25 results about "Harvest time" patented technology

The invention discloses an emergent vegetation management method for increasing a biological carbon sequestration function, and belongs to the technical field of ecological system management and restoration, and the method comprises the following steps: in the stable growth period of emergent vegetation, discharging part of wetland moisture, and carrying out first mowing on overground parts of plants above the water surface; after the emergent vegetation further grows, the water level is restored to the end of the growth season, finally water is drained, secondary mowing is carried out, and all the emergent vegetation on the ground is harvested. According to the method, the overground biomass is increased through the plant photosynthetic carbon sequestration function by adjusting the appropriate harvesting time and mode of the wetland emergent vegetation, and therefore the biological carbon sequestration amount is increased. Compared with a traditional method for harvesting wetland vegetation at a time, the method has the advantages that the plant growth rate is remarkably increased, the overground biomass of the plants and the accumulation of organic carbon in surface soil are promoted, and the improvement of the wetland carbon sequestration function is facilitated.

This invention relates to a method for dense planting of grain and medicinal herbs in intercropping, specifically within the field of intercropping of crops and medicinal herbs. The development of modern agriculture through corn / Astragalus intercropping requires reducing water and fertilizer inputs while maintaining high yields. However, it faces challenges such as unscientific management and a lack of technical support for increasing yield and reducing emissions. The method described herein is implemented according to the following steps: Step 1: Pre-planting tillage; Step 2: Drip irrigation tape installation and sowing; Step 3: Irrigation and fertilization in the first year; Step 4: First corn harvest: Harvest the corn at its optimal harvest time in the planting year, and then shred the corn stalks to cover the Astragalus in the furrows; Step 5: Planting corn in the second year; Step 6: Irrigation and fertilization in the second year; Step 7: Harvesting the corn on the ridges and the Astragalus in the furrows in the second year, and shredding and returning the corn stalks to the field after the second harvest; Step 8: Tilling the furrows.

The present application provides a kind of based on machine learning's mark metabolite model prediction method of optimal harvest period of Chinese yam, steps are as follows: collecting Chinese yam samples of different harvest periods, obtain metabolomics data by analyzing Chinese yam samples through metabolomics technology;Metabolomics data are preprocessed;The feature related to the growth period of Chinese yam is obtained by using machine learning algorithm to select potential marker metabolite;LASSO regression method is used to screen potential marker metabolite to construct marker metabolite prediction model;The area under ROC curve is used to verify the constructed marker metabolite prediction model;The metabolomics data of new Chinese yam are input into the marker metabolite prediction model to obtain model score, and whether Chinese yam is suitable for harvesting is judged according to model score.The present application can accurately predict the optimal harvest period of Chinese yam, eliminate subjectivity and experience dependence, improve scientificity, reduce external environmental influence, realize Chinese yam production capacity maximization, and provide reliable technical support for agricultural production.

The present application relates to improvements in lentiviral manufacturing for the production of CAR-T cell drug products wherein the manufacturing method comprises a change in time between transfection and harvest of the host cell, and a new vector ratio for transfection. Presented herein are methods of making lentiviruses at various vector ratios and the time between host cell transfection and harvest, as well as transfection compositions comprising various vector ratios.

A mechanism for monitoring cannabis and predicting or determining a harvesting time. A sensing arrangement generates a temporal sequence of VOC values, each representing a measured amount of a first set of one or more volatile organic compounds (VOCs) in the air surrounding some cannabis. This temporal sequence is then processed to determine a harvesting time, at which the cannabis is ready for harvesting (e.g., meets some predetermined criteria for achieving a harvesting goal).

The invention provides a plant growth regulator for delaying the harvesting time of cut-flower roses as well as a preparation method and application of the plant growth regulator, and belongs to the technical field of fresh cut flower cultivation. The plant growth regulator for delaying the harvesting time of the cut-flower roses comprises the following raw materials: 1-naphthylacetic acid, abscisic acid, cytokinin, a water-soluble fertilizer containing amino acid and monopotassium phosphate. According to the plant growth regulator for delaying the harvest time of the cut-flower roses, provided by the invention, the 1-naphthylacetic acid, the abscisic acid and the cytokinin are compounded together, so that the flower blooming process can be effectively delayed, and the harvest time is delayed. The plant growth regulator takes plant hormones as main raw materials, has the advantages of environmental friendliness, safety, harmlessness, low cost and the like, and further accurately regulates and controls the flower development process of the cut-flower roses by ensuring normal hormone signal transduction and development regulation and control. The growth regulator can effectively delay the harvesting time, powerfully ensures that the cut-flower roses are accurately marketed as required and the quality of the cut-flower roses is improved, and remarkably improves the production benefits and the industrial value.

