Efficient fresh corn harvesting and storing method based on ecological planting

Abstract

The invention relates to the technical field of agriculture, and discloses a fresh corn efficient harvesting and storage method based on ecological planting, which comprises the following steps: ecological planting management, harvesting opportunity determination, efficient harvesting operation and storage condition control. According to the ecological planting management, scientific fertilization and irrigation management are implemented, nutrient and water supply is dynamically adjusted according to the growth stage of the fresh corn, a balanced nutrition environment is provided for growth of the fresh corn, and therefore balanced development of quality indexes of the fresh corn is promoted; the harvesting opportunity is determined based on quality index monitoring and a harvesting prediction model, accurate judgment of the mature state of the fresh corn is achieved, it is guaranteed that harvesting is conducted at the optimal harvesting time, a foundation is laid for obtaining high-quality fresh corn, efficient harvesting operation reduces mechanical damage to the fresh corn by optimizing harvesting parameters and the harvesting environment, and the yield of the fresh corn is improved. And immediately transferring to a shading environment, and slowing down the physiological deterioration process after harvesting.

Description

Technical Field

[0001] This invention relates to the field of agricultural technology, specifically to a method for efficient harvesting and storage of fresh corn based on ecological planting. Background Technology

[0002] Sweet corn refers to young corn with a unique flavor and quality. Compared to regular corn, sweet corn kernels are plump, bright, and naturally glossy. During the milk stage, the kernels produce a lot of sugar, starch, crude fat, and various vitamins and amino acids. In recent years, sweet corn has become increasingly popular among consumers due to its comprehensive advantages, including high nutritional value, good taste, high added value, good economic benefits, low fat and high fiber content, and fashionable characteristics, making it one of the staple foods on people's tables.

[0003] Currently, in the process of harvesting and storing fresh corn based on ecological planting, it is impossible to integrate dynamic data of field microenvironment and physiological indicators of the crop in real time to determine the optimal harvest point. It mainly relies on preset static quality thresholds, which leads to delayed harvesting decisions or mismatch with the actual maturity status of local plots, affecting the initial quality and flavor substance accumulation of fresh corn.

[0004] Therefore, a method for efficient harvesting and storage of fresh corn based on ecological planting is proposed to solve the above problems. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an efficient harvesting and storage method for fresh corn based on ecological planting, which solves the problems mentioned in the background technology, such as delayed harvesting decisions or mismatch with the actual maturity state of local plots, affecting the initial quality and flavor compound accumulation of fresh corn.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for efficient harvesting and storage of fresh corn based on ecological planting, comprising the following steps:

[0007] Step 1: Ecological planting management, using green planting technology to grow sweet corn, reducing the use of chemical pesticides and fertilizers;

[0008] Step 2: Determining the harvesting time. Based on the monitoring of quality indicators of fresh corn, including sugar content, hardness, moisture content, taste indicators and nutritional indicators, the optimal harvesting time is determined. The quality indicators are measured in real time using portable testing equipment.

[0009] Step 3: Efficient harvesting operation. Mechanized harvesting equipment is used for harvesting. Harvesting parameters are adjusted to minimize mechanical damage. Fresh corn is immediately moved to a shaded environment after harvesting.

[0010] Step 4: Post-harvest processing. Clean and grade the harvested fresh corn, and use natural preservatives for preservation.

[0011] Step 5: Storage condition control. Place the processed fresh corn in a controlled storage environment, controlling the temperature, humidity, gas composition and light conditions, and conduct regular quality monitoring and adjustments.

[0012] Preferably, the ecological planting management in step one includes the following sub-steps:

[0013] For soil preparation, select sandy loam or loam with a pH value of 6.0-7.5, plow to a depth of 25-30cm, and apply organic fertilizer and bio-fertilizer to improve the soil. The amount of organic fertilizer applied is 2000-3000 kg / mu, and the amount of bio-fertilizer applied is 50-100 kg / mu.

[0014] The planting method adopts reasonable dense planting, with a row spacing of 60-70cm and a plant spacing of 25-30cm, resulting in a planting density of 3000-4000 plants per acre;

[0015] During the growing season, scientific fertilization and irrigation management are implemented according to the growth stages of sweet corn. Fertilization is mainly based on organic fertilizer, supplemented by chemical fertilizer. Irrigation adopts drip irrigation or sprinkler irrigation system, and the irrigation amount is controlled based on soil moisture sensor to maintain soil moisture at 60%-80% field capacity.

[0016] Preferably, the scientific fertilization operation in the growth period management specifically includes:

[0017] Base fertilizer application: Apply well-rotted organic fertilizer before planting. The organic fertilizer is made from livestock and poultry manure and crop straw compost, with the nitrogen, phosphorus and potassium ratio controlled at 1.0-1.5:0.3-0.7:0.5-1.2, and the application rate is 1500-2000 kg / mu.

[0018] For topdressing management, organic liquid fertilizer is applied during the jointing and tasseling stages of fresh corn. The organic liquid fertilizer is made by mixing soybean meal fermentation liquid and fish protein fertilizer at a mass ratio of 0.8-1.2:0.8-1.2. The amount applied each time is 100-150 kg / mu. After the topdressing is completed, weeding and cultivation are carried out between the crop rows. Use a cultivator or hoe to loosen the topsoil to a depth of 3-5 cm, and cut and remove the roots of weeds at the same time.

[0019] Foliar fertilizer supplementation: During the grain-filling period, spray micronutrient foliar fertilizer containing zinc, boron, and magnesium at a concentration of 0.1%-0.3% each. The application rate is 50-100 L / mu, and the spraying frequency is once every 7-10 days, for a total of 2-3 times.

[0020] Preferably, the irrigation management operations during the growth period specifically include:

[0021] The irrigation system is set up with an intelligent drip irrigation system. The spacing of the drip tape is matched with the row spacing, the dripper flow rate is 2-4L / h, and the irrigation water is purified rainwater or groundwater.

[0022] The irrigation plan is based on real-time meteorological data and soil moisture monitoring to formulate a dynamic irrigation scheme. During the seedling stage, the soil moisture is maintained at 50%-60%, from the jointing stage to the tasseling stage it is increased to 70%-80%, and during the grain filling stage it is maintained at 65%-75%. The irrigation depth is 20-30cm each time.

[0023] Moisture monitoring involves acquiring soil moisture data at a depth of 10-20cm, with data collection occurring once per hour, and irrigation parameters are adjusted in real time based on the monitoring data.

[0024] Preferably, the determination of harvesting timing in step two includes the following sub-steps:

[0025] Quality indicators are monitored starting from the milk stage of fresh corn. 10-20 ears of corn are sampled and tested daily. The test indicators include sugar content, starch content, moisture content, protein content and sensory score. The sugar content should be 14%-18% and the moisture content should be 70%-75%. The sensory score is based on appearance, color and smell and is conducted by professionals. The full score is 10 points and the score should be 8 points or above.

[0026] The monitoring equipment includes a digital refractometer to measure sugar content, a near-infrared spectrometer to measure starch and protein content, and a moisture meter to measure moisture content. All data are entered into a database for trend analysis.

[0027] The decision-making model, based on historical data and machine learning algorithms, establishes a harvest prediction model. When the quality indicators are stable within the optimal range for three consecutive days, a harvesting instruction is triggered, ensuring that the harvesting time error does not exceed 24 hours.

