577 results about "Chlorophyll content" patented technology

A rapid monitoring and discrimination method for drought conditions in summer maize based on chlorophyll content includes: 1) Obtaining multi-spectral imagery through UAV multi-payload low-altitude remote sensing technology and measuring chlorophyll content on the ground. Additionally, calculating vegetation indices including Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and Renormalized Difference Vegetation Index (RENDVI). 2) Selecting vegetation indices and constructing regression equations with measured chlorophyll content during different growth stages. The regression equation with the highest correlation for each growth stage is chosen as the optimal model equation for that particular stage. 3) Using the optimal model equations to retrieve chlorophyll content for each period and determining thresholds for chlorophyll content across different drought levels through calibration. 4) Calculating the required vegetation indices from real-time multi-spectral imagery of the field under test, retrieving chlorophyll content, and comparing it with the established thresholds to assess the real-time drought level.

A ginkgo canopy chlorophyll content estimation method based on an airborne hyperspectral image comprises the following steps: firstly, acquiring a ginkgo leaf canopy hyperspectral image and a chlorophyll content data set; and establishing a rapid prediction model for predicting the average content of chlorophyll in the canopy by using the hyperspectral image of the ginkgo leaf canopy, and predicting the corresponding chlorophyll content by using the model and taking the hyperspectral image of the ginkgo leaf canopy as input. The model establishment process comprises the following steps of: firstly, preprocessing an image by using multiple scatter correction (MSC); secondly, carrying out characteristic wave band selection on the preprocessed spectral data by adopting a competitive self-adaptive reweighted sampling algorithm CARS; and finally, substituting the screened characteristic wave band spectral data and the actually measured chlorophyll value into an XGBoost-RF machine learning model, and establishing a hyperspectral chlorophyll content estimation model. The method provided by the invention is a nondestructive rapid detection technology, and can monitor the plant health condition in real time.

The invention discloses an application of a GHERF114 gene in regulating and controlling salt stress tolerance and drought stress tolerance of a plant. The ID (Identity) of the gene is GHA05G2445. According to the invention, an arabidopsis thaliana homozygous line over-expressing the GHERF114 gene is obtained through a transgenic technology; through phenotypic change after salt stress treatment and drought stress treatment, leaf wilting degree, rosette leaf size and form comparison, in-vitro leaf water loss rate, leaf relative water content, chlorophyll content and the like verification, it is indicated that the tolerance of transgenic arabidopsis thaliana to salt stress and drought stress is remarkably reduced, and a TRV: GHERF114 gene silent plant is obtained through a VIGS technology; compared with a control group after salt stress and drought stress treatment, the salt tolerance and the drought resistance of silent plants are remarkably improved. Results show that the GHERF114 plays an important role in plant salt stress and drought stress response processes, has important significance in breeding and research for improving salt tolerance and drought tolerance of cotton, and can be applied to screening of stress-resistant cotton varieties through a gene knockout technology.

The invention belongs to the technical field of chlorophyll content inversion, and discloses a canopy chlorophyll content inversion method based on feature extraction and a machine learning model, and the method comprises the following steps: employing a mode of combining an unmanned plane carrying a multispectral camera and ground actual measurement; collecting and processing the chlorophyll content data of the potato canopies, and planting a quilt index; carrying out feature selection by using a Pearson correlation analysis and competitive self-adaptive reweighted sampling algorithm; constructing a chlorophyll content inversion model based on machine learning; and carrying out chlorophyll content inversion model optimization based on a grey wolf optimization algorithm and a sparrow optimization algorithm, and carrying out precision evaluation. According to the canopy chlorophyll content inversion method based on feature extraction and the machine learning model, comparative study is carried out on the single growth period and the whole growth period of potatoes, the optimal inversion model suitable for the single growth period and the whole growth period is determined, and the accuracy and applicability of the study are guaranteed.