1. A computer-implemented system for managing a tea harvest, the system comprising: a data store storing data defining one or more growing areas of a tea plantation; for each of the growing areas of the tea plantation defined in the data store, a growth and yield prediction module configured to model a plurality of tea plants within the respective growing area, thereby predicting the growth of each tea plant within the respective growing area over a period of time, and therefore the yield of each growing area of ​​the tea plantation when harvested; the growth and yield prediction module further configured to predict a recommended harvest time to achieve a desired quality of tea and a desired yield of tea; and a user interface module configured to provide a user with the predicted yield of each growing area of ​​the tea plantation when harvested.

A two-year-three-cropping planting method for areca taros, flue-cured tobaccos and rice comprises the following steps that 1, the areca taros are planted; planting the seed taros in the field from February to March in the same year; in September to November, mother taros of areca taros 2) flue-cured tobacco planting; the flue-cured tobaccos are transplanted in the field in spring of the second year, and leaves are harvested in time from May to June in the current year; 3) rice planting; performing irrigation, soil preparation and fertilization treatment on the field, planting rice, and harvesting the rice from September to October in the same year. According to the planting method, a new two-year three-cropping planting method for the areca taros, the flue-cured tobaccos and the rice is constructed, the harvesting time can be dispersed through a two-year three-cropping mode, labor tension caused by simultaneous harvesting is avoided, smooth crop harvesting is ensured, and the yield of the crops is increased. And moreover, the problems that diseases and insect pests are easily increased due to continuous cropping of areca taros and the quality and yield of succeeding crops are affected due to soil nutrient imbalance are solved, so that higher economic benefits are obtained, and new power is provided for local economic development.

The invention relates to a plant rapid breeding system and method based on optical detection. The system comprises an optical monitoring unit and a processing unit, and the optical monitoring unit is at least provided with a first monitoring part used for acquiring optical information of a first morphological characteristic of a plant and a second monitoring part used for acquiring optical information of a second morphological characteristic of the plant. The first monitoring part is started at least in response to a processing result obtained by the processing unit based on the monitoring data of the second monitoring part, and the processing result at least represents that the growth node of any cultivated plant enters a harvesting period. The method at least comprises the following steps: carrying out optical information acquisition on part of morphological characteristics of a plant by utilizing one or one group of monitoring parts; optical information collection is carried out on the other part of morphological characteristics of the plant through the other monitoring part or the other group of monitoring parts, and the other part of morphological characteristics at least comprise the harvesting tissue of the plant, so that the harvesting time and the harvesting scheme of the harvesting tissue of the plant are estimated and determined.

An object of the system according to the embodiment is to enable even a person who does not have knowledge about agriculture to identify characteristics of land, diseases of plants, and pests, and to realize stable production of agricultural crops in response to climate change.SOLUTION: A system includes a climate data analysis part, an image analysis part, a land characteristic analysis part, and a harvest prediction part. The climate data analyzer analyzes the climate data. The image analysis part specifies the disease and the harmful insect of the plant based on the weather data analyzed by the weather data analysis part. The land characteristic analysis unit analyzes the characteristics of the land based on the disease or pest of the plant specified by the image analysis unit. The harvest prediction unit predicts a harvest period and a harvest amount of the crop based on the property of the land analyzed by the land property analysis unit.SELECTED DRAWING: Figure 1

To provide an agricultural grain reaping auxiliary mechanism capable of harvesting a large amount of beans such as adzuki beans cultivated in a large number of ridges at a time while remarkably reducing harvest loss regardless of seeding in various ridge widths, remarkably improving harvest work efficiency and remarkably shortening harvest time.SOLUTION: The air blowing device includes an air blowing pipe 4 having a plurality of sets of a pair of branch pipe 4a parts connected to a main pipe 4b part, a structure for freely adjusting an inclination and a height position to a cutting blade 22 of the tip part 4b1 part of the branch pipe, and a structure for adjusting an interval between the respective branch pipes connected to the main pipe and a substantially horizontal direction of the tip part of the branch pipe. The distal end portions of the branch pipes are narrowed in the vertical direction of the pipe line so as to eject air in a carpet shape, and have a slit-shaped ejection hole 4b1a opened forward and laterally, and each pair of branch pipes is arranged in a direction in which the distal end portions approach each other so that the air ejected in the carpet shape from the slit-shaped ejection hole intersects at the distal end position of the cutting blade.SELECTED DRAWING: Figure 1

A system is provided.SOLUTION: The system includes a sensor means for measuring the humidity of soil, a sensor means for measuring temperature, a sensor means for measuring sunshine hours, a server means for collecting and analyzing data acquired from the respective sensor means, a control means for controlling watering and other environmental adjustment on the basis of a data analysis result, and an interface means for allowing a user to confirm a growth state and harvest timing.SELECTED DRAWING: Figure 1