[0028] Preferably, the efficient harvesting operation in step three includes the following sub-steps:

[0029] The harvesting equipment is a self-propelled fresh corn combine harvester, with the harvester's travel speed adjusted to 3-5 km / h and the ear-picking roller speed set at 300-500 r / min;

[0030] Harvesting should be done in the early morning or evening to avoid high-temperature periods. The ambient temperature should be controlled at 15-25°C and the humidity at 60%-80%. After harvesting, the ears of fruit should be placed in breathable containers and covered with shade nets.

[0031] On-site processing involves preliminary sorting during harvesting to remove diseased, pest-infested, and mechanically damaged fruit bunches. Qualified fruit bunches are transported to the processing point within 30 minutes. The transport vehicles are equipped with a temperature control system to maintain a temperature of 10-15°C.

[0032] Preferably, the post-harvest processing in step four includes the following sub-steps:

[0033] For cleaning, fresh corn ears are fed into a drum-type washing machine and cleaned with ozone water at an ozone concentration of 0.5-1.0 mg / L for 5-10 minutes. After cleaning, the ears are rinsed with clean water to remove any residue.

[0034] The grading standard uses an automatic photoelectric sorting machine to grade the fruit according to weight, length and appearance indicators. Grade 1 ear of fruit weighs 250-300g, is 18-22cm long and has no defects. Grade 2 ear of fruit weighs 200-250g, is 15-18cm long and allows for minor defects.

[0035] For preservation, the graded fresh corn is sprayed with a natural preservative. The spraying equipment is a high-pressure atomizing nozzle with a spraying pressure of 0.2-0.5 MPa. The amount of preservative used is 10-20 L per ton of fresh corn. After spraying, let it stand for 10-15 minutes to allow the preservative to form a film.

[0036] Preferably, the natural preservative is made from the following raw materials in parts by weight: 10-20 parts chitosan, 5-10 parts citric acid, 3-8 parts plant extract, 2-5 parts antioxidant and 50-70 parts water, wherein the plant extract is at least one of green tea extract or rosemary extract, and the antioxidant is at least one of vitamin C or vitamin E.

[0037] Methods for preparing natural preservatives include:

[0038] Raw material preparation: food-grade chitosan with a degree of deacetylation ≥85% is selected; citric acid is food-grade; plant extracts are prepared by supercritical CO2 extraction; and antioxidants are vitamin C or vitamin E in powder form.

[0039] The preparation process involves slowly adding chitosan to water while stirring at 200-400 rpm and maintaining a temperature of 40-50°C. After dissolving, citric acid is added to adjust the pH to 3.5-4.5. Then, plant extracts and antioxidants are added, and stirring continues for 30-60 minutes until the mixture is homogeneous. Finally, the mixture is filtered to remove impurities, yielding a transparent, viscous liquid.

[0040] Preferably, the storage condition control in step five includes the following sub-steps:

[0041] The storage environment is set up using an intelligent cold storage, with the temperature controlled at 0-4°C, the humidity maintained at 85%-90%, the gas composition adjusted to 2%-5% oxygen and 3%-6% carbon dioxide, and the light intensity below 50 lux to avoid photo-oxidation.

[0042] For storage management, fresh corn should be packaged in breathable plastic bags, each weighing 5-10 kg. Ventilation channels should be left when stacking, and the stacking height should not exceed 2 meters. The air circulation speed in the storage should be 0.5-1.0 m / s.

[0043] The monitoring system acquires real-time data on temperature, humidity, gas composition, and images inside the warehouse and transmits it to the central control system. The system automatically records and analyzes the data every two hours and automatically adjusts the refrigeration or controlled atmosphere equipment when the parameters deviate from the set range.

[0044] Preferably, the quality monitoring and adjustment in step five includes:

[0045] Regular sampling is conducted, with 10-20 bunches of fruit randomly selected from the storage warehouse every 7 days to test sugar content, moisture content, firmness, mold rate, and sensory quality.

[0046] The strategy is adjusted as follows: when the sugar content drops by more than 5%-15% or the mold rate exceeds 1%-5%, the storage temperature is adjusted to the lower limit or the frequency of preservative spraying is increased; when the moisture content is lower than 60%-70%, the humidity is increased to the upper limit. All adjustments are based on the prediction model.

[0047] Data integration involves comparing all test data with pre-harvest data to generate quality trend reports, which are used to optimize subsequent harvesting and storage parameters and shared with farmers and processing enterprises through a cloud platform.

[0048] Compared with existing technologies, this invention provides a highly efficient harvesting and storage method for fresh corn based on ecological planting, which has the following beneficial effects:

[0049] 1. In this invention, ecological planting management implements scientific fertilization and irrigation management, dynamically adjusting nutrient and water supply according to the growth stage of fresh corn to provide a balanced nutritional environment for the growth of fresh corn, thereby promoting the balanced development of the quality indicators of fresh corn; the timing of harvesting is determined based on the quality indicator monitoring and harvest prediction model to accurately judge the maturity status of fresh corn, ensuring that harvesting is carried out at the optimal time, laying the foundation for obtaining high-quality fresh corn.

[0050] 2. In this invention, the efficient harvesting operation reduces mechanical damage to fresh corn by optimizing harvesting parameters and the harvesting environment, and immediately transfers it to a shaded environment to slow down the post-harvest physiological deterioration process; the post-harvest treatment removes surface contaminants and performs quality grading through cleaning, grading and treatment with natural preservatives, while using natural preservatives to form a film on the surface of fresh corn to inhibit microbial growth and moisture loss, thus synergistically maintaining the freshness and marketability of fresh corn.

[0051] 3. In this invention, the storage conditions are controlled by placing fresh corn in a controlled storage environment and regulating the temperature, humidity, gas composition and light conditions to inhibit the respiration and nutrient loss of fresh corn; combined with regular quality monitoring and adjustment strategies based on prediction models, the storage parameters are dynamically optimized to achieve dynamic regulation of the storage quality of fresh corn, extend the shelf life and reduce storage losses. Detailed Implementation

[0052] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0053] Example 1: A method for efficient harvesting and storage of fresh corn based on ecological planting, comprising the following steps:

[0054] Step 1: Ecological planting management, using green planting technology to grow sweet corn, reducing the use of chemical pesticides and fertilizers;

[0055] Step 2: Determine the harvesting time. Based on the monitoring of quality indicators of fresh corn, including sugar content, hardness, moisture content, taste indicators and nutritional indicators, determine the optimal harvesting time. The quality indicators are measured in real time using portable testing equipment.

[0056] Step 3: Efficient harvesting operation. Mechanized harvesting equipment is used for harvesting. Harvesting parameters are adjusted to minimize mechanical damage. Fresh corn is immediately moved to a shaded environment after harvesting.

[0057] Step 4: Post-harvest processing. Clean and grade the harvested fresh corn, and use natural preservatives for preservation.

[0058] Step 5: Storage condition control. Place the processed fresh corn in a controlled storage environment, controlling the temperature, humidity, gas composition and light conditions, and conduct regular quality monitoring and adjustments.

