Sweet potato appearance quality evaluation method and system based on growth environment

Abstract

The present application provides a kind of sweet potato appearance quality evaluation method and system based on growth environment, it is related to sweet potato quality evaluation technical field, including: sweet potato planting area is divided into multiple monitoring areas, each monitoring area is numbered and adds attribute, constructs undirected graph, adds edge by the space information between nodes, forms network.Each node is placed in independent community, node is moved to the community of neighbor node in succession, the increment of modularity is calculated, until the node community ownership no longer changes.According to the condition of each community node, determine the growth health index, microbial activity index and environmental adaptability index, and then calculate the quality evaluation index of each community.Based on average tuber weight, neatness and tuber length-width ratio, the quality evaluation index is corrected, and the comprehensive quality index is obtained, to judge the quality grade of sweet potato in each community.The present application can truly reflect the growth conditions of sweet potatoes in different areas, so as to reasonably adjust the planting management measures.

Description

TECHNICAL FIELD

[0001] The present application relates to sweet potato quality evaluation technical field, specifically to a kind of sweet potato appearance quality evaluation method and system based on growth environment. BACKGROUND

[0002] In the traditional appearance quality evaluation of sweet potato, often rely on artificial observation and experience judgment, this method is not only subjective, and lack of systematicness and scientific basis. Many evaluations mainly focus on the appearance and taste of the final product, ignoring the influence of key environmental factors during growth. Soil pH, humidity, nutrient content and environmental temperature and other factors have a significant impact on the growth and quality of sweet potato, but these variables are usually difficult to monitor and accurately evaluate in real time. In addition, the traditional method often fails to fully consider the interaction between factors, resulting in one-sidedness of the evaluation results, thereby affecting the scientificity and effectiveness of agricultural management decisions.

[0003] On the other hand, with the development of technology, spectral analysis technology has gradually become an important tool in the field of agriculture. However, existing spectral applications are often limited to single nutrient or soil property analysis, and their potential in comprehensive evaluation of sweet potato quality has not been fully explored. Even in some applications, the nutrient values and soil properties obtained through spectral data are often not effectively combined with real-time monitoring data, lacking a comprehensive analysis of the growth environment of sweet potato. This information silo phenomenon makes it difficult for agricultural producers to develop planting and management strategies, and fails to achieve the goal of precision agriculture. Therefore, there is an urgent need for a new type of systematic evaluation method that can comprehensively consider the comprehensive influence of the growth environment on the quality of sweet potato, overcome the shortcomings of existing technology, and improve the scientificity and accuracy of sweet potato appearance quality evaluation.

[0004] The above information disclosed in the background section is only used to enhance the understanding of the background of the present disclosure, and therefore it can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0005] The purpose of the present application is to provide a sweet potato appearance quality evaluation method and system based on growth environment to solve the problems raised in the background.

[0006] To achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0007] A sweet potato appearance quality evaluation method based on growth environment, the specific steps include:

[0008] Step 1: divide the sweet potato planting area into multiple monitoring areas with equal area, take each monitoring area as a node, number each node, and construct an undirected graph, add edges in the undirected graph according to the spatial information between nodes, and form an undirected graph network;

[0009] Step 2: Place each node in an independent community, for each node in the network in an undirected graph, move it to the community where all its neighbor nodes are, calculate the corresponding modular increment value of each movement, move the node to the neighbor community that maximizes the modular increment value, repeat the movement of the node until the community attribution of all nodes no longer changes;

[0010] Step 3: According to the node situation in each community, form a community node set, obtain the spectral image of the sweet potato sample at the node position, extract the reflectivity data of the key waveband from the spectral image, collect the pH value and soil moisture of the planting soil at the node position, and simultaneously obtain the dry matter ratio and environmental temperature of the sweet potato sample at the node position;

[0011] Step 4: Calculate the nitrogen content, phosphorus content, potassium content, soil microbial biomass, soluble sugar content and starch content in the sweet potato according to the reflected wave data, determine the growth health index according to the dry matter ratio, nitrogen content, phosphorus content, potassium content, soluble sugar content and starch content of the sweet potato sample, determine the microbial activity index according to the soil microbial biomass, soil moisture and environmental temperature, and determine the environmental adaptability index according to the soil pH value, soil moisture and environmental temperature;

[0012] Step 5: Determine the quality evaluation index for reflecting the quality of sweet potato at each node according to the growth health index, microbial activity index and environmental adaptability index, and take the average value of the quality evaluation indexes of all nodes in the community as the quality evaluation index of the community;

[0013] Step 6: Obtain the average tuber weight, tuber uniformity and tuber length-width ratio in the community, correct the quality evaluation index based on the average tuber weight, tuber uniformity and tuber length-width ratio, obtain the comprehensive quality index, compare the comprehensive quality index with the preset threshold value, and according to the comparison result, divide the quality of sweet potato in the community into three grades, which are: low quality, medium quality and high quality.

[0014] Further, the calculation formula of the modular increment value is as follows:

[0015] ;

[0016] In the formula, is the modular increment value, is the weight sum of edges in the target community, is the weight sum of all edges in the target community, is the edge weight sum of the node , is the index of the node, is the index of the node, is the total edge weight sum of the network.

[0017] According to the calculation method of the modular value-added, each node is moved to a neighbor community that maximizes the modular value-added, and the movement of the nodes is repeated until the community attribution of all nodes no longer changes.

[0018] Further, the key wave band refers to a wave band in a spectral image that can reflect nitrogen content, phosphorus content, potassium content and soil microbial biomass;

[0019] The dry matter ratio is obtained according to the following specific logic: the sweet potato sample is cleaned to remove soil and impurities, the cleaned sweet potato is placed in an oven, the temperature is set to 70 DEG C, and drying treatment is performed until the mass of the sweet potato no longer changes, the dried sweet potato is weighed using an electronic balance, the dry matter weight is recorded, and the dry matter ratio is calculated:

[0020] ;

[0021] Wherein, the dry matter ratio, the dry matter weight, the wet weight of the sweet potato before drying;

[0022] The nitrogen content is calculated according to the reflected wave data, and the formula is as follows:

[0023] ;

[0024] Wherein, the nitrogen content, the reflectivity of the 970nm wave band, the reference wave band, which is the reflectivity of the 550nm wave band, a constant for reflecting the influence of the nitrogen content of a specific plant species on the reflectivity ratio;

[0025] The phosphorus content is calculated according to the reflected wave data, and the formula is as follows:

[0026] ;

[0027] Wherein, the phosphorus content, the reflectivity of the 520nm wave band, a constant for reflecting the influence of the phosphorus content of a specific plant species on the reflectivity ratio;

[0028] The potassium content is calculated according to the reflected wave data, and the formula is as follows:

[0029] ;

[0030] Wherein, Potassium content, The reflectivity is in the 850nm band. This is a constant used to reflect the effect of potassium content on the reflectance ratio of a specific plant species;

[0031] The formula used to calculate the soluble sugar content based on reflected wave data is as follows:

[0032] ;

[0033] in, This refers to the soluble sugar content. The reflectivity is in the 1200nm band. This is a constant used to reflect the effect of the soluble sugar content of a specific plant species on the reflectance ratio;

[0034] The starch content is calculated based on the reflected wave data using the following formula:

[0035] ;

[0036] in, This refers to the soluble sugar content. The reflectivity is in the 2100nm band. This is a constant used to reflect the effect of starch content on the reflectance ratio of a specific plant species;

[0037] The formula used to calculate microbial biomass based on reflected wave data is as follows:

[0038] ;

[0039] in, For microbial biomass, The reflectivity is at the 1450nm wavelength. This is a constant used to reflect the influence of microbial biomass on the reflectance ratio in a specific soil type;

[0040] The ambient temperature of the planting area was collected using a temperature sensor. This ambient temperature was measured at a height of 0.2-0.5 meters above the ground and denoted as [missing information]. ;

[0041] Using a pH sensor and a humidity sensor, the pH value and soil moisture of the planting soil were obtained and recorded as follows: and .