The invention discloses a comprehensive treatment method and system for improving the germination rate of epimedium seeds. The method comprises the following steps: S1, intelligently judging the harvesting time; s2, standardized after-ripening treatment: putting the harvested seeds with fruits in a ventilated environment with the temperature of 20-22 DEG C and the humidity of 50%-60% for in-vitro after-ripening, and turning every day until the fruit state reaches a preset after-ripening end point; s3, dynamic controlled atmosphere storage: mixing the seeds subjected to after-ripening treatment with sterilized river sand, storing in a controlled atmosphere environment with the temperature of 6-10 DEG C and the CO2 concentration of 5%, regularly ventilating, and adding a vitamin E preservative into the mixed matrix; s4, breaking dormancy and accelerating germination; and S5, process monitoring and parameter optimization. According to the method, a double-channel intelligent judgment model of image form recognition and physiological index (soluble sugar) detection is constructed, the limitation of purely depending on appearance experience is overcome, form maturity and physiological maturity indexes are combined, the optimal initial quality of the harvested seeds is ensured, and a foundation is laid for the high germination rate from the source.

We provide the system. [Solution] Means for obtaining environmental information, A means for integrating and standardizing acquired environmental information, An artificial intelligence model for evaluating and predicting plant growth based on integrated information, A means to propose the optimal management methods and harvest times for each plant, Means for notifying the user's terminal of suggestions and warnings, A means for monitoring and managing information on urban green spaces and agriculture in real time, A system that includes this.

The system according to the embodiment aims to enable individuals to easily grow high-quality coffee at home. [Solution] A system according to an embodiment includes a receiving unit, a generating unit, a monitoring unit, and a predicting unit. The receiving unit receives information from a user. The generating unit sets environmental conditions based on the information received by the receiving unit. The monitoring unit monitors the environmental conditions set by the generating unit. The predicting unit predicts the progress of cultivation or the harvest time based on the information monitored by the monitoring unit.

This invention discloses a method for targeted bud retention and production period control in banana cultivation, including bud retention principles, production period control, selection of primary buds, forced development of secondary buds, and production management. Specifically, production period control involves forcing secondary buds to develop based on the current banana crop's growth period, the following year's harvest time, and climatic conditions. For large banana plantations, this is done in 2-4 batches, with each batch spaced 0.5-3 months apart, achieving staggered market entry, reducing the risk of concentrated market entry, and improving economic benefits. Taking Guangxi as an example, the peak banana market period in Guangxi is from September to early October, with lower prices. Therefore, the time for retaining secondary buds is between July and early August and between late September and early November. Using this method, banana buds can be selectively retained at deeper buds, improving yield and quality, concentrating and controlling the production period, simplifying management, increasing economic benefits, and extending the management lifespan of the banana plantation.

An object of a system according to an embodiment is to accurately determine an optimum harvest time of fruit and efficiently harvest the fruit.SOLUTION: A system according to an embodiment includes an imaging and sweetness determination machine, a generation AI, a notifier, an automatic harvesting robot, and a harvesting box. The imaging and sweetness determination machine measures the sugar content of the fruit. The generation AI analyzes the sweetness measured by the imaging and sweetness determination machine, and calculates an optimum harvesting time. The notifying unit notifies the harvesting time calculated by the generation AI. The automatic harvesting robot harvests the fruit based on the harvest time notified by the notification unit. The harvest box stores harvested fruits.SELECTED DRAWING: Figure 1

The invention relates to the technical field of agricultural detection, in particular to a method for judging the optimal harvest time of Chinese herbaceous peony based on a soft X-ray imaging technology, which comprises the following steps: S1, collecting Chinese herbaceous peony samples according to a time gradient; s2, performing embedding and slicing treatment on the root of the peony sample; s3, scanning at double energy points of 530 eV and 545 eV by adopting a soft X-ray imaging system, and acquiring an oxygen element distribution image of the starch granules on the basis of oxygen element absorption edge characteristics; s4, processing the starch grain distribution image to obtain an oxygen element specificity distribution diagram; and S5, quantitatively detecting the average gray value of the starch granules through image analysis software, and judging the optimal harvesting time. According to the method, high-resolution imaging and quantitative analysis of the Chinese herbaceous peony root starch granules are realized and the optimal harvesting time of Chinese herbaceous peony is determined by utilizing the high sensitivity of soft X-rays to oxygen element absorption edge characteristics at a specific energy point.

The invention relates to the technical field of Laifeng ginger planting, and specifically provides a Laifeng ginger optimal harvesting time determination method based on texture characteristics and cell wall polysaccharides, and the method comprises the following steps: S1, time node determination: starting harvesting from the 60th day after sowing, then harvesting for one period every 30-60 days, and at least harvesting for four periods; s2, detection: selecting tender ginger of Laifeng ginger harvested at different periods in the step S1, and detecting the brittleness value, the moisture content, the transverse relaxation time of bound water, the total pectin content and the cellulose content; s3, single score conversion: converting the detection values into corresponding single scores according to a preset five-level segmentation scoring rule; and S4, comprehensively judging different brittleness harvesting periods by adopting a weighted scoring function. According to the method, a three-in-one harvesting standard of time nodes, quantitative indexes and visual characteristics is formed, traditional experience dependence is broken, technical support is provided for large-scale and standardized planting, and standardized development of the Laifeng ginger industry is promoted.