[0059] Step one of ecological planting management includes the following sub-steps:

[0060] For soil preparation, select sandy loam or loam with a pH of 6.0, plow to a depth of 25cm, and apply organic fertilizer and bio-fertilizer to improve the soil. The application rate of organic fertilizer is 2000kg / mu, and the application rate of bio-fertilizer is 50kg / mu.

[0061] The planting method adopts reasonable dense planting, with a row spacing of 60cm and a plant spacing of 25cm, resulting in a planting density of 3000 plants per acre;

[0062] During the growing season, scientific fertilization and irrigation management are implemented according to the growth stages of sweet corn. Fertilization is mainly based on organic fertilizer, supplemented by chemical fertilizer. Irrigation adopts drip irrigation or sprinkler irrigation system, and the irrigation amount is controlled based on soil moisture sensor to maintain soil moisture at 60% field capacity.

[0063] During the growth period, scientific fertilization includes the following specific procedures:

[0064] Base fertilizer application: Apply well-rotted organic fertilizer before planting. The organic fertilizer is made from livestock and poultry manure and crop straw compost, with the nitrogen, phosphorus and potassium ratio controlled at 1.0:0.3:0.5, and the application rate is 1500 kg / mu.

[0065] For topdressing management, apply organic liquid fertilizer during the jointing and tasseling stages of fresh corn. The organic liquid fertilizer is made by mixing soybean meal fermentation liquid and fish protein fertilizer at a mass ratio of 0.8:0.9. The amount of each topdressing is 100 kg / mu. After the topdressing is completed, weeding and cultivation should be carried out between the crop rows. Use a cultivator or hoe to loosen the topsoil to a depth of 3 cm, and cut and remove the roots of weeds at the same time.

[0066] Foliar fertilizer supplementation: During the grain-filling period, spray micronutrient foliar fertilizer containing zinc, boron, and magnesium at a concentration of 0.1% each. The application rate is 50L / acre, and the spraying frequency is once every 7 days, for a total of 2 times.

[0067] During the growing season, irrigation management specifically includes the following operations:

[0068] The irrigation system is set up with an intelligent drip irrigation system. The spacing of the drip tape is matched with the row spacing, the dripper flow rate is 2L / h, and the irrigation water is purified rainwater or groundwater.

[0069] The irrigation plan is based on real-time meteorological data and soil moisture monitoring to formulate a dynamic irrigation scheme. The soil moisture is maintained at 50% during the seedling stage, increased to 70% from the jointing stage to the tasseling stage, and maintained at 65% during the grain filling stage. The irrigation depth is 20cm each time.

[0070] Moisture monitoring acquires soil moisture data at a depth of 10cm, with data collection occurring once per hour, and irrigation parameters are adjusted in real time based on the monitoring data.

[0071] Step two, determining the harvesting timing, includes the following sub-steps:

[0072] Quality indicators are monitored starting from the milk stage of fresh corn. Ten ears of corn are sampled and tested daily. The test indicators include sugar content, starch content, moisture content, protein content and sensory score. The sugar content is required to reach 14% and the moisture content is 70%. The sensory score is based on appearance, color and smell and is conducted by professionals. The full score is 10 points and a score of 8 or above is required.

[0073] The monitoring equipment includes a digital refractometer to measure sugar content, a near-infrared spectrometer to measure starch and protein content, and a moisture meter to measure moisture content. All data are entered into a database for trend analysis.

[0074] The decision-making model, based on historical data and machine learning algorithms, establishes a harvest prediction model. When the quality indicators are stable within the optimal range for three consecutive days, a harvesting command is triggered, ensuring that the harvesting time error does not exceed 24 hours. Specifically, it includes the following operations:

[0075] Data collection: Collect data on the quality indicators of fresh corn during historical harvest seasons and the corresponding harvest time data;

[0076] Data preprocessing: Cleaning the collected historical data to remove outliers and noisy data;

[0077] Model Construction: A machine learning algorithm was selected, with quality index data as input and optimal harvest time as the output target, to construct a predictive model. Specifically, the constructed predictive model can be represented by the following mathematical relationship:

[0078] ;

[0079] in, To predict the optimal harvest time, The input feature vector consists of sugar content, starch content, moisture content, protein content, and sensory evaluation quality indicators. These are the model parameters to be determined through training;

[0080] Model training and optimization: Train the constructed prediction model using historical data and optimize the model parameters;

[0081] Model deployment: Deploy the trained and optimized prediction model to the monitoring system to receive and process the quality indicator data being monitored in real time;

[0082] Decision trigger: When the model processes real-time monitoring data and determines that the quality indicators of fresh corn are stable within the preset optimal range for three consecutive days, a harvesting command will be automatically triggered.

[0083] The efficient harvesting operation in step three includes the following sub-steps:

[0084] The harvesting equipment is a self-propelled fresh corn combine harvester, with the harvester's travel speed adjusted to 3km / h and the ear-picking roller speed set at 300r / min;

[0085] Harvesting should be done in the early morning or evening to avoid high-temperature periods. The ambient temperature should be controlled at 15°C and the humidity at 60%. After harvesting, the ears of fruit should be placed in breathable containers and covered with shade nets.

[0086] On-site processing involves preliminary sorting during harvesting to remove diseased, pest-infested, and mechanically damaged fruit bunches. Qualified fruit bunches are transported to the processing point within 30 minutes, with transport vehicles equipped with temperature control systems to maintain a temperature of 10°C.

[0087] Step four, post-harvest processing, includes the following sub-steps:

[0088] For cleaning, fresh corn ears are fed into a drum washing machine and cleaned with ozone water at an ozone concentration of 0.5 mg / L for 5 minutes. After cleaning, they are rinsed with clean water to remove residue.

[0089] The grading standard uses an automatic photoelectric sorting machine to grade the fruit according to weight, length and appearance indicators. Grade 1 ear of fruit weighs 250g, is 18cm long and has no defects. Grade 2 ear of fruit weighs 200g, is 15cm long and allows for minor defects.

[0090] For preservation, the graded fresh corn is sprayed with a natural preservative. The spraying equipment is a high-pressure atomizing nozzle with a spraying pressure of 0.2 MPa. The spraying amount is 10 L of preservative per ton of fresh corn. After spraying, the corn is left to stand for 10 minutes to allow the preservative to form a film.

[0091] The natural preservative is made from the following ingredients in parts by weight: 10 parts chitosan, 5 parts citric acid, 3 parts plant extract, 2 parts antioxidant, and 50 parts water, wherein the plant extract is at least one of green tea extract or rosemary extract, and the antioxidant is at least one of vitamin C or vitamin E.

[0092] Methods for preparing natural preservatives include:

[0093] Raw material preparation: food-grade chitosan with a deacetylation degree ≥85% was selected; citric acid was food-grade; plant extracts were prepared by supercritical CO2 extraction; and antioxidants were in powder form of vitamin C or vitamin E. The extraction process was carried out at a temperature of 31℃ and a pressure of 8MPa. After extraction, supercritical CO2 fluid rich in extract was introduced into a separation vessel. The pressure was controlled by a pressure reducing valve to uniformly reduce the pressure to below 5MPa within 5 minutes. At this point, the supercritical CO2 fluid lost its dissolving ability, and the extract precipitated and was collected in the separation vessel, thus achieving the separation of the extractant and the extract.