[0042] Furthermore, an optimal pH value and a suitable threshold range are set, with the optimal pH value falling within the suitable threshold range. If the soil pH value exceeds the threshold range, the absolute difference between the soil pH value and the optimal pH value is calculated and denoted as... If the soluble sugar content or the starch content of sweet potato does not exceed the threshold range, the absolute difference between the soluble sugar content or the starch content and the corresponding optimal value is calculated, respectively, and is denoted as and If the soluble sugar content or the starch content of sweet potato does not exceed the threshold range, the absolute difference between the soluble sugar content or the starch content and the corresponding optimal value is calculated, respectively, and is denoted as

[0043] The growth health index is calculated according to the following formula:

[0044] ;

[0045] wherein, is the growth health index, is the dry matter ratio, is the ideal value of the dry matter ratio, and are the reference values of the soluble sugar content and the starch content, respectively, is the nitrogen content, is the ideal value of the nitrogen content, is the phosphorus content, is the ideal value of the phosphorus content, is the potassium content, is the ideal value of the potassium content, , and are preset proportion coefficients, and satisfy ;

[0046] The microbial activity index is calculated according to the following formula:

[0047] ;

[0048] wherein, is the microbial activity index, is the microbial biomass, is the ideal microbial biomass, is the soil humidity, is the ideal soil humidity, is the environmental temperature, is the ideal environmental temperature, is a proportion coefficient, and ;

[0049] The environmental adaptability index is calculated according to the following formula:

[0050] ;

[0051] wherein, an environmental adaptability index, a soil humidity, an ideal soil humidity, an environmental temperature, an ideal environmental temperature, , a preset proportionality coefficient, , and satisfies .

[0052] Further, a quality evaluation index for reflecting the quality of sweet potato at each node is determined according to the growth health index, the microbial activity index, and the environmental adaptability index, and the formula is as follows:

[0053] ;

[0054] wherein, is the quality evaluation index, is the growth health index, is the microbial activity index, is the environmental adaptability index, , , is a weight determined according to the analytic hierarchy process;

[0055] The average value of the quality evaluation indexes of all nodes in the community is taken as the quality evaluation index of the community, denoted as .

[0056] Further, the specific logic for determining the weight according to the analytic hierarchy process is as follows:

[0057] The growth health index, the microbial activity index, and the environmental adaptability index are marked, the values of the relative importance between each other are determined by the nine-scale method, and a judgment matrix is constructed, wherein the index of the growth health index is marked as 1, the index of the microbial activity index is marked as 2, and the index of the environmental adaptability index is marked as 3, and the constructed judgment matrix is:

[0058] ;

[0059] wherein, , both represent the index of the index, and , , represents the importance of the index with the index of relative to the index with the index of , the importance adopts the 1-9 scale method, and the greater the value is, the more important the index with the index of is compared with the index with the index of The greater the importance of the index, and , ;

[0060] Each element value in the judgment matrix is divided by the sum of its column to obtain a normalized judgment matrix. The average value of each row element value in the normalized judgment matrix is calculated, and the average value of the first row element value is taken as the weight of the growth health index, the average value of the second row element value is taken as the weight of the microbial activity index, and the average value of the third row element value is taken as the weight of the environmental adaptability index. The three weights are scaled in equal proportions with the constraint that the sum of the scaled values is equal to 1, and the scaled weights are taken as the proportional coefficients of the corresponding indexes.

[0061] Further, the average tuber weight, tuber uniformity and tuber length-width ratio in the community are obtained according to the following specific logic: a certain number of sweet potato plants are randomly dug in each community, all tubers are harvested, soil and roots are removed, each tuber is weighed to 0.1g using an electronic scale, and damaged or diseased tubers are excluded. The average mass is taken as the average tuber weight of the community, and the average tuber weight refers to the average weight of a single tuber, i.e. the total weight of all tubers harvested from the randomly dug sweet potato plants in each community divided by the total number of tubers, denoted as ; the tuber length-width ratio refers to the ratio of the length of the tuber to the diameter of the largest part of the tuber, denoted as ;

[0062] The tuber uniformity is calculated according to the following formula:

[0063] ;

[0064] In the formula, is the tuber uniformity, which reflects the uniformity of tuber size in the community, is the standard deviation of the tuber weight of the community;

[0065] The quality evaluation index is corrected based on the average tuber weight, tuber uniformity and tuber length-width ratio according to the following formula:

[0066] ;

[0067] In the formula, is the comprehensive quality index, is the average tuber weight, is the reference weight of the tuber, is the tuber uniformity, is the tuber length-width ratio, is the length-width ratio reference value, , and are preset weights, , and satisfy .

[0068] Furthermore, the comprehensive quality index The comparison with the preset threshold is based on the following logic:

[0069] when At that time, the sweet potatoes in the community were judged to be of low quality. These sweet potatoes are usually characterized by tubers that are too small or too large, have poor uniformity, and low dry matter content.

[0070] when At that time, the quality of sweet potatoes in the community was determined to be of medium quality grade. The weight of sweet potato tubers of this grade is concentrated within the range of optimal commercial specifications, and the uniformity is good, which meets market demand.

[0071] when At that time, the sweet potatoes in the community were judged to be of high quality. This grade of sweet potatoes not only meets all the requirements of medium quality, but also performs better in terms of internal quality indicators such as dry matter content and nutrient content.

[0072] in, For the comprehensive quality index, This is the preset evaluation threshold.

[0073] This invention also provides a sweet potato appearance quality evaluation system based on the growth environment. This system is used to execute the aforementioned sweet potato appearance quality evaluation method based on the growth environment, and includes:

[0074] The network construction module is used to select multiple monitoring areas in the sweet potato planting area, treat each monitoring area as a node, number each node, and construct an undirected graph. Based on the spatial information between each node, edges are added to the undirected graph to form an undirected graph network.

[0075] The community dynamic partitioning module is used to place each node in an independent community. For each node in the network of the undirected graph, it is moved to the community of all its neighboring nodes one by one. The corresponding modular increment of each move is calculated, and the node is moved to the neighboring community that maximizes the modular increment. The node is moved repeatedly until the community affiliation of all nodes no longer changes.

[0076] The multi-source data acquisition module is used to form a community node set based on the node situation within each community, acquire the spectral image of sweet potato samples at the location of each node within the community, extract the reflectance data of key bands from the spectral image, acquire the pH value and soil moisture of the planting soil at the node location, and acquire the dry matter ratio and ambient temperature of the sweet potato samples at the node location.

