Balanced water and fertilizer management method for yield and quality of greenhouse tomatoes

Abstract

The invention discloses a balanced water and fertilizer management method for greenhouse tomato yield and quality, which is characterized in that a group benefit value, an individual regret value and a compromise evaluation value of each test water and fertilizer scheme are obtained by adopting a CRITIC-VIKOR comprehensive evaluation model, and then a wormcast irrigation management strategy meeting compromise requirements is obtained by comparing the group benefit value, the individual regret value and the compromise evaluation value. Compared with the prior art, the method has the advantages that the CRITIC-VIKOR comprehensive evaluation model has remarkable advantages in greenhouse drip irrigation tomato water and fertilizer management optimization, the core advantage of the method is that compromise thoughts are fused, all indexes are comprehensively analyzed and evaluated in subjective and objective aspects, the CRITIC method is mainly used for objective weighting, and the method has the advantages of being high in evaluation accuracy and high in evaluation efficiency. The comparison strength and conflict between indexes are comprehensively considered, and the group utility maximization and the individual regret minimization are comprehensively considered by the VIKOR model; in addition, compromise thoughts can be integrated according to preferences of decision makers, and higher sorting stability and credibility are achieved.

Description

Technical Field

[0001] This invention belongs to the field of greenhouse crop production management technology, specifically relating to a balanced water and fertilizer management method for greenhouse tomatoes to improve yield and quality. Background Technology

[0002] Tomatoes are a highly nutritious and economically valuable horticultural crop, now widely cultivated worldwide. However, greenhouse cultivation often involves continuous cropping of a single crop for many years, leading to severe continuous cropping obstacles. This damages soil structure, reduces fertility, lowers crop yield, degrades quality, and wastes water resources. Numerous studies have shown that drought stress reduces crop yield, while excessive irrigation causes severe waterlogging, hindering root respiration and reducing both yield and quality. Insufficient fertilizer application fails to meet the crop's nutritional needs, resulting in stunted growth and lower yields, while excessive application causes nitrate pollution, exacerbates soil salinity, and causes seedling burn, further reducing yields. In Northeast my country, due to its high latitude, fresh vegetables are mostly supplied by greenhouses, but farmers often employ unreasonable fertilization and irrigation strategies in pursuit of high yields, leading to soil structure damage, reduced crop yields, and lower quality. Solving these problems requires more scientific water and fertilizer management schemes. Therefore, it is urgent to explore the optimal combination of vermicompost and water through gradient experiments to achieve high yields, high quality, and efficient water resource utilization.

[0003] Currently, agricultural water and fertilizer management optimization models have gradually transitioned from single models to multi-objective comprehensive evaluation models. Previously, many scholars used methods such as grey relational analysis, principal component analysis, analytic hierarchy process (AHP), and TOPSIS; now, these are mostly used in combination. However, the selection of the optimal water and fertilizer scheme still largely relies on TOPSIS. But TOPSIS cannot consider the trade-offs between schemes, only utilizing partial information from the data. It doesn't adequately explore the complex relationships and internal structures between data points, and the results can deviate significantly from actual production due to differences in subjective and objective weighting methods. To address this issue, we need to collect more data and employ more advanced models to further optimize greenhouse water and fertilizer management, obtaining more scientific, reasonable, accurate, and stable evaluation results. Based on these reasons, we explored whether new models could improve water and fertilizer management optimization. Ultimately, we discovered the VIKOR multi-attribute decision model, which comprehensively considers maximizing group utility and minimizing individual regret. Furthermore, it incorporates trade-off ideas based on decision-makers' preferences, better reflecting the need to balance comprehensive benefits in actual decision-making, and exhibiting higher ranking stability and reliability. Furthermore, considering the influence of subjective preferences in this model, we also introduce the CRITIC method for objective weighting, comprehensively considering the comparative strength and conflict between indicators to make the obtained weights more scientific and reasonable. This method aims to overcome the shortcomings of a single evaluation model, integrate compromise ideas, and further improve the objectivity and accuracy of decision-making through a comprehensive evaluation model. It provides theoretical support for water and fertilizer management and green, efficient, and sustainable production of agricultural greenhouse crops, and provides technical support for the formulation of precision drip irrigation and fertilization strategies in greenhouse tomato cultivation. Summary of the Invention

