigation quantity control model based on a deep learning neural network, taking the soil moisture difference between the day after irrigation and the day of irrigation in the data set, as well as the daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall on the day of irrigation and the day after irrigation as input, taking the irrigation quantity on the day of irrigation as a label, training and testing the irrigation quantity control model to obtain an irrigation quantity control model that passes the test; S34, establishing a nutrient content control model based on a deep learning neural network, taking the difference in nutrient concentration between one week after fertilization and the day of fertilization, the soil moisture on the day of fertilization, and the daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall from the day of fertilization to one week after fertilization as input, taking the nutrient content of the fertilizer on the day of fertilization as a label, training and testing the nutrient content control model to obtain a nutrient content control model that passes the test; S4, collecting the current soil moisture and nutrient concentration data of the fruit trees to be regulated by water and fertilizer, and determining the soil moisture difference value and the nutrient concentration difference value in combination with the suitable soil moisture interval and the suitable nutrient concentration interval in step S2; S5, when the absolute value of the soil moisture difference value and the absolute value of the nutrient concentration difference value are both not greater than the preset threshold value, water and fertilizer regulation is not performed, otherwise the daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall of the fruit trees to be watered and fertilized are collected from the current day to the next week, and when the absolute value of the soil moisture difference value is greater than the preset threshold value, step S6 is entered, and when the absolute value of the nutrient concentration difference value is greater than the preset threshold value, step S7 is entered; S6, determining a water control strategy based on the data collected in step S5, the soil moisture difference value and the irrigation amount control model; S7, determining a nutrient control strategy based on the data collected in the above step S5, the nutrient concentration difference value and the nutrient content control model.

2. The method for regulating water and fertilizer in an orchard according to claim 1, characterized in that: The growth period includes the budding period, the flowering period, the fruit expansion period and the fruit ripening period, and the nutrient concentration includes the nitrogen element concentration, the phosphorus element concentration and the potassium element concentration.

3. The method for regulating water and fertilizer in an orchard according to claim 1, characterized in that: The step S1 comprises the following steps: S11, obtaining the soil moisture time series data, nutrient concentration time series data and fruit yield of each fruit tree in the orchard in previous years; S12, using the fruit yield being in the top column as a screening condition, screening out the fruit trees with the fruit yield being in the top column, and extracting the soil moisture time series data and the nutrient concentration time series data of the fruit trees; S13, using the budding period, flowering period, fruit expansion period and fruit maturity period as screening conditions, screening all the soil moisture time series data and nutrient concentration time series data extracted in step S12 to obtain a soil moisture data set and a nutrient concentration data set corresponding to the budding period, flowering period, fruit expansion period and fruit maturity period; S14, determining suitable soil moisture ranges and suitable nutrient concentration ranges in each growth period based on the soil moisture data set and the nutrient concentration data set.

4. The method for regulating water and fertilizer in an orchard according to claim 3, characterized in that: The step S14 comprises the following steps: S141, based on the mean and standard deviation of the soil moisture data set, determine the upper and lower limits of the suitable soil moisture range for the corresponding growing period, and the calculation formula is as follows: Among them, μRH, σ RH are the mean and standard deviation of the soil moisture data set, RHmax and RHmin are the upper and lower limits of the suitable soil moisture range for the corresponding growing period, and γ is a preset proportional coefficient greater than zero; S142, based on the mean and standard deviation of the nutrient concentration data set, determine the upper and lower limits of the appropriate nutrient concentration range for the corresponding growth period, and the calculation formula is as follows: Among them, μ C (i), σ C (i) are the mean and standard deviation of the nutrient concentration of the i-th nutrient in the nutrient concentration data set, i = 1, 2, 3, corresponding to nitrogen, phosphorus and potassium, respectively, C max (i) C min (i) are the upper and lower limits of the ith suitable nutrient concentration interval corresponding to the growth period, and δ is a preset proportional coefficient greater than zero.

5. The method for regulating water and fertilizer in an orchard according to claim 1, characterized in that: The step S2 comprises the following steps: S21, collecting a plurality of morphological images of fruit trees at different growth stages as a data set, and randomly dividing the data set into a training set and a test set, and marking the corresponding growth stage on each morphological image of the training set as a label; S22, constructing a fruit tree growth period judgment model based on a convolutional neural network, training the fruit tree growth period judgment model using a training set, and testing the fruit tree growth period judgment model using a test set to obtain a fruit tree growth period judgment model that passes the test; S23, taking real-time morphological images of the fruit trees to be regulated with water and fertilizer, and inputting the real-time morphological images into a growth period judgment model for fruit trees that have passed the test, so as to determine the growth period of the fruit trees to be regulated with water and fertilizer, and then determining the suitable soil moisture range and the suitable nutrient concentration range corresponding to this growth period.

6. The method for regulating water and fertilizer in an orchard according to claim 4, characterized in that: The calculation formulas for the soil moisture difference value and the nutrient concentration difference value are as follows: Among them, RH s , C s (i) are the current soil moisture of the fruit trees to be regulated by water and fertilizer, the concentration of the i-th nutrient, RH' max RH' min , C' max (i) C' min (i) are the upper limit of the suitable soil moisture range, the lower limit of the suitable soil moisture range, the upper limit of the i-th suitable nutrient concentration range, and the lower limit of the i-th suitable nutrient concentration range corresponding to the fruit trees to be regulated by water and fertilizer, respectively. ΔRH and ΔC(i) are the soil moisture difference value and the i-th nutrient concentration difference value of the fruit trees to be regulated by water and fertilizer, respectively.