The invention discloses a cauliflower phenotype analysis and prediction method based on a field high-throughput phenotype system. According to the method, on the basis of RGB images and hyperspectral images of field cauliflower, through a cauliflower segmentation model, cauliflower, flower ball and leaf areas are automatically extracted, phenotype data and chlorophyll content are extracted, data of different growth periods are sorted according to a time sequence, a growth curve is drawn, and a regression model is constructed, so that the growth states of the cauliflower in different stages are predicted. Compared with the prior art, an effective non-contact scheme is provided for cauliflower phenotype analysis, phenotype parameters of cauliflower can be obtained without manual field on-site measurement, and corresponding culture measurement is combined, so that the cauliflower culture efficiency can be effectively improved, the culture cost can be reduced, and double friendliness of human resources and biological safety is realized.

The invention belongs to the technical field of agriculture, and particularly provides a compound microbial agent and application thereof. The compound microbial agent is prepared from bacillus velezensis RKN1111, bacillus subtilis N-3 and paenibacillus mucilaginosus HX-02, and the compound microbial agent is prepared from bacillus velezensis RKN1111, bacillus subtilis N-3 and paenibacillus mucilaginosus HX-02, and the compound microbial agent is prepared from bacillus velezensis RKN1111, bacillus subtilis N-3 and paenibacillus mucilaginosus HX-02. The compound microbial agent can effectively improve the pH and EC of saline alkali soil, increase the content of alkali-hydrolyzable nitrogen, available phosphorus and quick-acting potassium in the soil, and play a significant role in increasing the plant height, stem diameter, chlorophyll content and aboveground biomass of corn plants in coastal saline-alkali soil.

The invention provides a small-region forest carbon sink accurate estimation method and system based on multiple constraints, and the method comprises the steps: respectively generating a canopy height model, a leaf area index and a chlorophyll content through obtaining unmanned plane laser radar data and multispectral data; generating a digital elevation model by adopting a lowest point filtering technology, realizing individual tree segmentation in combination with a gradient map and a watershed algorithm, and extracting individual tree geometric parameters; and constructing a carbon sink estimation model by using the geometric parameters and the physical and chemical parameters, and comprehensively calculating the carbon sink amount of the small region. The problems that a traditional carbon sink estimation method is insufficient in precision and low in automation level are solved, the single-tree segmentation precision and the carbon sink amount calculation precision are improved through deep fusion of geometric information and spectral information, full-process automation of data acquisition, data processing and carbon sink estimation is achieved, and the method is suitable for large-scale popularization and application. The method is suitable for carbon sink monitoring requirements of various forest types and complex terrain scenes.

The invention provides an organic fertilizer utilization effect evaluation system and method based on spectral analysis, and relates to the technical field of organic fertilizer effect evaluation.The method comprises the steps that spectral images of a crop # imgabs0 # before and after organic fertilizer application are collected, and meanwhile the dry matter ratio and the photosynthetic rate of a crop # imgabs1 # before and after fertilizer application are obtained; calculating the chlorophyll content, the nitrogen content, the leaf area index, the transpiration intensity and the plant moisture content of the crop # imgabs2 # before and after fertilization according to the reflected wave data, and calculating the plant growth health index, the moisture utilization efficiency index and the photosynthetic transpiration index; according to the method, a comprehensive evaluation model is constructed, comprehensive evaluation indexes of the crop # imgabs3 # before and after fertilization are respectively generated by utilizing the comprehensive evaluation model, a difference value of the comprehensive evaluation indexes is calculated to serve as a fertilizer efficiency evaluation index, and the utilization effect of the organic fertilizer is evaluated according to the difference value, so that comprehensive monitoring and quantitative analysis of the crop growth condition are realized, and the application effect of the organic fertilizer is objectively reflected.

The invention discloses a multifunctional peoriae paenibacillus and application thereof, and relates to the technical field of microorganisms, and the key point of the technical scheme is as follows: Paenibacillus peoriae S6330 is separated from rhizosphere soil; the peoriae paenibacillus has a good inhibition effect on pathogenic bacteria, pathogenic fungi and oomycetes; meanwhile, the peoriae paenibacillus has the functions of dissolving potassium, producing protease, producing amylase, producing cellulase, producing siderophore and the like, has a growth promoting effect on various crops such as wheat, corn, watermelons, small oilseed rapes, tobaccos and the like, and can remarkably improve indexes such as chlorophyll content, plant height, fresh weight, overground part weight, underground part weight and the like of plants; in addition, the peoriae paenibacillus can be used for effectively inhibiting the tobacco bacterial wilt; the peoriae paenibacillus has no environmental pollution problem, is simple in culture condition, and has wide disease prevention and growth promotion application prospects in agricultural production.