[0004] The purpose of this invention is to provide a balanced water and fertilizer management method for greenhouse tomatoes to improve yield and quality, overcome the shortcomings of existing technologies, explore the effects of applying vermicompost combined with irrigation on yield, quality, and water productivity of greenhouse tomatoes in Northeast China, collect experimental data, adopt CRITIC-VIKOR comprehensive evaluation, optimize the vermicompost water management strategy for greenhouse drip-irrigated tomatoes in Northeast China by comprehensively considering water-saving, high-yield, and high-quality objectives, and seek the optimal vermicompost water management strategy suitable for greenhouse drip-irrigated tomatoes in Northeast China based on experimental results analysis, model simulation analysis, and comprehensive evaluation results.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A balanced water and fertilizer management method for greenhouse tomatoes, which improves yield and quality, is proposed. The CRITIC-VIKOR comprehensive evaluation model is used to obtain the group benefit value, individual regret value, and compromise evaluation value of each experimental water and fertilizer scheme. Then, by comparing these three values, a vermicompost irrigation management strategy that meets the compromise requirements is obtained. The specific steps are as follows: 1) Data collection: Under the same greenhouse conditions, several experimental plots were determined according to different treatments; specific indicators were measured and recorded during the key growth and harvest periods of tomatoes for subsequent comprehensive evaluation. 2) Data processing: The CRITIC method is used to calculate the specific indicators measured in step 1) and obtain the corresponding weights. Then, the VIKOR model is used in combination with the weights obtained by the CRITIC method to continue to calculate the group benefit value, individual regret value and compromise evaluation value of each experimental treatment. The ranking results of each treatment are obtained by ranking the three. 3) Determine the optimal model: Select the optimal vermicompost irrigation management strategy that suits the region from the ranking results.

[0006] Compared with the prior art, the beneficial effects of the present invention are: 1) The CRITIC-VIKOR comprehensive evaluation model adopted in this invention has significant advantages in optimizing water and nitrogen management of greenhouse drip irrigation tomatoes. Its core advantage lies in the integration of the compromise idea, which comprehensively analyzes and evaluates all indicators from both subjective and objective perspectives. The CRITIC method mainly performs objective weighting, comprehensively considering the comparative strength and conflict between indicators, so that the obtained weights are more scientific and reasonable. The VIKOR model comprehensively considers the maximization of group utility and the minimization of individual regret. 2) This invention can also incorporate compromise ideas according to the decision-maker's preferences, which is more in line with the need to balance comprehensive benefits in actual decision-making, and has higher ranking stability and credibility. Detailed Implementation

[0007] The technical solution of the present invention will be clearly and completely described below with reference to specific embodiments. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments.

[0008] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the specific embodiments used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the specific embodiments described below are some embodiments of the present invention. For those skilled in the art, other embodiments can be obtained based on these specific embodiments without creative effort. Therefore, the following detailed description of the embodiments of the present invention provided in the specific embodiments is not intended to limit the scope of the claimed invention, but merely to represent selected embodiments of the invention.

[0009] The experimental conditions and material preparation for this embodiment of the invention were conducted in Greenhouse No. 43 of the Beishan Research Base of the College of Water Resources, Shenyang Agricultural University. The greenhouse used was a Liaoshen III type solar greenhouse. The tomato variety used in the experiment was "Cui Xiao Fan". Custom-grown tomato seedlings were cultivated until they reached approximately 20 cm in height before being transplanted into the greenhouse. The tomatoes were planted in double rows on wide ridges, with two drip irrigation tapes on each ridge. The dripper flow rate was 2.0 L·h. -1 The dripper spacing is 0.4m, and the drip irrigation pressure is 0.1~0.3Mpa. A 1m long plastic film is buried between each treatment cell to prevent lateral seepage of soil moisture.