[0094] The preparation process involves slowly adding chitosan to water while stirring at 200 rpm and maintaining the temperature at 40°C. After dissolving, citric acid is added to adjust the pH to 3.5. Then, plant extracts and antioxidants are added, and stirring continues for 30 minutes until the mixture is homogeneous. Finally, the mixture is filtered to remove impurities, yielding a transparent, viscous liquid.

[0095] Step five, storage condition control, includes the following sub-steps:

[0096] The storage environment is set up using an intelligent cold storage, with the temperature controlled at 0°C, humidity maintained at 85%, gas composition adjusted to 2% oxygen and 3% carbon dioxide, and light intensity below 50 lux to avoid photo-oxidation.

[0097] For storage management, fresh corn is packaged in breathable plastic bags, each weighing 5kg. Ventilation channels are left when stacking, and the stacking height does not exceed 2 meters. The air circulation speed in the storage is 0.5m / s.

[0098] The monitoring system acquires real-time data on temperature, humidity, gas composition, and images inside the warehouse and transmits it to the central control system. The system automatically records and analyzes the data every two hours and automatically adjusts the refrigeration or controlled atmosphere equipment when the parameters deviate from the set range.

[0099] Step five, quality monitoring and adjustment, includes:

[0100] Regular sampling is conducted, with 10 bunches of fruit randomly selected from the storage warehouse every 7 days to test sugar content, moisture content, firmness, mold rate, and sensory quality.

[0101] The strategy is adjusted as follows: when the sugar content drops by more than 5% or the mold rate exceeds 1%, the storage temperature is adjusted to the lower limit or the frequency of preservative spraying is increased; when the moisture content is below 60%, the humidity is increased to the upper limit. All adjustments are based on the prediction model.

[0102] Data integration involves comparing all test data with pre-harvest data to generate quality trend reports, which are used to optimize subsequent harvesting and storage parameters and shared with farmers and processing enterprises through a cloud platform.

[0103] Example 2: A method for efficient harvesting and storage of fresh corn based on ecological planting, comprising the following steps:

[0104] Step 1: Ecological planting management, using green planting technology to grow sweet corn, reducing the use of chemical pesticides and fertilizers;

[0105] Step 2: Determine the harvesting time. Based on the monitoring of quality indicators of fresh corn, including sugar content, hardness, moisture content, taste indicators and nutritional indicators, determine the optimal harvesting time. The quality indicators are measured in real time using portable testing equipment.

[0106] Step 3: Efficient harvesting operation. Mechanized harvesting equipment is used for harvesting. Harvesting parameters are adjusted to minimize mechanical damage. Fresh corn is immediately moved to a shaded environment after harvesting.

[0107] Step 4: Post-harvest processing. Clean and grade the harvested fresh corn, and use natural preservatives for preservation.

[0108] Step 5: Storage condition control. Place the processed fresh corn in a controlled storage environment, controlling the temperature, humidity, gas composition and light conditions, and conduct regular quality monitoring and adjustments.

[0109] Step one of ecological planting management includes the following sub-steps:

[0110] For soil preparation, select sandy loam or loam with a pH of 7, plow to a depth of 27cm, and apply organic fertilizer and bio-fertilizer to improve the soil. The application rate of organic fertilizer is 2500kg / mu, and the application rate of bio-fertilizer is 70kg / mu.

[0111] The planting method adopts reasonable dense planting, with a row spacing of 65cm and a plant spacing of 27cm, resulting in a planting density of 3500 plants per acre;

[0112] During the growing season, scientific fertilization and irrigation management are implemented according to the growth stages of sweet corn. Fertilization is mainly based on organic fertilizer, supplemented by chemical fertilizer. Irrigation adopts drip irrigation or sprinkler irrigation system, and the irrigation amount is controlled based on soil moisture sensor to maintain soil moisture at 70% field capacity.

[0113] During the growth period, scientific fertilization includes the following specific procedures:

[0114] Base fertilizer application: Apply well-rotted organic fertilizer before planting. The organic fertilizer is made from livestock and poultry manure and crop straw compost, with the nitrogen, phosphorus and potassium ratio controlled at 1.2:0.5:1, and the application rate is 1700 kg / mu.

[0115] For topdressing management, apply organic liquid fertilizer during the jointing and tasseling stages of fresh corn. The organic liquid fertilizer is made by mixing soybean meal fermentation liquid and fish protein fertilizer in a mass ratio of 1:1. The amount of each topdressing is 120 kg / mu. After the topdressing is completed, weeding and cultivation should be carried out between the crop rows. Use a cultivator or hoe to loosen the topsoil to a depth of 4 cm, and cut and remove the roots of weeds at the same time.

[0116] Foliar fertilizer supplementation: During the grain-filling period, spray micronutrient foliar fertilizer containing zinc, boron, and magnesium at a concentration of 0.2% each. The application rate is 70L / acre, and the spraying frequency is once every 9 days for a total of 3 times.

[0117] During the growing season, irrigation management specifically includes the following operations:

[0118] The irrigation system is set up with an intelligent drip irrigation system. The spacing of the drip tape is matched with the row spacing, the dripper flow rate is 3L / h, and the irrigation water is purified rainwater or groundwater.

[0119] The irrigation plan is based on real-time meteorological data and soil moisture monitoring to formulate a dynamic irrigation scheme. The soil moisture is maintained at 55% during the seedling stage, increased to 75% from the jointing stage to the tasseling stage, and maintained at 70% during the grain filling stage. The irrigation depth is 25cm each time.

[0120] Moisture monitoring acquires soil moisture data at a depth of 15cm, with data collection frequency once per hour, and irrigation parameters are adjusted in real time based on the monitoring data.

[0121] Step two, determining the harvesting timing, includes the following sub-steps:

[0122] Quality indicators are monitored starting from the milk stage of fresh corn. Fifteen ears of corn are sampled and tested daily. The test indicators include sugar content, starch content, moisture content, protein content and sensory score. The sugar content is required to reach 16% and the moisture content is required to be 73%. The sensory score is based on appearance, color and smell and is conducted by professionals. A score of 8 or above out of 10 is required.

[0123] The monitoring equipment includes a digital refractometer to measure sugar content, a near-infrared spectrometer to measure starch and protein content, and a moisture meter to measure moisture content. All data are entered into a database for trend analysis.

[0124] The decision-making model, based on historical data and machine learning algorithms, establishes a harvest prediction model. When the quality indicators are stable within the optimal range for three consecutive days, a harvesting command is triggered, ensuring that the harvesting time error does not exceed 24 hours. Specifically, it includes the following operations:

[0125] Data collection: Collect data on the quality indicators of fresh corn during historical harvest seasons and the corresponding harvest time data;

[0126] Data preprocessing: Cleaning the collected historical data to remove outliers and noisy data;

[0127] Model Construction: A machine learning algorithm was selected, with quality index data as input and optimal harvest time as the output target, to construct a predictive model. Specifically, the constructed predictive model can be represented by the following mathematical relationship:

[0128] ;

[0129] in, To predict the optimal harvest time, The input feature vector consists of sugar content, starch content, moisture content, protein content, and sensory evaluation quality indicators. These are the model parameters to be determined through training;

[0130] Model training and optimization: Train the constructed prediction model using historical data and optimize the model parameters;

[0131] Model deployment: Deploy the trained and optimized prediction model to the monitoring system to receive and process the quality indicator data being monitored in real time;

[0132] Decision trigger: When the model processes real-time monitoring data and determines that the quality indicators of fresh corn are stable within the preset optimal range for three consecutive days, a harvesting command will be automatically triggered.