The invention relates to the technical field of agricultural irrigation, and discloses a water-saving irrigation intelligent self-adaptive regulation and control system which comprises a sensor module including a soil humidity sensor, a meteorological sensor group and a crop growth sensor group, and the soil humidity sensor and the crop growth sensor group are installed in a farmland; and the meteorological sensor group is arranged near the farmland. According to the intelligent self-adaptive regulation and control system and method for water-saving irrigation, various sensors are integrated, so that data such as real-time temperature, humidity, rainfall and wind speed of an irrigation area and data such as plant height, leaf area and chlorophyll content of crops are monitored, and indexes for further reflecting the water demand condition of the crops are provided. According to the method, comprehensive and accurate environment and crop information can be obtained in real time, comprehensive analysis is carried out by utilizing an algorithm based on the data, and the actual water demand of the crops in different growth stages is accurately determined, so that targeted irrigation of the land is realized, and water source waste is reduced.

The invention belongs to the field of crop science and agricultural molecular biology, and particularly relates to application of a BAK gene to enhancement of flood tolerance of rape, and the BAK gene is a BnaA04.BAK7 gene; the login number of the BnaA04. BAK7 gene in a gene pool is BnaA04g015000WE, and the login number of the BnaA04. BAK7 gene in the gene pool is By destroying the expression of the BAK gene, it is found that after the expression of the BAK gene is destroyed, the flooding tolerance of the brassica napus under flooding stress is weakened, and the invention discloses for the first time that hypocotyl growth of the brassica napus under flooding stress is slow and chlorophyll content is reduced due to function deletion of the BAK gene. New gene resources and theoretical guidance are provided for research and application of the flood tolerance of the rape.

The invention provides application of molybdenum disulfide nanoparticles in preparation of a tomato leaf fertilizer, and particularly relates to the technical field of tomato fertilizers. The molybdenum disulfide nano-particles act on tomato plants in a foliage spraying manner, so that the growth of the tomato plants is promoted and / or the fruit quality is improved. The molybdenum disulfide nanoparticles are used as the foliar fertilizer to significantly increase the plant height and stem diameter of tomatoes, increase the chlorophyll content and trace element content of plants, increase the vitamin C content, soluble sugar content and soluble solid content of tomato fruits, and significantly increase the accumulation of Mo and S of plants through the sulfur-molybdenum synergistic effect, so that the yield of the tomatoes is increased. A scientific basis is provided for reasonable application of the nano molybdenum fertilizer, and a way is opened up for high-yield and high-quality cultivation of tomatoes.

The invention discloses application of a GsRZ1A gene in improving alkali resistance of plants, and belongs to the technical field of genetic engineering. The nucleotide sequence of the GsRZ1A gene is as shown in SEQ ID NO: 1, and the coded amino acid sequence of the GsRZ1A gene is as shown in SEQ ID NO: 2. A transgenic line is obtained by constructing an overexpression vector of the GsRZ1A gene and transforming soybeans. A transgenic line is subjected to alkali stress treatment, and a result shows that the overexpressed GsRZ1A soybean line shows a faster relative growth rate, the total leaf area, the leaf chlorophyll content and the relative water content are all higher than those of a control line of an empty vector, the total root length and the total root surface area of a root system are also remarkably larger than those of a control group, and the antioxidant enzyme activity can be improved; the accumulation of superoxide anions and malonaldehyde is reduced, and the accumulation of osmotic regulation substances such as soluble sugar is increased to enhance the tolerance of the soybeans to alkali stress, so that the method has an important application prospect in alkali-resistant plant breeding.