[0077] An index calculation module is configured to calculate the nitrogen content, phosphorus content, potassium content, soil microbial biomass, soluble sugar content and starch content in sweet potatoes in the planting soil according to the reflected wave data, and determine the growth health index according to the dry matter ratio, nitrogen content, phosphorus content, potassium content, soluble sugar content and starch content of the sweet potato sample, determine the microbial activity index according to the soil microbial biomass, soil humidity and environmental temperature, and determine the environmental adaptability index according to the soil pH value, soil humidity and environmental temperature;

[0078] A quality preliminary evaluation aggregation module is configured to determine a quality evaluation index for reflecting the quality of sweet potatoes at each node according to the growth health index, microbial activity index and environmental adaptability index, and take the average value of the quality evaluation indexes of all nodes in the community as a quality evaluation index of the community;

[0079] A correction classification module is configured to obtain the average sweet potato weight, sweet potato neatness and sweet potato length-width ratio in the community, correct the quality evaluation index based on the average sweet potato weight, sweet potato neatness and sweet potato length-width ratio, obtain a comprehensive quality index, compare the comprehensive quality index with a preset threshold, and according to the comparison result, divide the quality of sweet potatoes in the community into three levels, i.e., low quality, medium quality and high quality.

[0080] Compared with the prior art, the beneficial effects of the present application are:

[0081] The present application establishes a sweet potato appearance quality evaluation method based on the growth environment, significantly improving the scientificity and accuracy of sweet potato appearance quality evaluation. First, the environmental data of each monitoring area is systematically processed using an undirected graph network structure, so that the spatial information between nodes can be fully utilized. This method can effectively identify key environmental factors affecting sweet potato growth, thereby providing more comprehensive evaluation results. Second, by extracting and analyzing the reflectivity of key wavebands from spectral images, the content of key quality indicators such as nitrogen, phosphorus and potassium in the soil can be accurately calculated. This analysis based on spectral technology avoids the qualitative judgment of nutrients in traditional methods, ensuring the objectivity and reliability of the data. In addition, the comprehensive evaluation of the growth health index, microbial activity index and environmental adaptability index can more comprehensively reflect the growth status and environmental adaptability of sweet potatoes, helping farmers to adjust production management strategies in a timely manner. Finally, the calculation of the comprehensive quality index and the comparison with the preset threshold make the quality classification of sweet potatoes more explicit, thereby providing a scientific basis for market supply and sales. Through this systematic evaluation method, farmers can not only improve the yield and quality of sweet potatoes, but also effectively promote the sustainable development of agriculture. BRIEF DESCRIPTION OF DRAWINGS

[0082] Figure 1 It is a schematic diagram of the overall method flow of the present application;

[0083] Figure 2 A schematic diagram of a system module of the present application. DETAILED DESCRIPTION

[0084] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to specific embodiments.

[0085] It should be noted that, unless otherwise defined, technical terms or scientific terms used in the present application should be understood as their common meanings to those having ordinary skills in the art to which the present application pertains. The terms "first", "second", and similar terms used in the present application do not denote any order, quantity, or importance, but are only used to distinguish different components. The terms "comprise", "include" and similar terms mean that the elements or objects before the terms encompass the elements or objects listed after the terms and their equivalents, and do not exclude other elements or objects. The terms "connect" or "connected" and similar terms do not mean physical or mechanical connection, but can include electrical connection, whether direct or indirect. The terms "upper", "lower", "left", "right", and the like only represent relative positional relationships, which can change when the absolute positions of the described objects change.

[0086] Embodiment:

[0087] Please refer to Figure 1 The present application provides a technical solution:

[0088] A sweet potato appearance quality evaluation method based on growth environment, the specific steps comprising:

[0089] Step 1: Select multiple monitoring areas in the sweet potato planting area, take each monitoring area as a node, number each node, and construct an undirected graph, add edges in the undirected graph according to the spatial information between nodes, and form an undirected graph network;

[0090] Step 2: Place each node in an independent community. For each node in the network in the undirected graph, move it to the community where all its neighbor nodes are located one by one, calculate the corresponding modularity increment of each movement, move the node to the neighbor community that maximizes the modularity increment, repeat the movement of the node until the community attribution of all nodes no longer changes;

[0091] In this embodiment, in the sweet potato planting area, a regular grid method is used to select the monitoring area, the area of each monitoring area is controlled within 10m x 10m, and the spatial distribution is uniform and covers different terrains and soil types. The center point of each monitoring area is taken as a node, and each node is numbered in order. When constructing an undirected graph, the edges are added according to the following rules: if the Euclidean distance between two nodes is ≤50m, then connect the edge in the undirected graph, and the edge weight is set as the inverse of the absolute difference of the soil moisture between the two nodes, to reflect the spatial correlation;

[0092] At initialization, each node is an independent community. Each node is traversed, and the modularity increment after moving to the adjacent community is calculated , The calculation formula is as follows:

[0093] ;

[0094] In the formula, is the modularity increment, is the weight sum of the edges in the target community (excluding the connection edges of node i before moving), is the weight sum of all edges in the target community (including the connection edges of node i and external nodes before moving), is the edge weight sum of node i, is the index of the node, is the total edge weight sum of the network;

[0095] According to the above calculation method of modularity increment, each node is moved to the neighbor community with the maximum modularity increment. Repeat the movement of the node until the community attribution of all nodes no longer changes. The community division method can automatically aggregate monitoring nodes with similar environmental characteristics into the same community through the modularity maximization algorithm. Specifically, the edge weight defined based on the inverse of the soil moisture difference makes the nodes with similar humidity have stronger connection strength. In the modularity increment In the calculation process, the algorithm will preferentially divide nodes with similar soil moisture into the same community while ensuring that the environmental characteristics between different communities are significantly different. This division results in high homogeneity within the community, manifested as consistency in key growth environment indicators such as soil moisture and nutrient content, while there is obvious environmental heterogeneity between different communities. The beneficial effects of this technical solution are: on the one hand, it ensures that the collected sweet potato growth data within the same community is comparable and representative, improving the accuracy of quality assessment; on the other hand, it provides a scientific basis for differentiated agricultural management, allowing precise irrigation, fertilization, and other agricultural operations based on the environmental characteristics of different communities, thereby optimizing resource allocation and improving sweet potato quality and yield. In addition, this community division method based on environmental similarity lays a scientific foundation for subsequent quality assessment index correction, enabling the final comprehensive quality index to truly reflect the actual quality level of sweet potatoes in each region.

[0096] The advantages of steps 1 and 2 are that by constructing an undirected graph network and classifying nodes into communities, the environmental data within the sweet potato planting area can be systematically integrated and analyzed. This structure not only effectively reflects the spatial relationship between nodes but also reveals the mutual influence of each node under different environmental conditions, thereby promoting precision agriculture management. Compared with existing technologies, this method overcomes the limitations of traditional single-index evaluation, providing a more comprehensive analysis of the growth environment through a comprehensive and dynamic data structure.

[0097] In this solution, this step can play an important role in promoting the overall solution. Through the construction of an undirected graph network, the influence of different environmental variables on sweet potato quality can be more accurately identified, and community affiliation can be dynamically optimized between nodes, thereby improving the accuracy of quality assessment. This systematic environmental analysis provides a solid foundation for subsequent quality assessment, making the final quality evaluation more scientific and reliable, thereby improving the overall efficiency of sweet potato cultivation and market competitiveness.