[0133] The efficient harvesting operation in step three includes the following sub-steps:

[0134] The harvesting equipment is a self-propelled fresh corn combine harvester, with the harvester's travel speed adjusted to 4km / h and the ear-picking roller speed set at 400r / min;

[0135] Harvesting should be done in the early morning or evening to avoid high-temperature periods. The ambient temperature should be controlled at 20°C and the humidity at 70%. After harvesting, the ears of fruit should be placed in a breathable container and covered with a shade net.

[0136] On-site processing involves preliminary sorting during harvesting to remove diseased, pest-infested, and mechanically damaged fruit bunches. Qualified fruit bunches are transported to the processing point within 30 minutes, with transport vehicles equipped with temperature control systems to maintain a temperature of 12°C.

[0137] Step four, post-harvest processing, includes the following sub-steps:

[0138] For cleaning, fresh corn ears are fed into a drum washing machine and cleaned with ozone water at a concentration of 0.7 mg / L for 8 minutes. After cleaning, they are rinsed with clean water to remove residue.

[0139] The grading standard uses an automatic photoelectric sorting machine to grade the fruit according to weight, length and appearance indicators. Grade 1 ear of fruit weighs 270g, is 20cm long and has no defects. Grade 2 ear of fruit weighs 230g and is 17cm long and allows for minor defects.

[0140] For preservation, the graded fresh corn is sprayed with a natural preservative. The spraying equipment is a high-pressure atomizing nozzle with a spraying pressure of 0.4 MPa. The spraying amount is 15 L of preservative per ton of fresh corn. After spraying, the corn is left to stand for 12 minutes to allow the preservative to form a film.

[0141] The natural preservative is made from the following ingredients in parts by weight: 15 parts chitosan, 7 parts citric acid, 5 parts plant extract, 3 parts antioxidant, and 60 parts water, wherein the plant extract is at least one of green tea extract or rosemary extract, and the antioxidant is at least one of vitamin C or vitamin E.

[0142] Methods for preparing natural preservatives include:

[0143] Raw material preparation: food-grade chitosan with a deacetylation degree ≥85% was selected; citric acid was food-grade; plant extracts were prepared by supercritical CO2 extraction; and antioxidants were in powder form of vitamin C or vitamin E. The extraction process was carried out at a temperature of 45℃ and a pressure of 20MPa. After extraction, supercritical CO2 fluid rich in extract was introduced into a separation vessel. The pressure was controlled by a pressure-reducing valve to uniformly reduce the pressure to below 5MPa within 10 minutes. At this point, the supercritical CO2 fluid lost its dissolving ability, and the extract precipitated and was collected in the separation vessel, thus achieving the separation of the extractant and the extract.

[0144] The preparation process involves slowly adding chitosan to water while stirring at 300 rpm and maintaining a temperature of 45°C. After dissolving, citric acid is added to adjust the pH to 4. Then, plant extracts and antioxidants are added, and stirring continues for 45 minutes until the mixture is homogeneous. Finally, the mixture is filtered to remove impurities, yielding a transparent, viscous liquid.

[0145] Step five, storage condition control, includes the following sub-steps:

[0146] The storage environment is set up using an intelligent cold storage, with the temperature controlled at 2°C, humidity maintained at 87%, gas composition adjusted to 3% oxygen and 4% carbon dioxide, and light intensity below 50 lux to avoid photo-oxidation.

[0147] For storage management, fresh corn is packaged in breathable plastic bags, each weighing 7kg. Ventilation channels are left when stacking, and the stacking height does not exceed 2 meters. The air circulation speed inside the storage is 0.7m / s.

[0148] The monitoring system acquires real-time data on temperature, humidity, gas composition, and images inside the warehouse and transmits it to the central control system. The system automatically records and analyzes the data every two hours and automatically adjusts the refrigeration or controlled atmosphere equipment when the parameters deviate from the set range.

[0149] Step five, quality monitoring and adjustment, includes:

[0150] Regular sampling was conducted, with 15 bunches of fruit randomly selected from the storage warehouse every 7 days to test sugar content, moisture content, firmness, mold rate, and sensory quality.

[0151] The strategy is adjusted as follows: when the sugar content drops by more than 10% or the mold rate exceeds 3%, the storage temperature is adjusted to the lower limit or the frequency of preservative spraying is increased; when the moisture content is below 65%, the humidity is increased to the upper limit. All adjustments are based on the prediction model.

[0152] Data integration involves comparing all test data with pre-harvest data to generate quality trend reports, which are used to optimize subsequent harvesting and storage parameters and shared with farmers and processing enterprises through a cloud platform.

[0153] Example 3: A method for efficient harvesting and storage of fresh corn based on ecological planting, comprising the following steps:

[0154] Step 1: Ecological planting management, using green planting technology to grow sweet corn, reducing the use of chemical pesticides and fertilizers;

[0155] Step 2: Determine the harvesting time. Based on the monitoring of quality indicators of fresh corn, including sugar content, hardness, moisture content, taste indicators and nutritional indicators, determine the optimal harvesting time. The quality indicators are measured in real time using portable testing equipment.

[0156] Step 3: Efficient harvesting operation. Mechanized harvesting equipment is used for harvesting. Harvesting parameters are adjusted to minimize mechanical damage. Fresh corn is immediately moved to a shaded environment after harvesting.

[0157] Step 4: Post-harvest processing. Clean and grade the harvested fresh corn, and use natural preservatives for preservation.

[0158] Step 5: Storage condition control. Place the processed fresh corn in a controlled storage environment, controlling the temperature, humidity, gas composition and light conditions, and conduct regular quality monitoring and adjustments.

[0159] Step one of ecological planting management includes the following sub-steps:

[0160] For soil preparation, select sandy loam or loam with a pH of 7.5, plow to a depth of 30cm, and apply organic fertilizer and bio-fertilizer to improve the soil. The application rate of organic fertilizer is 3000kg / mu, and the application rate of bio-fertilizer is 100kg / mu.

[0161] The planting method adopts reasonable dense planting, with a row spacing of 70cm and a plant spacing of 30cm, resulting in a planting density of 4000 plants per acre;

[0162] During the growing season, scientific fertilization and irrigation management are implemented according to the growth stages of sweet corn. Fertilization is mainly based on organic fertilizer, supplemented by chemical fertilizer. Irrigation adopts drip irrigation or sprinkler irrigation system, and the irrigation amount is controlled based on soil moisture sensor to maintain soil moisture at 80% field capacity.

[0163] During the growth period, scientific fertilization includes the following specific procedures:

[0164] Base fertilizer application: Apply well-rotted organic fertilizer before planting. The organic fertilizer is made from livestock and poultry manure and crop straw compost, with the nitrogen, phosphorus and potassium ratio controlled at 1.5:0.7:1.2, and the application rate is 2000 kg / mu.