The invention relates to the technical field of agricultural quantitative remote sensing and intelligent agriculture, and discloses a multi-source remote sensing data radiation correction and chlorophyll content cross-platform inversion method, which comprises the following steps: synchronously obtaining ground actual measurement, unmanned aerial vehicle and satellite remote sensing data, calculating vegetation indexes, and screening sensitive characteristic variables by using Pearson correlation analysis; establishing a radiation correction model by adopting a ratio averaging method, performing radiation normalization processing on satellite data by taking unmanned aerial vehicle data as a reference, and eliminating sensor response differences; an SPAD inversion model is constructed and optimized based on Z-score standardization, the SPAD inversion model is migrated and applied to corrected satellite data, a regional scale chlorophyll distribution diagram is generated through pixel-by-pixel calculation, and then a differentiated farmland management strategy is formulated. According to the method, the difficulty of multi-source data collaboration is solved, the regional scale crop chlorophyll monitoring precision is improved, and scientific decision support is provided for large-area crop fertilization.

The invention relates to the technical field of saline-alkali soil improvement and microorganisms, in particular to bacillus pumilus S3-9 and application thereof. The bacillus pumilus S3-9 is preserved in the China General Microbiological Culture Collection Center on December 19, 2024, and the preservation number of the bacillus pumilus S3-9 is CGMCC (China General Microbiological Culture Collection Center) No. 33120. The bacillus pumilus S3-9 provided by the invention has the effects of reducing salinity in saline-alkali soil, increasing nutrients of the saline-alkali soil and improving the diversity and stability of rhizosphere microbial communities of the saline-alkali soil, and can be applied to improving soil fertility, promoting nutrient circulation, improving soil quality, relieving soil salinization and the like. The strain can also be used for increasing the yield of sweet sorghum in saline-alkali land, has a remarkable growth promoting effect on plant height, overground part fresh weight and underground part fresh weight, can effectively improve the K < + > / Na < + > ratio, chlorophyll content, superoxide dismutase activity and catalase activity, and is beneficial to enhancing the adaptive capacity of plants to salt stress.

The invention provides a bamboo forest growth monitoring method and device based on a multispectral image, and relates to the technical field of remote sensing monitoring, and the method comprises the steps: obtaining a multispectral image of a to-be-detected bamboo forest through a multispectral camera, and enabling the multispectral camera to be carried on an unmanned aerial vehicle; based on the multispectral image, growth indexes of the bamboo forest to be detected are obtained, and the growth indexes comprise the height of bamboo plants, the number of the bamboo plants, chlorophyll content indication values of the bamboo plants and biomass of the bamboo plants; based on the growth indexes, determining the bamboo forest growth vigor. According to the bamboo forest growth vigor monitoring method based on the multispectral image, the growth vigor of the bamboo forest is comprehensively analyzed through all growth indexes, and accurate and efficient growth vigor monitoring of the large-area regional bamboo forest is achieved.

The invention provides a cotton verticillium wilt resistance detection method based on an unmanned aerial vehicle chlorophyll detection model, relates to the technical field of data detection, and solves the technical problem of low cotton verticillium wilt resistance detection efficiency. The method comprises the following steps: acquiring RGB data and multispectral data of a specified field area of cotton through image acquisition equipment arranged on an unmanned aerial vehicle; based on the RGB digital orthoimage, the multispectral digital orthoimage and chlorophyll content data measured on site by different varieties of cotton, utilizing a machine learning algorithm to construct chlorophyll detection models of chlorophyll of different varieties of cotton in different growth periods by adjusting initial model parameters; based on the optimal chlorophyll detection model and the verticillium wilt disease index data, K-means clustering analysis and GIS space analysis are carried out, chlorophyll change rule data and verticillium wilt resistance levels of different varieties of cotton are obtained, and the verticillium wilt resistance levels of different varieties of cotton serve as cotton verticillium wilt resistance detection results.