[0098] Step 3: According to the node conditions within each community, a community node set is formed, the spectral image of the sweet potato sample at the node location is obtained, and the reflectivity data of the key waveband is extracted from the spectral image. The pH value and soil moisture of the planting soil at the node location are collected, and the dry matter ratio and environmental temperature of the sweet potato sample at the node location are obtained;

[0099] In this embodiment, the key waveband refers to the waveband in the spectral image that can reflect the nitrogen content, phosphorus content, potassium content, and soil microbial biomass;

[0100] The dry matter ratio is obtained, and the specific logic is as follows: the sweet potato sample is cleaned to remove soil and impurities, the cleaned sweet potato is placed in an oven, the temperature is set to 70 DEG C, and the drying treatment is carried out until the mass of the sweet potato no longer changes, the dried sweet potato is weighed by using an electronic balance, the dry matter weight is recorded, and the dry matter ratio is calculated:

[0101] ;

[0102] Wherein, is the dry matter ratio, is the dry matter weight, is the wet weight of the sweet potato before drying;

[0103] The nitrogen content is calculated according to the reflected wave data, and the formula is as follows:

[0104] ;

[0105] Wherein, is the nitrogen content, is the reflectivity of the 970nm wave band, is the reflectivity of the reference wave band, which is the reflectivity of the 550nm wave band here, is a constant, which is used to reflect the influence of the nitrogen content of a specific plant species on the reflectivity ratio;

[0106] The phosphorus content is calculated according to the reflected wave data, and the formula is as follows:

[0107] ;

[0108] Wherein, is the phosphorus content, is the reflectivity of the 520nm wave band, is the reflectivity of the reference wave band, which is the reflectivity of the 550nm wave band here, is a constant, which is used to reflect the influence of the phosphorus content of a specific plant species on the reflectivity ratio;

[0109] The potassium content is calculated according to the reflected wave data, and the formula is as follows:

[0110] ;

[0111] Wherein, is the potassium content, is the reflectivity of the 850nm wave band, is the reflectivity of the reference wave band, which is the reflectivity of the 550nm wave band here, is a constant, which is used to reflect the influence of the potassium content of a specific plant species on the reflectivity ratio;

[0112] The soluble sugar content is calculated according to the reflected wave data, and the formula is as follows:

[0113] ;

[0114] wherein, is the soluble sugar content, is the reflectance in the 1200 nm band, is a constant used to reflect the influence of the soluble sugar content on the reflectance ratio for a specific plant species;

[0115] The starch content is calculated according to the reflected wave data, and the formula is as follows:

[0116] ;

[0117] wherein, is the soluble sugar content, is the reflectance in the 2100 nm band, is a constant used to reflect the influence of the starch content on the reflectance ratio for a specific plant species;

[0118] The microbial biomass is calculated according to the reflected wave data, and the formula is as follows:

[0119] ;

[0120] wherein, is the microbial biomass, is the reflectance in the 1450 nm band, is the reflectance in the reference band, which is the reflectance in the 550 nm band, is a constant used to reflect the influence of the microbial biomass on the reflectance ratio for a specific soil type;

[0121] The environmental temperature of the planting area is collected using a temperature sensor, which is the temperature data at a height of 0.2-0.5 meters from the ground, denoted as ;

[0122] The pH value and soil humidity of the planting soil are obtained using a pH sensor and a humidity sensor, respectively denoted as and .

[0123] The advantage of step 3 is that by obtaining the spectral images and environmental data of the nodes within the community, the influence of the sweet potato growing environment on its quality can be accurately analyzed. This process combines various environmental variables such as soil pH, humidity, and sweet potato dry matter ratio, which helps to comprehensively evaluate the growth conditions of sweet potatoes. Compared with the prior art, traditional methods often rely on only a small number of soil or plant samples for analysis, lacking dynamic monitoring of the entire planting environment, while this step can provide more details and higher accuracy.

[0124] In this approach, this step enhances the overall program by providing crucial foundational data and multi-dimensional information for subsequent quality assessments. This comprehensive environmental analysis not only improves the reliability of quality assessments but also helps farmers and agricultural managers monitor the dynamics of sweet potato growth in real time, enabling timely adjustments to management practices to optimize production and quality. This data-driven approach will contribute to improving the scientific rigor and sustainability of agricultural production.

[0125] Step 4: Calculate the nitrogen, phosphorus, and potassium content of the planting soil, soil microbial biomass, and soluble sugar and starch content in sweet potatoes based on the reflected wave data. Determine the growth health index based on the dry matter ratio, nitrogen, phosphorus, potassium, soluble sugar, and starch content of the sweet potato samples. Determine the microbial activity index based on soil microbial biomass, soil moisture, and ambient temperature. Determine the environmental adaptability index based on soil pH, soil moisture, and ambient temperature.

[0126] In this embodiment, an optimal pH value and a suitable threshold range are set, with the optimal pH value falling within the suitable threshold range. If the soil pH value exceeds the threshold range, the absolute difference between the soil pH value and the optimal pH value is calculated and denoted as . If the content is within the threshold range, it will not be included in the subsequent calculation of the environmental adaptability index. Similarly, if the soluble sugar content or starch content in sweet potatoes exceeds the threshold range, the absolute differences between the soluble sugar content and starch content and the corresponding optimal values ​​will be calculated and recorded as follows: and If the value does not exceed the threshold range, it will not be included in the subsequent calculation of the growth health index;

[0127] The formula used to calculate the growth health index is as follows:

[0128] ;

[0129] in, For growth and health index, The dry matter ratio is... This is the ideal value for the dry matter ratio. and These are the reference values ​​for soluble sugar content and starch content, respectively. Nitrogen content, This represents the ideal value for nitrogen content. Phosphorus content, This represents the ideal value for phosphorus content. Potassium content, This is the ideal value for potassium content. , and This is a preset proportional coefficient. , , ; this is because the dry matter ratio directly reflects the nutrient accumulation and energy storage of sweet potatoes, which is an important indicator of plant growth and health, so it is reasonable to give the highest weight to the dry matter ratio, indicating that its influence on the growth and health index is the greatest; the influence of nitrogen, phosphorus, potassium and other nutrients is relatively complex, although they are essential for plant growth, but they usually do not directly affect the overall growth of plants like dry matter ratio, soluble sugar content and starch content, so they are given a lower weight.

[0130] is a comprehensive index for evaluating the growth and health of sweet potatoes, reflecting the growth potential of sweet potatoes. It takes into account the dry matter ratio, soluble sugar and starch content, as well as the suitability of nitrogen, phosphorus, potassium and other nutrients. When increases, it means that the plant's growth condition is good, is also larger; when increases, it means that the deviation of the organic matter content in the current soil from the preset threshold value increases, which may have a negative impact on the healthy growth of sweet potatoes, so will decrease; when , , , or increases, it means that the deviation of the nutrient content in the soil from the ideal value increases, and too high or too low nutrient content will have a negative effect on the growth of sweet potatoes, so will decrease accordingly; that is, it indicates that and are positively correlated, , , , , and are negatively correlated.