[0010] The experiment employed a completely randomized block design, with two factors: vermicompost application rate and irrigation amount. Vermicompost treatment was applied by mixing purchased vermicompost with undisturbed soil from the planting area and then rotary tilling. The vermicompost application rate was V1: 150 t·hm². -2 V2: 300 t·hm -2 V3: 450t·hm -2 The irrigation amount was controlled by the degree of water level drop in the evaporation pan, with the irrigation amount for each treatment being W1:0.6ET. gage W2: 0.8ET gage W3: 1.0ET gage Nine treatments (V1W1, V1W2, V1W3, ​​V2W1, V2W2, V2W3, V3W1, V3W2, and V3W3) were obtained by combining the above earthworm casting application rates with irrigation rates. Each treatment was replicated three times, for a total of 27 experimental plots.

[0011] The earthworm castings used are earthworm fermented organic fertilizer produced by Hebei Wolme Biotechnology Co., Ltd.

[0012] This invention provides a balanced water and fertilizer management method for greenhouse tomatoes that improves yield and quality. It employs the CRITIC-VIKOR comprehensive evaluation model to obtain the group benefit value, individual regret value, and compromise evaluation value of each experimental water and fertilizer scheme. Then, by comparing these three values, the optimal vermicompost irrigation management strategy that meets the compromise requirements is obtained. The specific steps are as follows: 1) Data collection: Under the same greenhouse conditions, several experimental plots were determined according to different treatments; specific indicators were measured and recorded during the key growth stages and harvest period of tomatoes for subsequent comprehensive evaluation; growth data such as plant height, leaf area, and photosynthesis were collected at different stages of tomato growth to determine the effects of earthworm castings and irrigation on tomato growth and development; mature fruits from each treatment were harvested at the tomato harvest period to determine their quality indicators, such as vitamin C content (Vc), soluble sugar content (SS), total soluble solids content (TSS), organic acids (OA), and sugar-acid ratio (SAR); the total weight of tomato fruits and irrigation amount throughout the entire growth period were recorded to calculate fruit yield (Y) and water productivity (WP) and to conduct a comprehensive evaluation. 2) Data processing: The CRITIC method was used to calculate the specific indicators measured in step 1) and obtain their corresponding weights. Then, the VIKOR model was used in conjunction with the weights calculated by the CRITIC method to further calculate the group benefit value, individual regret value, and compromise evaluation value for each experimental treatment. The ranking of each treatment was obtained by ranking these three values. The standardized data of each treatment (V1W1 to V3W3) were input to finally obtain the group benefit value, individual regret value, and compromise evaluation value for each experimental water and fertilizer scheme. The decision mechanism coefficient was then analyzed. Sensitivity analysis was conducted to rank the treatments based on their effectiveness, and the coefficients of different decision-making mechanisms were analyzed. The calculated ranking results are subjected to Kendall correlation analysis to determine the set of results with the strongest correlation and the most stable ranking results as the final ranking results. 3) Determine the optimal model: From the ranking results, determine the best water and fertilizer irrigation management strategy that suits the region, and jointly determine the best water and fertilizer irrigation treatment combination that meets the compromise requirements.