The invention discloses a potato seedling grading environment parameter dynamic optimization regulation and control method, and relates to the technical field of agricultural informationization. Based on an Internet of Things sensor deployed in a target area, stem diameter, chlorophyll content and plant height data of potato seedlings are collected, the seedlings are divided into weak seedlings, middle seedlings and strong seedlings by adopting K-means clustering, and the weak seedlings, the middle seedlings and the strong seedlings are classified into a weak seedling classification model, a middle seedling classification model and a strong seedling classification model; setting the duration of the initial light period; and carrying out gradient photoperiod test on each type of potato seedlings by taking the stem elongation rate and the chlorophyll content as constraint conditions. Through grading photoperiod modeling and ant colony algorithm dynamic optimization, the limitation of traditional fixed photoperiod regulation and control is broken through, the initial photoperiod range is set based on the seedling physiological difference, and the photoperiod-growth rate response curved surface model is constructed in combination with the stem elongation rate and chlorophyll content constraint conditions. The influence of different photoperiod combinations on seedling growth is quantified, accurate matching of photoperiods and seedling requirements is ensured, excessive growth or premature senility is avoided, and the growth rhythm stability and the resource utilization efficiency are improved.

The invention discloses a continuous cropping Chinese cabbage planting method based on a microbial agent and application, and belongs to the technical field of crop cultivation. According to the planting method, Chinese cabbage and garlic are intercropped according to the ratio of 1: 1, and a trichoderma harzianum agent is applied. Results show that the planting method can significantly increase the growth indexes such as the plant height, the root length, the leaf chlorophyll content and the soluble sugar content of the Chinese cabbage; the soluble protein content, the peroxidase activity, the superoxide dismutase activity and the malondialdehyde content of the Chinese cabbage leaves are obviously reduced. Meanwhile, the content of rapidly available phosphorus, rapidly available potassium, effective calcium and other substances in the soil can be increased; the activities of urease, catalase and alkaline phosphatase in the soil are also obviously improved. In addition, the number of fungi, bacteria and actinomycetes in the soil is also remarkably increased. Therefore, according to the planting method, the quality of continuous cropping soil can be improved, Chinese cabbage growth is promoted, and theoretical support is provided for healthy and sustainable development of the Chinese cabbage industry.

The invention provides a method for improving maturity of a cigar coating, a product thereof and application of the product. The method comprises the following steps: carrying out infiltration and humidification, hanging rod balancing, vacuum pressure maintaining and humidification and microbial agent fermentation treatment on the cigar coating of a supplied material; the bacterial strains in the microbial inoculum comprise a combination of a brachybacterium paragglutinum HB001 bacterial strain with the preservation number of GDMCC No: 63066 and an agrobacterium przewalskii HB002 bacterial strain with the preservation number of GDMCC No: 63067. According to the method, the cigar coating is treated by adopting a specific treatment process, so that fence tissues and cell walls of the tobacco leaves are effectively damaged, the tobacco leaf tissues are loosened, and the chlorophyll content in the tobacco leaves is reduced, thereby effectively improving the conditions of greenness, stiffness and the like of the cigar coating and improving the quality of the tobacco leaves.

The invention discloses an ecological environment remote sensing data analysis method, and belongs to the technical field of ecological environment. The data analysis method comprises the following steps: collecting remote sensing image data of a monitored water area, and carrying out atmospheric correction and geometric correction on the remote sensing image data; utilizing a co-occurrence matrix method to extract water body spectral texture features so as to identify spectral texture feature wavebands related to water body turbidity, chlorophyll content and dissolved oxygen; constructing a water quality parameter inversion model, training and verifying the model by using field sampling data, and optimizing the model; regularly acquiring new remote sensing image data of a monitoring area, inputting the new remote sensing image data into the optimized water quality parameter inversion model, and monitoring spatial and temporal distribution changes of water pollution parameters; determining a key area according to an inversion result, and obtaining high-temporal-spatial-resolution supplementary data of the key area by using the unmanned aerial vehicle; and collecting meteorological and hydrological station observation data, and comprehensively analyzing the source and flow direction of pollutants in combination with the inverted water quality parameter spatial and temporal distribution information.