[0131] The formula for calculating the microbial activity index is as follows:

[0132] ;

[0133] wherein is the microbial activity index, is the microbial biomass, is the ideal state of the microbial biomass, is the soil moisture, is the ideal state of the soil moisture, is the environmental temperature, is the ideal state of the environmental temperature, is a proportionality coefficient, and ;

[0134] is a comprehensive index for evaluating the activity status of microorganisms in the soil. It reflects the degree of influence of microbial biomass, soil humidity, and environmental temperature on microbial activity. When increases, it means that the microbial biomass in the planting soil deviates from the ideal value, and excessive microbial biomass can affect the diversity of soil microbial communities, leading to overpopulation of certain microbial species, thereby affecting the ecological balance, while insufficient microbial biomass can lead to soil fertility decline, reducing the productivity of the soil, so when increases, will increase accordingly; when increases, it means that the humidity of the planting soil deviates from the ideal value, and microorganisms are very sensitive to water demand, and excessive soil humidity can lead to anoxic environment, inhibiting the activity of certain microorganisms; while low humidity can cause dehydration of microorganisms, affecting their survival and reproduction, will increase accordingly;

[0135] When increases, it means that the temperature of the planting soil deviates from the ideal value, and the metabolic activity of microorganisms is closely related to temperature, and excessive or low temperature can inhibit the growth and reproduction of microorganisms, leading to reduced activity, so increases; that is, it indicates that , , is positively correlated with .

[0136] The formula for calculating the environmental adaptability index is as follows:

[0137] ;

[0138] wherein, is the environmental adaptability index, is the soil humidity, is the ideal soil humidity, is the environmental temperature, is the ideal environmental temperature, , is a preset proportionality coefficient, , This is because changes in humidity and temperature directly affect the growth of plants and the activity of microorganisms, so in the environmental adaptability assessment, the influence of temperature and humidity is considered to be more common and critical. Therefore, a larger The value can enhance the influence of humidity and temperature on the adaptability index, ensuring that the environmental adaptability index can provide corresponding feedback when the two parameters change significantly.

[0139] is a comprehensive index used to evaluate the adaptability of sweet potato to its environmental conditions. It takes into account factors such as soil pH, humidity, and temperature, reflecting the impact of environmental conditions on sweet potato. Deviation in pH can result in greater impact on soil health and plant growth, so when increases, decreases; when increases, it means that the humidity of the planting soil deviates from the ideal value, and the plant's root system may not be able to effectively absorb the required water. Low humidity can cause plants to exhibit drought symptoms, affecting their growth; high humidity can lead to root hypoxia, inhibiting the normal growth of plants, will decrease accordingly; when increases, it means that the temperature of the planting soil deviates from the ideal value, and extreme deviations in temperature can cause physiological processes to be hindered, high temperatures can cause cell damage to plants, and even cause physiological drought; low temperatures can cause growth to stop, and even cause frost damage, will be smaller; that is, , , and are negatively correlated.

[0140] The advantage of step 4 is that it can comprehensively and accurately evaluate the key nutrient components of soil and sweet potato samples and their growth and health status through the analysis of reflected wave data. This step combines various biochemical indicators such as nitrogen, phosphorus, potassium content, and microbial biomass, providing a more comprehensive growth and health index, microbial activity index, and environmental adaptability index. Compared with existing technologies, this method effectively overcomes the limitations of relying on a single indicator or traditional soil testing, and can more comprehensively reflect the growth environment and quality status of sweet potato.

[0141] In this scheme, the use of this step can play an important role in promoting the overall scheme, as it provides scientific basis and rich data support for the evaluation of sweet potato quality. This comprehensive analysis makes subsequent quality evaluation more reliable, helping farmers and managers to make more accurate agricultural management decisions based on empirical data. At the same time, by monitoring the health status of soil and plants in real time, management measures can be adjusted in a timely manner to optimize the growth conditions of sweet potato, improve the final product quality and yield.

[0142] Step 5: Determine the quality evaluation index for reflecting the quality of sweet potato at each node according to the growth health index, microbial activity index and environmental adaptability index, and take the average value of the quality evaluation index of all nodes in the community as the quality evaluation index of the community;

[0143] In this embodiment, the quality evaluation index for reflecting the quality of sweet potato at each node is determined according to the growth health index, microbial activity index and environmental adaptability index, and the formula is as follows:

[0144] ;

[0145] Wherein, is the quality evaluation index, is the growth health index, is the microbial activity index, is the environmental adaptability index, , , is the weight, which is determined according to the analytic hierarchy process;

[0146] represents the overall quality evaluation result, and the higher the value, the better the quality of the plant or ecosystem, and vice versa; reflects the growth condition of the plant, and the higher the value, the better the growth condition of the sweet potato, so that when increases, also increases; is used to measure the adaptability of environmental conditions to plant growth, and reflects the suitability of soil and climate conditions to plant growth. The higher the value, the more suitable the growth environment of sweet potato, the greater the value; represents the activity and diversity of microorganisms in the soil, and the higher the value, the greater the impact on nutrient supply and soil ecological balance, which has a negative impact on the quality of sweet potato, therefore , and are positively correlated, and are negatively correlated.

[0147] The formula amplifies the synergistic effect of key parameters through the exponential function, which is more in line with the non-linear accumulation law of biological quality formation, and can sensitively reflect the marginal influence of small changes in the index on sweet potato quality. The cubic root compresses the index, avoiding the dominance of a single indicator in the evaluation results. At the same time, the denominator introduces the adjustment effect of the microbial activity index, reflecting the potential inhibitory effect of the microbial activity index on sweet potato quality. The weight coefficient is determined by the analytic hierarchy process, ensuring that the formula can adjust the priority of parameters for different varieties or planting modes, enhancing the model's generalization ability. The exponential function always outputs positive, and the cubic root smooths the fluctuations of input parameters, making the evaluation results remain within a reasonable range even under extreme values, avoiding distorted scores caused by soil or climate abnormalities.

[0148] The average of all node quality evaluation indexes in the community is taken as the quality evaluation index of the community, denoted as .

[0149] The specific logic for determining the weight by the analytic hierarchy process is as follows:

[0150] The growth health index, microbial activity index, and environmental adaptability index are marked, and the relative importance values between each other are determined by the nine-scale method to construct the judgment matrix. The growth health index is marked as 1, the microbial activity index is marked as 2, and the environmental adaptability index is marked as 3. The constructed judgment matrix is:

[0151] ;

[0152] wherein, , both represent the index of the index, and , , represent the importance of the index of relative to the index of . The importance uses the 1-9 scale method, and the larger the value, the greater the importance of the index of compared to the index of , and , ;

[0153] Each element value in the judgment matrix is divided by the sum of its column to obtain a normalized judgment matrix. The average value of each row element value in the normalized judgment matrix is calculated, and the average value of the first row element value is taken as the weight of the growth health index, the average value of the second row element value is taken as the weight of the microbial activity index, and the average value of the third row element value is taken as the weight of the environmental adaptability index. The three weights are scaled in equal proportions with the constraint that the sum of the scaled values is equal to 1, and the scaled weights are taken as the proportionality coefficients of the corresponding indexes.

[0154] The advantage of step 5 is that it establishes a systematic quality evaluation model by integrating the growth health index, microbial activity index, and environmental adaptability index, which can accurately evaluate the quality of sweet potatoes at each node. This method not only integrates multiple dimensions of data, but also considers the influence of different environments and growth conditions on sweet potato quality, providing a more comprehensive and scientific quality analysis compared to traditional single-index evaluation.