[0013] The specific calculation process for data processing in step 2) of this embodiment of the invention is as follows: 11) Construct the decision matrix, assuming it exists. Processing ,have Evaluation indicators Decision matrix Indicates the first The first process in the Evaluation values ​​under each indicator, among which , ; Formula (1) 12) Data standardization, including positive and negative indicators, and calculation of the comparative strength of the indicators: using standard deviation as the measure, the first... Standard deviation of each indicator Calculate using the following formula: Formula (2) In the formula: It is the first The mean of each indicator; for positive indicators, the higher the value, the better; for negative indicators, the lower the value, the better. The formula for calculating the positive indicator is: Formula (3) The formula for calculating the negative indicator is: Formula (4) 13) Calculate the conflict between indicators. The conflict between indicators is measured by the Pearson correlation coefficient. Conflict between this indicator and all other indicators The calculation formula is: Formula (5) In the formula, It is the first The first indicator and the first The Pearson correlation coefficient between the indicators is calculated using the following formula: Formula (6) 14) Calculate the information content of the indicators Formula (7) 15) Determine the weights of the indicators. Weight of each indicator The calculation formula is: Formula (8) And satisfy 16) Calculate the population benefit value of each treatment to the positive ideal solution using the VIKOR model. and individual regret value Group benefit value and individual regret value The calculation formulas are as follows: Formula (9) Formula (10) In the formula, Representative indicators The ideal solution is as follows: Representative indicators The negative ideal solution is as follows. Representative processing The next One indicator, It is an indicator The weights are calculated using step 15); Reflects the first The overall deviation of a treatment from the ideal solution across all indicators reflects the maximization of group benefits. Reflects the first The maximum deviation of a treatment from the ideal solution under a certain index reflects the minimization of individual regret; 17) Calculate the compromise evaluation value compromise evaluation value A coefficient is set to measure the overall performance of each process. Weights used to control whether decision outcomes are biased towards group utility or individual regret. The larger the value, the more the result leans towards group utility; conversely, the smaller the value, the more it leans towards individual regret. The calculation formula is as follows: Formula (11) In the formula, , , , , It is the decision matrix coefficient, usually It reflects the degree to which decision-makers prefer group benefits over individual regrets; when At times, more emphasis is placed on group benefits; when At times, more attention is paid to individual regrets; when At the same time, both should be given equal importance; 18) Scheme ranking and selection, , and Sort them from smallest to largest to obtain the corresponding sorting results; If the following two conditions are met, then the compromise solution (optimal solution) is: Processing the smallest value : Condition 1 (Acceptable Advantage): , in yes The second smallest solution, ; Formula (13) Condition 2 (Acceptable stability): Too Sort or Optimal handling in sorting; If neither of the above two conditions is met, a compromise solution is provided: If only condition 1 is not met, then the compromise is as follows: and ; If only condition 2 is not met, then the compromise is as follows: ,in It is to satisfy The largest sequence number.

[0014] After two years of repeated trials and verification, and comprehensive evaluation using the CRITIC-VIKOR comprehensive evaluation model, the optimal earthworm casting irrigation management mode of this invention was determined to be: applying 450 t·hm -2 Earthworm castings, used for irrigation of 0.6 ET gage The water volume, i.e., V3W1 treatment. This model can significantly improve fruit quality and water resource utilization efficiency while ensuring high tomato yield, achieving cost reduction, efficiency improvement, and sustainable development in greenhouse tomato production.

[0015] Table 1 Comparison of indicator weights in 2023 and 2024 Note: In the table, C, I, and W represent the conflict, information content, and weight of each indicator calculated using the CRITIC method, respectively. Table 1 shows the indicator weights for 2023 and 2024 calculated using the CRITIC method. Analysis of Table 1 reveals that the overall weights of the indicators remained relatively stable between 2023 and 2024, but the structure changed slightly: the weights of yield and water productivity (WP) both increased, from 15.20% to 17.11% and from 18.52% to 19.05%, respectively, indicating their increased importance in the comprehensive evaluation. Meanwhile, the weights of vitamin C (VC), soluble sugars (SS), total soluble solids (TSS), and sugar-acid ratio (SAR) all decreased slightly, reflecting a weakening relative influence in the system; the weight of organic acids (OA) increased slightly. Overall, water productivity had the highest weight for two consecutive years, highlighting its core position in the evaluation system, while the increased importance of yield may indicate a greater emphasis on output efficiency in decision-making.