The invention provides a cotton yield prediction method and device, equipment and a medium, and relates to the field of cotton yield prediction, and the method comprises the steps: obtaining an RGB image and a multispectral image of to-be-predicted cotton in a flowering and boll-setting period; based on the RGB image and the multispectral image, determining the growth state of the to-be-predicted cotton and agricultural condition parameters of a cotton field where the to-be-predicted cotton is planted; inputting the agricultural condition parameters into a pre-trained chlorophyll prediction model to obtain predicted chlorophyll of the to-be-predicted cotton in a flowering and boll setting period; inputting the growth state and the predicted chlorophyll into a pre-trained cotton yield prediction model to obtain the predicted yield of the to-be-predicted cotton; wherein the cotton yield prediction model is obtained by training chlorophyll detection values and growth states of different varieties of cotton in historical flowering and boll-forming periods and yields of corresponding cotton in historical harvesting periods. The cotton chlorophyll content can be accurately predicted, the cotton yield can be efficiently predicted, and support is provided for cotton germplasm screening and accurate breeding.

The invention belongs to the technical field of biological agents, and particularly relates to ginsenoside variant flavobacterium DG-16 and application thereof in relieving continuous cropping obstacles of angelica sinensis and improving the quality of the angelica sinensis. According to the ginsenoside variant flavobacterium DG-16 disclosed by the invention, the growth of angelica sinensis is promoted by increasing the contents of jasmonic acid and cytokinin hormones, reducing the contents of gibberellin and salicylic acid hormones and promoting the circulation and utilization of nitrogen; in addition, the flavobacterium ginsenoside variant DG-16 can significantly increase the chlorophyll content, is beneficial to photosynthesis of the angelica sinensis, effectively changes the physiological and biochemical states of the angelica sinensis, can resist root rot of the angelica sinensis so as to relieve successive cropping obstacles and improve the quality, and has a significant effect.

The invention discloses a SiERF109 gene for regulating drought resistance, salt tolerance and flavonoid accumulation of millet and application of the SiERF109 gene, and belongs to the technical field of plant breeding. According to the invention, a gene SiERF109 with a nucleotide sequence shown as SEQ ID NO.1 is separated and cloned from millet, and fluorescent quantitative expression analysis shows that SiERF109 participates in drought and salt stress response of millet. After the gene is over-expressed in foxtail millet, in drought and salt stress experiments, compared with a wild type strain, the survival rate and chlorophyll content of a strain over-expressed with the SiERF109 gene are remarkably increased, the flavonoid content is increased by 33.5%-39.5%, and active oxygen accumulation is remarkably reduced; it is shown that the SiERF109 gene and the protein coded by the SiERF109 gene can remarkably improve the drought resistance, the salt resistance and the flavonoid content of the plant.

The invention provides a salt-tolerant gene, namely a PrABC1 gene and application thereof, and also provides a vector containing the gene, an expression cassette, a recombinant cell, a transgenic plant and a method for producing the transgenic plant. Specifically, the gene has a nucleotide sequence as shown in SEQ ID NO: 1 or SEQ ID NO: 2. The plant growth regulator can be used for improving the tolerance of plants to a salt stress environment, relieving the adverse effects of a high-salt environment on the germination rate and root length of the plants, reducing the water loss rate of the plants under the high-salt stress condition and reducing the reduction of the chlorophyll content.

The invention discloses a method for evaluating and screening salt tolerance of triticale germplasm resources in a germination stage, and belongs to the technical field of evaluation and screening of plant salt tolerance, salt stress concentration screening: triticale seeds are treated by NaCl solutions with different concentrations, indexes such as survival rate, plant height and overground part fresh weight are measured, the NaCl solution with the concentration of 200 mmol. L <-1 > is determined as the salt tolerance evaluation appropriate concentration, and the salt stress concentration is determined as the salt tolerance evaluation appropriate concentration. Salt tolerance evaluation test: carrying out salt stress treatment by adopting a 200mmol. L <-1 > NaCl solution, determining phenotypic indexes such as survival rate, plant height, fresh weight of overground part, root length and chlorophyll content, and physiological and biochemical indexes such as catalase, peroxidase and superoxide dismutase activity and malondialdehyde content, and carrying out principal component analysis, membership function analysis and clustering analysis to obtain a salt tolerance evaluation result. Calculating a salt tolerance comprehensive evaluation value, and screening salt tolerance triticale germplasm resources.