[0165] For topdressing management, apply organic liquid fertilizer during the jointing and tasseling stages of fresh corn. The organic liquid fertilizer is made by mixing soybean meal fermentation liquid and fish protein fertilizer at a mass ratio of 1.2:1.1. The amount of each topdressing is 150 kg / mu. After the topdressing is completed, weeding and cultivation should be carried out between the crop rows. Use a cultivator or hoe to loosen the topsoil to a depth of 5 cm, and cut and remove the roots of weeds at the same time.

[0166] Foliar fertilizer supplementation: During the grain-filling period, spray micronutrient foliar fertilizer containing zinc, boron, and magnesium at a concentration of 0.3% each. The application rate is 100L / acre, and the spraying frequency is once every 10 days for a total of 3 times.

[0167] During the growing season, irrigation management specifically includes the following operations:

[0168] The irrigation system is set up with an intelligent drip irrigation system. The spacing of the drip tape is matched with the row spacing, the dripper flow rate is 4L / h, and the irrigation water is purified rainwater or groundwater.

[0169] The irrigation plan is based on real-time meteorological data and soil moisture monitoring to formulate a dynamic irrigation scheme. The soil moisture is maintained at 60% during the seedling stage, increased to 80% from the jointing stage to the tasseling stage, and maintained at 75% during the grain filling stage. The irrigation depth is 30cm each time.

[0170] Moisture monitoring acquires soil moisture data at a depth of 20cm, with data collection occurring once per hour, and irrigation parameters are adjusted in real time based on the monitoring data.

[0171] Step two, determining the harvesting timing, includes the following sub-steps:

[0172] Quality indicators are monitored starting from the milk stage of fresh corn. Twenty ears of corn are sampled and tested daily. The test indicators include sugar content, starch content, moisture content, protein content, and sensory score. The sugar content is required to reach 18%, the moisture content is required to be 75%, and the sensory score is based on appearance, color and smell and is conducted by professionals. The full score is 10 points and a score of 8 or above is required.

[0173] The monitoring equipment includes a digital refractometer to measure sugar content, a near-infrared spectrometer to measure starch and protein content, and a moisture meter to measure moisture content. All data are entered into a database for trend analysis.

[0174] The decision-making model, based on historical data and machine learning algorithms, establishes a harvest prediction model. When the quality indicators are stable within the optimal range for three consecutive days, a harvesting command is triggered, ensuring that the harvesting time error does not exceed 24 hours. Specifically, it includes the following operations:

[0175] Data collection: Collect data on the quality indicators of fresh corn during historical harvest seasons and the corresponding harvest time data;

[0176] Data preprocessing: Cleaning the collected historical data to remove outliers and noisy data;

[0177] Model Construction: A machine learning algorithm was selected, with quality index data as input and optimal harvest time as the output target, to construct a predictive model. Specifically, the constructed predictive model can be represented by the following mathematical relationship:

[0178] ;

[0179] in, To predict the optimal harvest time, The input feature vector consists of sugar content, starch content, moisture content, protein content, and sensory evaluation quality indicators. These are the model parameters to be determined through training;

[0180] Model training and optimization: Train the constructed prediction model using historical data and optimize the model parameters;

[0181] Model deployment: Deploy the trained and optimized prediction model to the monitoring system to receive and process the quality indicator data being monitored in real time;

[0182] Decision trigger: When the model processes real-time monitoring data and determines that the quality indicators of fresh corn are stable within the preset optimal range for three consecutive days, a harvesting command will be automatically triggered.

[0183] The efficient harvesting operation in step three includes the following sub-steps:

[0184] The harvesting equipment is a self-propelled fresh corn combine harvester, with the harvester's travel speed adjusted to 5 km / h and the ear-picking roller speed set at 500 r / min;

[0185] Harvesting should be done in the early morning or evening to avoid high-temperature periods. The ambient temperature should be controlled at 25°C and the humidity at 80%. After harvesting, the ears of fruit should be placed in a breathable container and covered with a shade net.

[0186] On-site processing involves preliminary sorting during harvesting to remove diseased, pest-infested, and mechanically damaged fruit bunches. Qualified fruit bunches are transported to the processing point within 30 minutes, with transport vehicles equipped with temperature control systems to maintain a temperature of 15°C.

[0187] Step four, post-harvest processing, includes the following sub-steps:

[0188] For cleaning, fresh corn ears are fed into a drum-type washing machine and cleaned with ozone water at an ozone concentration of 1.0 mg / L for 10 minutes. After cleaning, they are rinsed with clean water to remove residue.

[0189] The grading standard uses an automatic photoelectric sorting machine to grade the fruit according to weight, length and appearance indicators. Grade 1 ear of fruit weighs 300g, is 22cm long and has no defects. Grade 2 ear of fruit weighs 250g and is 18cm long and allows for minor defects.

[0190] For preservation, the graded fresh corn is sprayed with a natural preservative. The spraying equipment is a high-pressure atomizing nozzle with a spraying pressure of 0.5 MPa. The amount of preservative used is 20 L per ton of fresh corn. After spraying, the corn is left to stand for 15 minutes to allow the preservative to form a film.

[0191] The natural preservative is made from the following ingredients in parts by weight: 20 parts chitosan, 10 parts citric acid, 8 parts plant extract, 5 parts antioxidant, and 70 parts water, wherein the plant extract is at least one of green tea extract or rosemary extract, and the antioxidant is at least one of vitamin C or vitamin E.

[0192] Methods for preparing natural preservatives include:

[0193] Raw material preparation: food-grade chitosan with a deacetylation degree ≥85% was selected; citric acid was food-grade; plant extracts were prepared by supercritical CO2 extraction; and antioxidants were in powder form of vitamin C or vitamin E. The extraction process was carried out at a temperature of 60℃ and a pressure of 35MPa. After extraction, supercritical CO2 fluid rich in extract was introduced into a separation vessel. The pressure was controlled by a pressure-reducing valve to uniformly reduce the pressure to below 5MPa within 15 minutes. At this point, the supercritical CO2 fluid lost its dissolving ability, and the extract precipitated and was collected in the separation vessel, thus achieving the separation of the extractant and the extract.

[0194] The preparation process involves slowly adding chitosan to water while stirring at 400 rpm and maintaining a temperature of 50°C. After dissolving, citric acid is added to adjust the pH to 4.5. Then, plant extracts and antioxidants are added, and stirring continues for 60 minutes until the mixture is homogeneous. Finally, the mixture is filtered to remove impurities, yielding a transparent, viscous liquid.

[0195] Step five, storage condition control, includes the following sub-steps:

[0196] The storage environment is set up using an intelligent cold storage, with the temperature controlled at 4°C, humidity maintained at 90%, gas composition adjusted to 5% oxygen and 6% carbon dioxide, and light intensity below 50 lux to avoid photo-oxidation.

[0197] For storage management, fresh corn is packaged in breathable plastic bags, each weighing 10kg. Ventilation channels are left when stacking, and the stacking height does not exceed 2 meters. The air circulation speed in the storage is 1.0m / s.

[0198] The monitoring system acquires real-time data on temperature, humidity, gas composition, and images inside the warehouse and transmits it to the central control system. The system automatically records and analyzes the data every two hours and automatically adjusts the refrigeration or controlled atmosphere equipment when the parameters deviate from the set range.