7. The method for regulating water and fertilizer in an orchard according to claim 1, characterized in that: The step S6 comprises the following steps: S61, when the soil moisture difference value of the fruit tree to be regulated by water and fertilizer is less than 0, digging ditches and draining water for the fruit tree to be regulated by water and fertilizer, and when the soil moisture difference value of the fruit tree to be regulated by water and fertilizer is greater than 0, entering step S62; S62, input the soil moisture difference value and the current and next day's average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall of the fruit tree to be regulated by water and fertilizer into the irrigation quantity regulation model to obtain the irrigation watering quantity. When the irrigation watering quantity is not greater than 0, no irrigation is performed. When the irrigation watering quantity is greater than 0, enter step S63; S63, based on the daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall of the fruit trees to be regulated by water and fertilizer from the current day to the next week, the irrigation watering amount is corrected to generate an irrigation watering correction amount, and the calculation formula is as follows: Among them, κ2 is the second irrigation adjustment coefficient, are the average daily temperature, average daily light intensity, average daily air humidity, average daily wind speed and average daily rainfall of the fruit trees to be regulated by water and fertilizer from the current to the next week, ω1, ω2, ω3, ω4 are all preset proportional coefficients, and ω1+ω2+ω3+ω4=1, and 0<ω3<ω2<ω4≤ω1<1, l is the irrigation watering amount generated by the irrigation amount regulation model, κ1 is the preset first irrigation regulation coefficient, and the first irrigation regulation coefficient κ1>1, l' is the irrigation watering correction amount; S64: when the irrigation and watering correction amount is not greater than 0, irrigation and watering are not performed; and when the irrigation and watering correction amount is greater than 0, irrigation and watering are performed based on the irrigation and watering correction amount.

8. The method for regulating water and fertilizer in an orchard according to claim 4, characterized in that: The step S7 comprises the following steps: S71, when the nutrient concentration difference value of the fruit tree to be regulated by water and fertilizer is less than 0, irrigate the fruit tree to be regulated by water and fertilizer, and when the nutrient concentration of the fruit tree to be regulated by water and fertilizer is greater than 0, enter step S72; S72, inputting the nutrient concentration difference value, the current soil moisture of the fruit tree to be water-fertilizer regulated, the daily average temperature, the daily average light intensity, the daily average air humidity, the daily average wind speed and the daily average rainfall from the current day to the next week into the nutrient content regulation model to obtain the nutrient content of the fertilizer for fertilization; S73, correcting the nutrient content of the fertilizer for fertilization to obtain a corrected amount of the nutrient content of the fertilizer for fertilization, and configuring fertilizers based on the corrected amount of the nutrient content of the fertilizer for fertilization for fertilization, wherein the calculation formula of the corrected amount of the nutrient content of the fertilizer for fertilization is as follows: m'(i)=m(i)*η(i) Among them, m'(i) is the correction amount of the i-th nutrient content of the fertilizer for fertilization, m(i) represents the i-th nutrient content of the fertilizer for fertilization, η(i) is the fertilization adjustment coefficient corresponding to m(i), and the fertilization adjustment coefficient η(i)>1.

9. An orchard water and fertilizer control system, used to execute the orchard water and fertilizer control method according to any one of claims 1 to 8, characterized in that: include: The suitable interval generation module is used to determine the suitable soil moisture interval and suitable nutrient concentration interval of the fruit trees in each growth period based on the fruit yield as the evaluation benchmark; A suitable interval selection module is used to determine the growth period of the fruit tree to be regulated by water and fertilizer based on the real-time morphological image, and to determine the suitable soil moisture interval and suitable nutrient concentration interval of the fruit tree to be regulated by water and fertilizer based on the growth period; The control model building module is used to build an irrigation quantity control model and a nutrient content control model based on historical data. The historical data includes irrigation water quantity, nutrient content of fertilizers used for fertilization, soil moisture, nutrient concentration, daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall data; The difference value judgment module is used to collect the current soil moisture and nutrient concentration data of the fruit trees to be regulated by water and fertilizer, and determine the soil moisture difference value and the nutrient concentration difference value in combination with the suitable soil moisture interval and the suitable nutrient concentration interval in step S2; The control judgment module is used for not performing water and fertilizer control when the absolute value of the soil moisture difference value and the absolute value of the nutrient concentration difference value are both not greater than the preset threshold value, otherwise the daily average temperature, daily average light intensity, daily average air humidity, daily average wind speed and daily average rainfall of the fruit trees to be watered and fertilized are collected from the current day to the next week, and the step is entered into step S6 when the absolute value of the soil moisture difference value is greater than the preset threshold value, and the step is entered into step S7 when the absolute value of the nutrient concentration difference value is greater than the preset threshold value; A water control strategy generation module, used to determine the water control strategy based on the data collected in step S5, the soil moisture difference value and the irrigation amount control model; The nutrient control strategy generation module is used to determine the nutrient control strategy based on the data collected in the above step S5, the nutrient concentration difference value and the nutrient content control model.

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