The invention belongs to the field of gene engineering, and particularly relates to a rice leaf whitening gene ALS as well as an encoding protein and application thereof. The invention discloses a chloroplast development regulation gene ALS (Albino Seedling), the gDNA sequence of the gene is as shown in SEQ ID NO.1, the CDS sequence of the gene is as shown in SEQ ID NO.2, and the amino acid sequence of encoded protein is as shown in SEQ ID NO.3. The invention also discloses a chloroplast development regulation gene ALS. Experiments show that after function deletion of the ALS gene, chloroplast in a rice mutant develops abnormally, the chlorophyll content is sharply reduced, and the rice mutant is albino and lethal in the seedling stage. The study on the ALS gene function provides a new germplasm resource for the study on the rice chloroplast development regulation mechanism, and the ALS gene can also be used as a leaf color marker in the seedling stage to be applied to the breeding of a new rice variety.

The invention relates to the field of gene engineering and molecular breeding, and discloses application of a ZmTCP5 gene in regulation and control of heat resistance of corn. According to the invention, three types of knockout mutants of the gene are obtained by using a CRISPR / Cas9 technology, and three overexpression materials are created. At normal temperature (25-28 DEG C), the material has no obvious phenotypic difference with a wild type; however, under high temperature stress (45 DEG C), the ZmTCP5 knockout mutant has enhanced heat resistance, reduced reactive oxygen species (ROS) accumulation, and significantly increased ROS scavenging enzyme activity, chlorophyll content and photochemical efficiency; on the contrary, the ZmTCP5 overexpression strain is more sensitive to heat stress, which indicates that the ZmTCP5 negatively regulates the heat resistance of the corn. The research provides a theoretical basis for analyzing a heat-resistant molecular mechanism of the corn, and also provides an important gene resource for creating a new germplasm of the heat-resistant corn.

The invention provides a fresh tobacco leaf chlorophyll content integrated model prediction method, medium and system, and belongs to the technical field of tobacco leaf detection.The method comprises the steps that transmission spectrums of fresh tobacco leaves with different maturity degrees are collected and subjected to black and white correction; dividing the leaf into six areas, collecting spectrums, and calculating an average value; carrying out multiple pretreatments on the original spectrum and dividing a data set; analyzing and establishing a relationship between the chlorophyll content and the spectrum based on a photosynthetic pigment absorption mechanism, and screening key wavelengths; the FMR-NSGA multi-objective optimization algorithm is fused with the F test and mutual information method to screen characteristic wavelengths; dynamically eliminating redundant features by using a recursive feature elimination method; establishing a parameter mapping function, and automatically determining a model hyper-parameter according to the wavelength importance index; a Stacking framework is constructed, hyper-parameters are dynamically optimized by adopting a grey wolf optimization algorithm, the prediction precision is improved, and the technical problem of rapid and accurate prediction of the chlorophyll content of the fresh tobacco leaves is solved.

The invention discloses a microbial agent for promoting cucumber growth and a preparation method and application thereof, and belongs to the technical field of agricultural microorganisms. The microbial agent is prepared from the following components: achromobacter denitrificans, bradyrhizobium angularis and Vilnelandan nitrogen-fixing bacteria in a volume ratio of 2 to 1 to 1. Bacteria with a growth promoting effect are reasonably combined for use, so that the growth promoting effect of the mixed flora on cucumbers is better than that of a single strain, and the adaptability of the synergistic effect of the strains in the actual soil rhizosphere complex environment is higher. By determining the number of strains and mixing according to a specific proportion, germination of cucumber seeds is stably and effectively promoted, root elongation is promoted, the flowering and fruit setting rate is increased, and meanwhile the plant height, plant biomass and chlorophyll content of cucumbers in the seedling stage are increased. Besides, the microbial agent disclosed by the invention is beneficial to improving the growth quality and yield of plants and reducing environmental pollution, has wide application potential in the fields of agriculture and ecology, and is worthy of popularization.