[0199] Step five, quality monitoring and adjustment, includes:

[0200] Regular sampling was conducted, with 20 bunches of fruit randomly selected from the storage warehouse every 7 days to test sugar content, moisture content, firmness, mold rate, and sensory quality.

[0201] The strategy is adjusted as follows: when the sugar content drops by more than 15% or the mold rate exceeds 5%, the storage temperature is adjusted to the lower limit or the frequency of preservative spraying is increased; when the moisture content is below 70%, the humidity is increased to the upper limit. All adjustments are based on the prediction model.

[0202] Data integration involves comparing all test data with pre-harvest data to generate quality trend reports, which are used to optimize subsequent harvesting and storage parameters and shared with farmers and processing enterprises through a cloud platform.

[0203] Comparative Example 1 differs from Example 1 in that: in ecological planting management, scientific fertilization and irrigation management were not implemented according to the growth stages of fresh corn.

[0204] Comparative Example 2 differs from Example 1 in that, in determining the harvesting time, the decision was not based on quality index monitoring and harvesting prediction models, but rather on a fixed number of planting days.

[0205] Comparative Example 3 differs from Example 1 in that no natural preservatives were used in the post-harvest processing.

[0206] Comparative Example 4 differs from Example 1 in that, during the storage condition control process, the fresh corn was not placed in a controlled storage environment for regular quality monitoring and adjustment.

[0207] The comprehensive performance of the efficient harvesting and storage methods for fresh corn implemented in Examples 1-3 and Comparative Examples 1-4 was tested. The test items and methods are as follows:

[0208] Nutritional quality testing involved immediate sampling after harvesting to determine the sugar content, starch content, vitamin C content, and soluble protein content of fresh corn kernels. The comprehensive score of each nutritional indicator was calculated to assess the impact of different planting and management practices on the basic quality of fresh corn.

[0209] Sensory evaluation and harvest maturity assessment are conducted by a sensory evaluation team composed of trained evaluators. The team scores the appearance, color, aroma, kernel plumpness, sweetness, and crispness of fresh corn. Combined with data measured by a saccharimeter, the team comprehensively evaluates the accuracy of the harvest timing and its impact on the quality of the product.

[0210] The quality retention rate test during storage involves placing fresh sweet corn that has undergone post-harvest treatment under standard storage conditions and taking samples on day 0, day 15, and day 30 of storage to measure its sugar content, hardness, weight loss rate, and mold rate. The retention rate of each index relative to the initial value is calculated to quantify the effect of different post-harvest treatment methods on delaying quality deterioration.

[0211] The shelf life and loss rate test: at the end of the set storage period, the proportion of fresh corn in each group that still maintains commercial value, that is, the proportion of ears with a sensory score of not less than 7 points and no visible mold, is defined as the shelf life qualification rate; at the same time, the proportion of inedible ears due to rot, water loss and serious quality decline is calculated and defined as the storage loss rate.

[0212] The test data of the efficient harvesting and storage methods for fresh corn implemented in Examples 1-3 and Comparative Examples 1-4 are recorded in the table below:

[0213]

[0214] Comparison and analysis of the data in the table show that the high-efficiency harvesting and storage of fresh corn implemented using the methods in Examples 1-3 exhibits significantly superior overall performance compared to Comparative Examples 1-4. This indicates that ecological planting management, through the implementation of scientific fertilization and irrigation management, dynamically adjusts nutrient and water supply according to the growth stages of fresh corn, providing a balanced nutritional environment for its growth and thus promoting the balanced development of fresh corn quality indicators. The timing of harvesting, based on quality indicator monitoring and harvest prediction models, accurately judges the maturity status of fresh corn, ensuring harvesting at the optimal time and laying the foundation for obtaining high-quality fresh corn. High-efficiency harvesting operations reduce mechanical damage to fresh corn by optimizing harvesting parameters and the harvesting environment, and immediately transfer it to a shaded environment to slow down post-harvest physiological deterioration. Post-harvest treatment, through cleaning, grading, and treatment with natural preservatives, removes surface contaminants and performs quality grading. Simultaneously, natural preservatives form a film on the surface of the fresh corn, inhibiting microbial growth and moisture loss, synergistically maintaining the freshness and marketability of the fresh corn. Storage condition control involves placing fresh corn in a controlled storage environment and regulating temperature, humidity, gas composition, and light conditions to inhibit respiration and nutrient loss. Combined with regular quality monitoring and adjustment strategies based on predictive models, storage parameters are dynamically optimized to achieve dynamic control of the storage quality of fresh corn, extend its shelf life, and reduce storage losses.

[0215] By comparing and analyzing the relevant data in the table, it can be seen that the method provided by the present invention can not only improve the nutritional quality and harvest maturity accuracy of fresh corn, but also extend its shelf life and reduce storage losses.

[0216] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0217] 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 efficient harvesting and storage of fresh corn based on ecological planting, characterized in that: Includes the following steps: Step 1: Ecological planting management, using green planting technology to grow sweet corn, reducing the use of chemical pesticides and fertilizers; Step 2: Determining the harvesting time. Based on the monitoring of quality indicators of fresh corn, including sugar content, hardness, moisture content, taste indicators and nutritional indicators, the optimal harvesting time is determined. The quality indicators are measured in real time using portable testing equipment. Step 3: Efficient harvesting operation. Mechanized harvesting equipment is used for harvesting. Harvesting parameters are adjusted to minimize mechanical damage. Fresh corn is immediately moved to a shaded environment after harvesting. Step 4: Post-harvest processing. Clean and grade the harvested fresh corn, and use natural preservatives for preservation. Step 5: Storage condition control. Place the processed fresh corn in a controlled storage environment, controlling the temperature, humidity, gas composition and light conditions, and conduct regular quality monitoring and adjustments.

2. The method for efficient harvesting and storage of fresh corn based on ecological planting according to claim 1, characterized in that: The ecological planting management in step one includes the following sub-steps: For soil preparation, select sandy loam or loam with a pH value of 6.0-7.5, plow to a depth of 25-30cm, and apply organic fertilizer and bio-fertilizer to improve the soil. The amount of organic fertilizer applied is 2000-3000 kg / mu, and the amount of bio-fertilizer applied is 50-100 kg / mu. The planting method adopts reasonable dense planting, with a row spacing of 60-70cm and a plant spacing of 25-30cm, resulting in a planting density of 3000-4000 plants per acre; During the growing season, scientific fertilization and irrigation management are implemented according to the growth stages of sweet corn. Fertilization is mainly based on organic fertilizer, supplemented by chemical fertilizer. Irrigation adopts drip irrigation or sprinkler irrigation system, and the irrigation amount is controlled based on soil moisture sensor to maintain soil moisture at 60%-80% field capacity.

3. The method for efficient harvesting and storage of fresh corn based on ecological planting according to claim 2, characterized in that: The specific procedures for scientific fertilization during the growth period management include: Base fertilizer application: Apply well-rotted organic fertilizer before planting. The organic fertilizer is made from livestock and poultry manure and crop straw compost, with the nitrogen, phosphorus and potassium ratio controlled at 1.0-1.5:0.3-0.7:0.5-1.2, and the application rate is 1500-2000 kg / mu. For topdressing management, organic liquid fertilizer is applied during the jointing and tasseling stages of fresh corn. The organic liquid fertilizer is made by mixing soybean meal fermentation liquid and fish protein fertilizer at a mass ratio of 0.8-1.2:0.8-1.