[0155] Compared with the prior art, the beneficial effect of step 5 is that its multi-index comprehensive analysis method can effectively reduce the deviation and misjudgment risk that may be caused by a single index. By comprehensively considering multiple indexes, the reliability and accuracy of the evaluation results are ensured, making the judgment of sweet potato quality more scientific and objective. In this scheme, the use of this step can promote the overall scheme, as it provides quantitative basis for the evaluation of sweet potato appearance quality, making the evaluation results more practical. In practical application, farmers and agricultural managers can adjust planting management measures in a timely manner based on the quality evaluation index, thereby optimizing the production process of sweet potatoes, improving yield and quality, and ultimately achieving higher economic benefits.

[0156] Step 6: Obtain the average tuber weight, tuber neatness, and tuber length-width ratio in the community, correct the quality evaluation index based on the average tuber weight, tuber neatness, and tuber length-width ratio, obtain the comprehensive quality index, compare the comprehensive quality index with the preset threshold, and according to the comparison result, divide the quality of sweet potatoes in the community into three levels, namely: low quality, medium quality, and high quality.

[0157] In this embodiment, the specific logic for obtaining the average tuber weight, tuber neatness, and tuber length-width ratio in the community is as follows: a certain number of sweet potato plants are randomly dug in each community, all tubers are harvested, and soil and roots are removed. Each tuber is weighed using an electronic scale to 0.1 g, and damaged or diseased tubers are excluded. The average mass is taken as the average tuber weight of the community. The average tuber weight refers to the average weight of a single tuber, i.e. the total weight of all tubers harvested from the randomly dug sweet potato plants in each community divided by the total number of tubers, denoted as ; the tuber length-width ratio refers to the ratio of the length of the tuber to the diameter of the largest part of the tuber, denoted as . ;

[0158] Calculate the uniformity of potato chunks using the following formula:

[0159] ;

[0160] In the formula, The uniformity of potato tuber size is used to reflect the uniformity of tuber size within the same community. A value closer to 1 indicates more uniform tuber weight, and vice versa. A lower uniformity value indicates greater variation in the weight of the sweet potatoes and poorer uniformity. A higher uniformity value indicates that the sweet potatoes from that community are of better quality and can gain greater recognition in the market. The standard deviation of potato tuber weight in this community;

[0161] The quality evaluation indicators are adjusted based on average tuber weight, tuber uniformity, and tuber length-to-width ratio, using the following formula:

[0162] ;

[0163] In the formula, For the comprehensive quality index, This represents the average weight of the potato chunks. This is a reference weight for the potato chunks. To ensure the uniformity of the potato chunks, The aspect ratio of the potato tuber. This is a reference value for the aspect ratio. , and To preset weights, , , This is because in many markets, the weight of sweet potatoes is a significant factor influencing their selling price. Consumers and markets tend to buy sweet potatoes of moderate weight, as they generally represent higher yield and economic value. Therefore, average tuber weight has a greater impact on quality assessment and is given a higher weight.

[0164] is an evaluation of the overall quality of sweet potatoes, and also takes into account the average tuber weight, tuber uniformity, and tuber length-width ratio, which are three key factors. It reflects the overall quality level of sweet potatoes, combining the effects of yield, size, and uniformity, providing a more comprehensive evaluation of sweet potato quality, which better reflects market value and consumer acceptance. The relationship between the comprehensive quality index and tuber weight and uniformity reflects the optimal commercial characteristics. Specifically, when the tuber uniformity improves, the comprehensive quality index will increase accordingly, because high uniformity is beneficial to mechanized harvesting and processing, significantly reducing production costs; and when the tuber weight is within the optimal commercial size range of 150-400g (i.e. 3-8 two), the comprehensive quality index reaches a peak, which reflects the market's premium recognition of this size of sweet potatoes. It is worth noting that small or large tubers, although they may perform well in some intrinsic quality indicators, have relatively low economic value because they do not meet the needs of the mainstream market, so they are appropriately corrected in the calculation of the comprehensive quality index. This design ensures a high degree of consistency between the quality evaluation results and market value, taking into account the processing suitability and appearance of the tubers, as well as the intrinsic quality and market demand characteristics.

[0165] The comprehensive quality index is compared with a preset threshold, and the specific logic is as follows:

[0166] When , it is determined that the quality of sweet potatoes in the community is low, and such sweet potatoes usually have small or large tubers, poor uniformity, and low dry matter content;

[0167] When , it is determined that the quality of sweet potatoes in the community is medium, and such sweet potatoes have tuber weights concentrated in the optimal commercial size range and good uniformity, meeting market demand;

[0168] When , it is determined that the quality of sweet potatoes in the community is high, and such sweet potatoes not only meet all the requirements of medium quality, but also have more excellent intrinsic quality indicators such as dry matter content and nutrient element content;

[0169] wherein is the comprehensive quality index, is the preset evaluation threshold.

[0170] The advantage of step 6 is that it further improves the accuracy and reliability of the evaluation of the appearance quality of sweet potatoes by obtaining the average tuber weight and uniformity of sweet potatoes in the community. By actually measuring the physical characteristics of the tubers and combining the correction of the quality evaluation indicators, the quality of the sweet potatoes can be more comprehensively reflected, providing a more intuitive evaluation. This method increases the multidimensional consideration of the quality of sweet potatoes, ensuring that the evaluation results are true and reliable.

[0171] Compared with the prior art, the beneficial effect of step 6 is that it not only relies on biochemical indicators, but also introduces physical characteristics as evaluation criteria, which is relatively rare in traditional methods. By integrating biochemical data and physical indicators, errors caused by a single indicator can be effectively reduced, ensuring the comprehensiveness and accuracy of quality evaluation, thereby improving the scientificity of sweet potato appearance quality evaluation. In this scheme, the use of this step can play an important role in promoting the overall scheme, because it enables sweet potato appearance quality evaluation not only to be limited to laboratory analysis, but also to include on-site actual measurement, enhancing the practicality and guidance of the evaluation results. This process not only helps farmers better understand and grasp the growth status of sweet potatoes, but also provides practical basis for subsequent management decisions, thereby improving the overall production efficiency and market competitiveness of sweet potatoes.