To accurately determine timing for harvesting a harvesting object of a plant.SOLUTION: The harvest determination apparatus 100 includes a detection unit 110, a noise removal signal acquisition unit 120, a noise removal unit 130, and a determination unit 140. The detection unit 110 detects light transmitted through or reflected by the harvesting target F (hereinafter, referred to as detection light) and generates a detection signal. The noise removal signal acquisition unit 120 acquires a signal (hereinafter, referred to as a noise removal signal) for removing noise included in the detection signal. The noise removal unit 130 generates a noise-removed detection signal (hereinafter, referred to as a determination signal) using the detection signal and the noise removal signal. The determination unit 140 determines the harvest timing of the harvesting target using the determination signal.SELECTED DRAWING: Figure 1

A system is provided.SOLUTION: A system comprising means for collecting weather data, means for collecting soil data, means for collecting crop growth data, means for preprocessing the weather data, the soil data, and the crop growth data, means for training a generative AI model based on the preprocessed data, means for predicting an optimal harvest time and harvest method using the trained generative AI model, means for notifying an agricultural operator of the optimal harvest time and harvest method based on the prediction, and means for collecting feedback data and retraining to improve the generative AI model.SELECTED DRAWING: Figure 1

We provide the system. [Solution] Multiple sensors for collecting agricultural data, A data processing device equipped with a machine learning algorithm for predicting optimal growing conditions for crops based on collected data, A control device for automatically adjusting the cultivation environment of crops based on the aforementioned growth conditions, Based on the environmental adjustments made by the control device, a notification means predicts the harvest time of crops and notifies the user; A system that includes this.

The invention relates to the technical field of intelligent agricultural machinery operation decision making, in particular to a corn mechanized harvesting decision making method based on machine learning, which comprises the following steps: acquiring target variety grain moisture content observation data, genotype data and meteorological data aligned with observation time; establishing a grain moisture content dynamic prediction model based on the data, outputting probability distribution of the grain moisture content at the future moment, and determining a variety dehydration type according to the probability distribution; and inputting the future moisture content probability distribution, the dehydration type and the machine tool operation parameters into a mechanical harvesting operation loss model, respectively calculating ear harvesting and grain harvesting operation loss expected values and quantiles, determining a harvesting time window and a corresponding harvesting mode on a candidate moment set by adopting dynamic programming, and outputting a harvesting decision result. According to the method, the average loss and risk can be considered under the condition of predicting uncertainty, and the comprehensive loss such as crushing, entrainment, cleaning and drying energy consumption is reduced.

The invention relates to the technical field of vegetable sweet potato cultivation, and discloses a vegetable sweet potato annual high-yield cultivation method which comprises the following steps: S1, variety selection: selecting an existing vegetable sweet potato variety which is required to be high in regeneration capacity, good in disease resistance and suitable for multi-season planting; s2, seedling raising mode: selecting cutting seedling raising; s3, soil preparation and field planting, wherein loose and fertile sandy loam with good drainage is selected, and annual production is achieved through combination of a greenhouse and an open field; s4, field management: keeping the soil moist, watering seedling recovering water 7-10 days after field planting, watering once every 10-15 days in the growing period, and regularly applying fertilizer and preventing and controlling diseases and pests. According to the method, an existing vegetable sweet potato variety is selected, the requirements for high regeneration capacity, good disease resistance and adaptation to multi-season planting are met, the seedling raising mode of cutting seedling raising is selected, regular fertilization and pest control are conducted, the first-time harvesting time is delayed, side branch regeneration is promoted, and the harvesting frequency is increased; therefore, the method has the advantages of integrating facility regulation and control, improved variety breeding, rational close planting, green prevention and control and the like.

An object of a system according to an embodiment is to improve the efficiency of a process from agricultural production planning to harvesting and sales.SOLUTION: A system includes a data analysis part, a planting plan drafting part, a cultivation management part, a harvest management part, and a sales management part. FIG. 1 is a block diagram illustrating a configuration of a AI generation system according to a first embodiment; The planting plan creator creates an optimal planting plan based on the data analyzed by the data analyzer. The cultivation management unit analyzes the data collected from the sensors and instructs the timing of optimal irrigation, fertilization, and pest control. The harvest management unit analyzes the growth state of the crop and determines an optimal harvest time. The sales management unit sells the crop through the online sales platform.SELECTED DRAWING: Figure 1