2. The amount applied each time is 100-150 kg / mu. After the topdressing is completed, weeding and cultivation are carried out between the crop rows. Use a cultivator or hoe to loosen the topsoil to a depth of 3-5 cm, and cut and remove the roots of weeds at the same time. Foliar fertilizer supplementation: During the grain-filling period, spray micronutrient foliar fertilizer containing zinc, boron, and magnesium at a concentration of 0.1%-0.3% each. The application rate is 50-100 L / mu, and the spraying frequency is once every 7-10 days, for a total of 2-3 times.

4. The method for efficient harvesting and storage of fresh corn based on ecological planting according to claim 2, characterized in that: The irrigation management operations during the growth period specifically include: The irrigation system is set up with an intelligent drip irrigation system. The spacing of the drip tape is matched with the row spacing, the dripper flow rate is 2-4L / h, and the irrigation water is purified rainwater or groundwater. The irrigation plan is based on real-time meteorological data and soil moisture monitoring to formulate a dynamic irrigation scheme. During the seedling stage, the soil moisture is maintained at 50%-60%, from the jointing stage to the tasseling stage it is increased to 70%-80%, and during the grain filling stage it is maintained at 65%-75%. The irrigation depth is 20-30cm each time. Moisture monitoring involves acquiring soil moisture data at a depth of 10-20cm, with data collection occurring once per hour, and irrigation parameters are adjusted in real time based on the monitoring data.

5. The method for efficient harvesting and storage of fresh corn based on ecological planting according to claim 1, characterized in that: Step two, determining the harvesting timing, includes the following sub-steps: Quality indicators are monitored starting from the milk stage of fresh corn. 10-20 ears of corn are sampled and tested daily. The test indicators include sugar content, starch content, moisture content, protein content and sensory score. The sugar content should be 14%-18% and the moisture content should be 70%-75%. The sensory score is based on appearance, color and smell and is conducted by professionals. The full score is 10 points and the score should be 8 points or above. The monitoring equipment includes a digital refractometer to measure sugar content, a near-infrared spectrometer to measure starch and protein content, and a moisture meter to measure moisture content. All data are entered into a database for trend analysis. The decision-making model, based on historical data and machine learning algorithms, establishes a harvest prediction model. When the quality indicators are stable within the optimal range for three consecutive days, a harvesting instruction is triggered, ensuring that the harvesting time error does not exceed 24 hours.

6. The method for efficient harvesting and storage of fresh corn based on ecological planting according to claim 1, characterized in that: The efficient harvesting operation in step three includes the following sub-steps: The harvesting equipment is a self-propelled fresh corn combine harvester, with the harvester's travel speed adjusted to 3-5 km / h and the ear-picking roller speed set at 300-500 r / min; Harvesting should be done in the early morning or evening to avoid high-temperature periods. The ambient temperature should be controlled at 15-25°C and the humidity at 60%-80%. After harvesting, the ears of fruit should be placed in breathable containers and covered with shade nets. On-site processing involves preliminary sorting during harvesting to remove diseased, pest-infested, and mechanically damaged fruit bunches. Qualified fruit bunches are transported to the processing point within 30 minutes. The transport vehicles are equipped with a temperature control system to maintain a temperature of 10-15°C.

7. The method for efficient harvesting and storage of fresh corn based on ecological planting according to claim 1, characterized in that: The post-harvest processing in step four includes the following sub-steps: For cleaning, fresh corn ears are fed into a drum-type washing machine and cleaned with ozone water at an ozone concentration of 0.5-1.0 mg / L for 5-10 minutes. After cleaning, the ears are rinsed with clean water to remove any residue. The grading standard uses an automatic photoelectric sorting machine to grade the fruit according to weight, length and appearance indicators. Grade 1 ear of fruit weighs 250-300g, is 18-22cm long and has no defects. Grade 2 ear of fruit weighs 200-250g, is 15-18cm long and allows for minor defects. For preservation, the graded fresh corn is sprayed with a natural preservative. The spraying equipment is a high-pressure atomizing nozzle with a spraying pressure of 0.2-0.5 MPa. The amount of preservative used is 10-20 L per ton of fresh corn. After spraying, let it stand for 10-15 minutes to allow the preservative to form a film.

8. A method for efficient harvesting and storage of fresh corn based on ecological planting, as described in claim 7, characterized in that: The natural preservative is made from the following raw materials in parts by weight: 10-20 parts chitosan, 5-10 parts citric acid, 3-8 parts plant extract, 2-5 parts antioxidant and 50-70 parts water, wherein the plant extract is at least one of green tea extract or rosemary extract, and the antioxidant is at least one of vitamin C or vitamin E. Methods for preparing natural preservatives include: Raw material preparation: food-grade chitosan with a degree of deacetylation ≥85% is selected; citric acid is food-grade; plant extracts are prepared by supercritical CO2 extraction; and antioxidants are vitamin C or vitamin E in powder form. The preparation process involves slowly adding chitosan to water while stirring at 200-400 rpm and maintaining a temperature of 40-50°C. After dissolving, citric acid is added to adjust the pH to 3.5-4.

5. Then, plant extracts and antioxidants are added, and stirring continues for 30-60 minutes until the mixture is homogeneous. Finally, the mixture is filtered to remove impurities, yielding a transparent, viscous liquid.

9. A method for efficient harvesting and storage of fresh corn based on ecological planting, as described in claim 1, characterized in that: Step five, which involves controlling storage conditions, includes the following sub-steps: The storage environment is set up using an intelligent cold storage, with the temperature controlled at 0-4°C, the humidity maintained at 85%-90%, the gas composition adjusted to 2%-5% oxygen and 3%-6% carbon dioxide, and the light intensity below 50 lux to avoid photo-oxidation. For storage management, fresh corn should be packaged in breathable plastic bags, each weighing 5-10 kg. Ventilation channels should be left when stacking, and the stacking height should not exceed 2 meters. The air circulation speed in the storage should be 0.5-1.0 m / s. The monitoring system acquires real-time data on temperature, humidity, gas composition, and images inside the warehouse and transmits it to the central control system. The system automatically records and analyzes the data every two hours and automatically adjusts the refrigeration or controlled atmosphere equipment when the parameters deviate from the set range.

10. A method for efficient harvesting and storage of fresh corn based on ecological planting, as described in claim 5, characterized in that: The quality monitoring and adjustment in step five includes: Regular sampling is conducted, with 10-20 bunches of fruit randomly selected from the storage warehouse every 7 days to test sugar content, moisture content, firmness, mold rate, and sensory quality. The strategy is adjusted as follows: when the sugar content drops by more than 5%-15% or the mold rate exceeds 1%-5%, the storage temperature is adjusted to the lower limit or the frequency of preservative spraying is increased; when the moisture content is lower than 60%-70%, the humidity is increased to the upper limit. All adjustments are based on the prediction model. Data integration involves comparing all test data with pre-harvest data to generate quality trend reports, which are used to optimize subsequent harvesting and storage parameters and shared with farmers and processing enterprises through a cloud platform.

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