[0172] Please refer to Figure 2 A sweet potato appearance quality evaluation system based on growth environment, comprising:

[0173] A network construction module for selecting multiple monitoring areas in a sweet potato planting area, numbering each monitoring area as a node, constructing an undirected graph, adding edges in the undirected graph according to the spatial information between nodes, and forming an undirected graph network;

[0174] A community dynamic division module for placing each node in an independent community. For each node in the network in the undirected graph, it is moved to the community where all its neighbor nodes are located, and the corresponding module increment value of each movement is calculated. The node is moved to the neighbor community that maximizes the module increment value. Repeat the movement of the node until the community attribution of all nodes no longer changes;

[0175] A multi-source data acquisition module for constructing a community node set according to the node conditions inside each community, obtaining the spectral image of the sweet potato sample at the location of each internal node, extracting the reflectivity data of the key waveband from the spectral image, acquiring the pH value and soil moisture of the planting soil at the location of the node, and simultaneously obtaining the dry matter ratio and environmental temperature of the sweet potato sample at the location of the node;

[0176] An index calculation module for calculating the nitrogen content, phosphorus content, potassium content, soil microbial biomass, soluble sugar content and starch content in sweet potatoes according to the reflectivity data, determining the growth health index according to the dry matter ratio, nitrogen content, phosphorus content, potassium content, soluble sugar content and starch content of the sweet potato sample, determining the microbial activity index according to the soil microbial biomass, soil moisture and environmental temperature, and determining the environmental adaptability index according to the soil pH value, soil moisture and environmental temperature;

[0177] The quality preliminary evaluation aggregation module is configured to determine a quality evaluation index reflecting the quality of sweet potato at each node according to the growth health index, the microbial activity index and the environmental adaptability index, and take the average of the quality evaluation indexes of all nodes in the community as the quality evaluation index of the community;

[0178] The correction grading module is configured to obtain the average weight of tubers, the tuber neatness and the length-width ratio of tubers in the community, correct the quality evaluation index based on the average weight of tubers, the tuber neatness and the length-width ratio of tubers, obtain a comprehensive quality index, compare the comprehensive quality index with a preset threshold, and divide the quality of sweet potato in the community into three grades, i.e., low quality, medium quality and high quality, according to the comparison result.

[0179] The above formulas are all dimensionless values calculated, the formulas are obtained by collecting a large amount of data to simulate a formula closest to the actual situation, and the preset parameters in the formulas are set by a person skilled in the art according to the actual situation.

[0180] The above embodiments can be realized wholly or partially by software, hardware, firmware or any combination thereof. When realized by software, the above embodiments can be realized wholly or partially in the form of a computer program product. Those skilled in the art can realize that the units and algorithm steps of the examples described in connection with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized by hardware or software methods depends on the specific application and design constraints of the technical solutions.

[0181] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, which can be located in one place or distributed on multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiments.

[0182] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered within the protection scope of the present application.

Claims

1. A method for evaluating the appearance quality of sweet potatoes based on their growing environment, characterized in that, The specific steps include: Step 1: Divide the sweet potato planting area into multiple monitoring areas of equal size, treat each monitoring area as a node, number each node, and construct an undirected graph. Based on the spatial information between each node, add edges to the undirected graph to form an undirected graph network. Step 2: Place each node in an independent community. For each node in the network of the undirected graph, move it to the community of all its neighboring nodes one by one. Calculate the corresponding modular increment for each move and move the node to the neighboring community that maximizes the modular increment. Repeat the node movement until the community affiliation of all nodes no longer changes. Step 3: Based on the node situation within each community, construct a community node set, obtain the spectral image of sweet potato samples at the location of each community node, extract the reflectance data of key bands from the spectral image, collect the pH value and soil moisture of the planting soil at the node location, and at the same time obtain the dry matter ratio and ambient temperature of the sweet potato samples at the node location. Step 4: Calculate the nitrogen, phosphorus, and potassium content of the planting soil, soil microbial biomass, and soluble sugar and starch content in sweet potatoes based on the reflected wave data. Determine the growth health index based on the dry matter ratio, nitrogen, phosphorus, potassium, soluble sugar, and starch content of the sweet potato samples. Determine the microbial activity index based on soil microbial biomass, soil moisture, and ambient temperature. Determine the environmental adaptability index based on soil pH, soil moisture, and ambient temperature. Step 5: Determine the quality assessment index to reflect the quality of sweet potatoes at each node based on the growth health index, microbial activity index, and environmental adaptability index, and use the average quality assessment index of all nodes in the community as the quality evaluation index of the community. Step 6: Obtain the average weight, uniformity, and aspect ratio of sweet potatoes in the community. Based on the average weight, uniformity, and aspect ratio, correct the quality evaluation indicators to obtain the comprehensive quality index. Compare the comprehensive quality index with the preset threshold. Based on the comparison results, classify the quality of sweet potatoes in the community into three levels: low quality, medium quality, and high quality. The formula for calculating the modular added value is as follows: In the formula, To add value through modularization, The sum of the weights of the edges within the target community. The sum of the weights of all edges in the target community. For nodes The right to the side and, For the node index, For the sum of edge weights across the entire network; Represents a node The sum of the weights of the edges connecting to nodes within the target community; Following the modular value-added calculation method described above, each node is moved to the neighboring community that maximizes the modular value-added. This process of moving nodes is repeated until the community affiliation of all nodes no longer changes.

2. The method for evaluating the appearance quality of sweet potatoes based on the growth environment according to claim 1, characterized in that: The key bands refer to the bands in the spectral image that can reflect nitrogen content, phosphorus content, potassium content, and soil microbial biomass. The specific logic for obtaining the dry matter ratio is as follows: The sweet potato sample is washed to remove soil and impurities. The washed sweet potatoes are then placed in an oven at 70℃ for drying until the weight of the sweet potatoes no longer changes. The dried sweet potatoes are weighed using an electronic balance, and their dry matter weight is recorded. The dry matter ratio is then calculated. in, The dry matter ratio is... This is the dry matter weight. This refers to the wet weight of the sweet potato before drying. The nitrogen content is calculated based on the reflected wave data using the following formula: in, Nitrogen content, The reflectivity is in the 970nm band. For reference wavelengths, here we are referring to the reflectivity at 550nm. This is a constant used to reflect the effect of nitrogen content on the reflectance ratio of a specific plant species; The phosphorus content is calculated based on the reflected wave data using the following formula: in, Phosphorus content, The reflectivity is in the 520nm band. This is a constant used to reflect the effect of phosphorus content on the reflectance ratio of a specific plant species; The potassium content is calculated based on the reflected wave data using the following formula: in, Potassium content, The reflectivity is in the 850nm band. This is a constant used to reflect the effect of potassium content on the reflectance ratio of a specific plant species; The formula used to calculate the soluble sugar content based on reflected wave data is as follows: in, This refers to the soluble sugar content. The reflectivity is in the 1200nm band. This is a constant used to reflect the effect of the soluble sugar content of a specific plant species on the reflectance ratio; The starch content is calculated based on the reflected wave data using the following formula: in, This refers to the soluble sugar content. The reflectivity is in the 2100nm band. This is a constant used to reflect the effect of starch content on the reflectance ratio of a specific plant species; The formula used to calculate microbial biomass based on reflected wave data is as follows: in, For microbial biomass, The reflectivity is at the 1450nm wavelength. This is a constant used to reflect the influence of microbial biomass on the reflectance ratio in a specific soil type; The ambient temperature of the planting area was collected using a temperature sensor. This ambient temperature was measured at a height of 0.2-0.5 meters above the ground and denoted as [missing information]. ; Using a pH sensor and a humidity sensor, the pH value and soil moisture of the planting soil were obtained and recorded as follows: and .