[0016] Table 2 shows the correlation between the measured indicators and the ranking results calculated from the coefficient values ​​of different decision-making mechanisms. Note: The values ​​in Table 2 represent the correlation between the measured indicators and the ranking results calculated from the coefficient values ​​of different decision-making mechanisms. The larger the absolute value, the stronger the correlation. The asterisks (*) after the numbers indicate significance at the 0.05, 0.01, and 0.001 levels, respectively. No asterisk indicates no significance.

[0017] Table 2 shows the coefficients for different decision-making mechanisms ( Kendall correlation analysis was performed on the ranking results obtained under different decision-making mechanism coefficients and the selected indicators. The table shows the Kendall correlation between the ranking of each indicator and the final result. Overall, most indicators show a significant negative correlation, indicating that an increase in the value of these indicators often leads to a decrease in the overall ranking (the lower the ranking value, the better). Among them, total soluble solids (TSS) shows a significant negative correlation in most indicators. The value below this threshold shows the strongest negative correlation (up to -0.944), indicating that this indicator is most sensitive to ranking changes and its direction is consistent. Organic acids (OA), on the other hand, show a significant positive correlation, indicating that an increase in their value leads to a ranking improvement. As values ​​change, the correlation strength of some indicators fluctuates; for example, water productivity (WP) changes. The correlation weakens around 0.5, indicating that the choice of decision-making mechanism coefficient affects the contribution of different indicators in the evaluation. This analysis suggests that decision-makers can adjust... Values ​​are used to balance or emphasize the influence of certain indicators in the overall evaluation.

[0018] Table 3. Ranking results calculated from selected indicators for each treatment in 2023 and 2024. Note: The results in Table 3 are for this analysis when the decision mechanism coefficient... The result is obtained when the value is 0.7. Here, S, R, and Q represent the group effect value, individual regret value, and compromise evaluation value, respectively. The treatment schemes corresponding to the ranking results 1 and 2 are the ideal treatment schemes that meet the requirements.

[0019] Table 3 shows the ranking results calculated from the selected indicators for each treatment in 2023 and 2024. This table illustrates the ranking of the decision-making mechanism coefficient. When the coefficient of performance (COP) is 0.7, the CRITIC-VIKOR method is used to comprehensively evaluate the treatments in 2023 and 2024, including combinations of vermicompost application amount (V) and irrigation amount (W). Here, the S value represents population utility, the R value represents individual regret, and the Q value is the comprehensive compromise evaluation value. A smaller Q value indicates better overall performance, and the treatments are ranked accordingly. The results show that V3W1 performed best in Q value for two consecutive years, ranking first, indicating that this treatment is the most ideal in comprehensively balancing population utility and individual regret; followed by V3W2, ranking second. V1W3 (the combination of applying the least amount of vermicompost and the most irrigation) had the highest Q value, ranking ninth, indicating the worst performance. Overall, the treatments with the highest amount of vermicompost (V3) performed well under various water conditions, while the treatments with the lowest amount of vermicompost (V1) ranked low among all treatments, indicating that the greater the amount of vermicompost applied, the greater the advantage in the comprehensive evaluation system.

[0020] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for balanced water and fertilizer management to improve the yield and quality of greenhouse tomatoes, characterized in that, The CRITIC-VIKOR comprehensive evaluation model was used to obtain the group benefit value, individual regret value, and compromise evaluation value of each experimental water and fertilizer scheme. Then, by comparing the three, the earthworm casting irrigation management strategy that meets the compromise requirements was obtained. The specific processing of each step is as follows: 1) Data collection: Under the same greenhouse conditions, several experimental plots were determined according to different treatments; specific indicators were measured and recorded during the key growth and harvest periods of tomatoes for subsequent comprehensive evaluation. 2) Data processing: The CRITIC method is used to calculate the specific indicators measured in step 1) and obtain the corresponding weights. Then, the VIKOR model is used in combination with the weights obtained by the CRITIC method to continue to calculate the group benefit value, individual regret value and compromise evaluation value of each experimental treatment. The ranking results of each treatment are obtained by ranking the three. 3) Determine the optimal model: Select the optimal vermicompost irrigation management strategy that suits the region from the ranking results.

2. The method for balanced water and fertilizer management of greenhouse tomatoes according to claim 1, characterized in that, The number of test plots shall not be less than 27.

3. The method for balanced water and fertilizer management of greenhouse tomatoes to improve yield and quality according to claim 1, characterized in that, The specific indicators include, but are not limited to: plant height, stem diameter, leaf area index (L), dry matter of each organ, number of fruits per plant, weight of a single fruit, total yield (Y), vitamin C content (VC), soluble solids content (TSS), soluble sugar content (SS), organic acid content (OA), and water productivity (WP).

4. The method for balanced water and fertilizer management of greenhouse tomatoes according to claim 1, characterized in that, The organs referred to are any one of the following: fruit dry matter (FDM), stem dry matter (SDM), root dry matter (RDM), and leaf dry matter (LDM).

5. The method for balanced water and fertilizer management of greenhouse tomatoes according to claim 1, characterized in that, The specific calculation process for data processing in step 2) is as follows: 11) Construct the decision matrix, assuming it exists. Processing ,have Evaluation indicators Decision matrix Indicates the first The first process in the Evaluation values ​​under each indicator, among which , ; 12) Data standardization, including positive and negative indicators, and calculation of the comparative strength of the indicators: using standard deviation as the measure, the first... Standard deviation of each indicator Calculate using the following formula: In the formula: It is the first The average of the indicators; for positive indicators, the higher the value, the better; for negative indicators, the lower the value, the better. The formula for calculating the positive indicator is: The formula for calculating the negative indicator is: 13) Calculate the conflict between indicators. The conflict between indicators is measured by the Pearson correlation coefficient. Conflict between this indicator and all other indicators The calculation formula is: In the formula, It is the first The first indicator and the first The Pearson correlation coefficient between the indicators is calculated using the following formula: 14) Calculate the information content of the indicators 15) Determine the indicator weights, the first Weight of each indicator The calculation formula is: And satisfy ; 16) Calculate the population benefit value of each treatment to the positive ideal solution using the VIKOR model. and individual regret value Group benefit value and individual regret value The calculation formulas are as follows: In the formula, Representative indicators The ideal solution is as follows: Representative indicators The negative ideal solution is as follows. Representative processing The next One indicator, It is an indicator The weights are calculated in step 15); Reflects the first The overall deviation of a treatment from the ideal solution across all indicators reflects the maximization of group benefits. Reflects the first The maximum deviation of a treatment from the ideal solution under a certain index reflects the minimization of individual regret; 17) Calculate the compromise evaluation value compromise evaluation value A coefficient is set to measure the overall performance of each process. Weights used to control whether decision outcomes are biased towards group utility or individual regret. The larger the value, the more the result leans towards group utility; conversely, the smaller the value, the more it leans towards individual regret. The calculation formula is as follows: In the formula, , , , , It is the decision matrix coefficient, usually It reflects the degree to which decision-makers prefer group benefits over individual regrets; when At times, more emphasis is placed on group benefits; when At times, more attention is paid to individual regrets; when At the same time, both should be given equal importance; 18) Handle sorting and selection, and... , and Sort them from smallest to largest to obtain the corresponding sorting results; If the following two conditions are met, then the compromise solution (optimal solution) is: Handling the smallest value: Condition 1 (Acceptable Advantage): ,in yes The second smallest value is processed. , The total number of all processes; Condition 2 (Acceptable stability): Too Sort or Optimal handling in sorting; If neither of the above two conditions is met, a compromise solution is provided: If only condition 1 is not met, then the compromise is as follows: and ; If only condition 2 is not met, then the compromise is as follows: ,in It is to satisfy The largest sequence number.

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