3. The method for evaluating the appearance quality of sweet potatoes based on the growth environment according to claim 2, characterized in that: Set an optimal pH value and a suitable threshold range, ensuring the optimal pH value falls within the suitable threshold range. If the soil pH value exceeds the threshold range, calculate the absolute difference between the soil pH value and the optimal pH value, denoted as . If the content is within the threshold range, it will not be included in the subsequent calculation of the environmental adaptability index. Similarly, if the soluble sugar content or starch content in sweet potatoes exceeds the threshold range, the absolute differences between the soluble sugar content and starch content and the corresponding optimal values ​​will be calculated and recorded as follows: and If the value does not exceed the threshold range, it will not be included in the subsequent calculation of the growth health index; The formula used to calculate the growth health index is as follows: in, For growth and health index, The dry matter ratio is... This is the ideal value for the dry matter ratio. and These are the reference values ​​for soluble sugar content and starch content, respectively. Nitrogen content, This represents the ideal value for nitrogen content. Phosphorus content, This represents the ideal value for phosphorus content. Potassium content, This is the ideal value for potassium content. , and This is a preset proportional coefficient. And satisfy ; The formula used to calculate the microbial activity index is as follows: in, This is the microbial activity index. For microbial biomass, This represents the ideal microbial biomass. For soil moisture, Ideal soil moisture For ambient temperature, The ideal ambient temperature, It is a proportionality coefficient, and ; The formula used to calculate the environmental adaptability index is as follows: in, It is an environmental adaptability index. For soil moisture, Ideal soil moisture For ambient temperature, The ideal ambient temperature, , This is a preset proportional coefficient. And satisfy .

4. The method for evaluating the appearance quality of sweet potatoes based on the growth environment according to claim 1, characterized in that: The quality assessment index used to reflect the quality of sweet potatoes at each node is determined based on the growth health index, microbial activity index, and environmental adaptability index. The formula used is as follows: in, As a quality assessment index, For growth and health index, This is the microbial activity index. It is an environmental adaptability index. , , The weights are determined according to the analytic hierarchy process. The average quality assessment index of all nodes within the community is used as the quality evaluation index of the community, denoted as . .

5. The method for evaluating the appearance quality of sweet potatoes based on the growth environment according to claim 4, characterized in that: The specific logic behind determining weights using the Analytic Hierarchy Process (AHP) is as follows: The three indicators—growth health index, microbial activity index, and environmental adaptability index—were labeled, and the relative importance of each pair of indicators was determined using the nine-scale method. A judgment matrix was constructed, where the index of the growth health index was labeled as 1, the index of the microbial activity index as 2, and the index of the environmental adaptability index as 3. The constructed judgment matrix is ​​as follows: in, , Both represent the index of the index, and , , Indicates that the index is The exponent relative to the index is The importance index is used, with importance calculated using a 1-9 scale. The larger the value, the higher the index. The index is compared to the index. The greater the importance of the index, and , ; Indicates that the index is The importance of the index relative to itself, Indicates that the index is The exponent relative to the index is The importance of the index; Divide each element value in the judgment matrix by the sum of its columns to obtain a normalized judgment matrix. Calculate the mean of the element values ​​in each row of the normalized judgment matrix. Use the mean of the first row as the weight of the growth health index, the mean of the second row as the weight of the microbial activity index, and the mean of the third row as the weight of the environmental adaptability index. With the constraint that the sum of the scaled values ​​equals 1, scale the three weights proportionally and use the scaled weights as the scaling coefficients for the corresponding indices.

6. The method for evaluating the appearance quality of sweet potatoes based on the growth environment according to claim 1, characterized in that: The specific logic for obtaining the average tuber weight, uniformity, and aspect ratio within a community is as follows: A certain number of sweet potato plants are randomly selected from each community. All tubers are harvested, soil and fibrous roots are removed, and each tuber is weighed individually using an electronic scale, accurate to 0.1g. Damaged or diseased tubers are excluded. The average weight is taken as the average tuber weight for that community. The average tuber weight refers to the average weight of a single tuber, which is calculated by dividing the total weight of all tubers harvested from randomly selected sweet potato plants in each community by the total number of tubers. This is denoted as _____. The aspect ratio of the potato tuber refers to the ratio of the tuber's length to the diameter of its largest enlarged portion, denoted as ; ; Calculate the uniformity of potato chunks using the following formula: In the formula, The uniformity of potato tubers is used to reflect the evenness of tuber size within the same community. The standard deviation of potato tuber weight in this community; The quality evaluation indicators are adjusted based on average tuber weight, tuber uniformity, and tuber length-to-width ratio, using the following formula: In the formula, For the comprehensive quality index, This represents the average weight of the potato chunks. This is a reference weight for the potato chunks. To ensure the uniformity of the potato chunks, The aspect ratio of the potato tuber. This is a reference value for the aspect ratio. , and To preset weights, And satisfy .

7. The method for evaluating the appearance quality of sweet potatoes based on the growth environment according to claim 6, characterized in that: Comprehensive quality index The comparison with the preset threshold is based on the following logic: when At that time, the sweet potatoes in the community were judged to be of low quality, characterized by tubers that were too small or too large, poor uniformity, and low dry matter content. when At that time, the quality of sweet potatoes in the community was determined to be of medium quality grade. The weight of sweet potato tubers of this grade is concentrated within the range of optimal commercial specifications, and the uniformity is good, which meets market demand. when At that time, the sweet potatoes in the community were judged to be of high quality. This grade of sweet potatoes not only meets all the requirements of medium quality, but also performs better in terms of internal quality indicators such as dry matter content and nutrient content. in, For the comprehensive quality index, This is the preset evaluation threshold.

8. A sweet potato appearance quality evaluation system based on the growth environment, characterized in that: The sweet potato appearance quality evaluation system based on the growth environment is used to execute the sweet potato appearance quality evaluation method based on the growth environment as described in any one of claims 1-7, comprising: The network construction module is used to select multiple monitoring areas in the sweet potato planting area, treat each monitoring area as a node, number each node, and construct an undirected graph. Based on the spatial information between each node, edges are added to the undirected graph to form an undirected graph network. The community dynamic partitioning module is used to place each node in an independent community. For each node in the network of the undirected graph, it is moved to the community of all its neighboring nodes one by one. The corresponding modular increment of each move is calculated, and the node is moved to the neighboring community that maximizes the modular increment. The node is moved repeatedly until the community affiliation of all nodes no longer changes. The multi-source data acquisition module is used to form a community node set based on the node situation within each community, acquire the spectral image of sweet potato samples at the location of each node within the community, extract the reflectance data of key bands from the spectral image, acquire the pH value and soil moisture of the planting soil at the node location, and acquire the dry matter ratio and ambient temperature of the sweet potato samples at the node location. The index calculation module is used to calculate the nitrogen, phosphorus, and potassium content of the planting soil, soil microbial biomass, and soluble sugar and starch content in sweet potatoes based on reflected wave data. It also determines the growth health index based on the dry matter ratio, nitrogen, phosphorus, potassium, soluble sugar, and starch content of sweet potato samples, the microbial activity index based on soil microbial biomass, soil moisture, and ambient temperature, and the environmental adaptability index based on soil pH, soil moisture, and ambient temperature. The initial quality assessment aggregation module is used to determine the quality assessment index reflecting the quality of sweet potatoes at each node based on the growth health index, microbial activity index, and environmental adaptability index, and to use the average quality assessment index of all nodes in the community as the quality evaluation index of the community. The graded correction module is used to obtain the average weight, uniformity, and aspect ratio of sweet potatoes in the community. Based on the average weight, uniformity, and aspect ratio, the quality evaluation indicators are corrected to obtain a comprehensive quality index. The comprehensive quality index is compared with a preset threshold. Based on the comparison results, the quality of sweet potatoes in the community is divided into three levels: low quality, medium quality, and high quality.

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