10 results about "GREEN BELL PEPPER" patented technology

The invention provides an intelligent automatic green pepper harvesting device, which relates to the technical field of agricultural machinery and comprises an automatic harvesting vehicle, a cab is arranged on the left side above the automatic harvesting vehicle, a collecting box is arranged on the right side above the automatic harvesting vehicle, and a green pepper harvesting table is mounted in front of the automatic harvesting vehicle. A roller type conveying table is arranged behind the green pepper harvesting table, flexible clamping and guiding of green pepper fruit bodies are achieved through cooperation of a flexible silica gel baffle and a belt type clamping frame, direct rigid extrusion of a traditional rigid clamp is avoided, buffering protection is provided, a multi-stage flexible contact interface is jointly formed, and therefore the green pepper harvesting machine can be used for harvesting green peppers. The risk of skin abrasion or breakage caused by collision and extrusion in the initial picking stage of the green peppers is greatly reduced, and the problems that most picking parts are of rigid structures, lack of buffering in the fruit contact process, extremely prone to extrusion breakage or skin abrasion of the green peppers, serious influence on the appearance of commodities, shortening of the storage period and poor picking effect are solved. And direct economic loss is brought to planters.

The application discloses a kind of nothocinnamomum officinale grafting seedling raising methods, belong to the technical field of pepper grafting seedling, the method includes the following steps: (1) top pot pepper stock seedling cultivation: select 2-year-old disease-resistant, drought-resistant, well-growing top pot pepper big green pepper variety seedling as stock;(2) nothocinnamomum officinale scion collection: select current year nothocinnamomum officinale branch as scion, top of pruned scion, compound leaf, get grafting scion;(3) grafting: on the same stock, complete first branch grafting in late December-2 late, complete second bud grafting in late May-early July;(5) management after grafting: grafting survival carries out fertilization and weeding, solve the problem of low grafting survival rate caused by that cambium does not completely adhere when grafting.

This invention belongs to the field of pesticide residue detection technology, specifically relating to a method for detecting flufenoxuron and its active metabolites in plant-derived foods. The detection method includes: mixing and shaking the plant-derived food to be tested with a formic acid-acetonitrile solution; mixing and shaking the resulting mixture with sodium chloride and magnesium sulfate, followed by solid-liquid separation to obtain an extract; purifying the extract by mixing it with 10-30 nm multi-walled carbon nanotubes, followed by solid-liquid separation to obtain a test solution; and performing liquid chromatography-mass spectrometry (LC-MS) on the test solution to determine the content of flufenoxuron and its active metabolites in the plant-derived food based on the obtained peak area and a predetermined standard curve. The detection method provided by this invention can simultaneously detect flufenoxuron and its active metabolites with high sensitivity. In the examples, two compounds showed good repeatability and reproducibility in five matrices, enabling simultaneous detection of flufenoxuron and its active metabolites in spinach, green peppers, lemons, sweet oranges, and tea.

1. Name of the product in this design: Candle (Abstract Green Pepper). 2. Purpose of this design: Scented candle. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The invention relates to the technical field of seasoning processing, and discloses a cooking freshness-locking process for preparing green pepper sauce, which comprises the following steps: carrying out graded ultrasonic wall breaking treatment on green pepper pulp, promoting chlorophyll release by low-power ultrasound in the first stage and keeping fiber bundles complete, and thoroughly extracting chlorophyll by enhanced ultrasound in the second stage; separating the fiber bundles softened by enzymolysis from the pulp; preparing a natural phospholipid stabilized plant essential oil microemulsion, a modified polysaccharide-protein graft compound emulsifier and a natural chelated polysaccharide compound; performing low-temperature stir-frying for alkaline color protection and essential oil oxidation resistance, performing medium-temperature cooking to form polysaccharide gel embedded chlorophyll, and performing rapid cooling to 70-75 DEG C to lock a color protection state; soluble dietary fibers, xanthan gum-guar gum and konjac glucomannan are added to regulate the texture, and fiber bundles are added again to reconstruct tissues; and carrying out hot filling and sealing at 70-75 DEG C. According to the invention, high-efficiency release and long-acting protection of chlorophyll are realized, and good granular sensation and flowability of the green pepper sauce are maintained.

The invention discloses a construction method of a green pepper shredded potato quality sensory evaluation model. The method comprises the following steps: acquiring a multi-source database; performing data preprocessing on the multi-source index database; performing principal component analysis dimension reduction processing on the preprocessed data, and constructing a dimension reduction data set; carrying out clustering analysis on the dimension reduction data set and determining an optimal clustering number; performing mapping association on the clustering result and the sensory evaluation total score, and endowing quality grade meanings; performing multi-round feature screening on machine detection multi-source indexes to obtain an optimal feature set; and constructing and training a machine learning model by taking the optimal feature set as input and the quality grade after clustering mapping as output, and screening an optimal model through multi-dimensional index evaluation to obtain a green pepper shredded potato quality sensory evaluation model. According to the method, by integrating multi-dimensional machine detection indexes such as texture, color, smell and nutrition and combining clustering analysis, a quantitative mapping relation with artificial sensory evaluation is established, and objective, efficient and accurate evaluation of the quality of the shredded potatoes with the green peppers is achieved.

1. The name of the design product: bottle sticker (fresh green pepper sauce). 2. The use of the design product: for bottle stickers. 3. The design points of the design product: the combination of shape and pattern. 4. The picture or photo that best indicates the design points: front view. 5. The design product is a flat product, omitting the left view; the design product is a flat product, omitting the right view; the design product is a flat product, omitting the top view; the design product is a flat product, omitting the bottom view.

The present application relates to a kind of intelligent green pepper picking machine, including walking mechanism, support frame, mechanical joint arm, intelligent identification module, shearing assembly and controller, support frame is rotatably connected on walking mechanism, one end of mechanical joint arm is connected on support frame, shearing assembly is connected at the other end of mechanical joint arm, for picking mature green pepper, intelligent identification module is set on support frame, for identifying green pepper and obtaining mature green pepper position coordinates, controller is electrically connected with intelligent identification module, mechanical joint arm, shearing assembly and walking mechanism, and for according to mature green pepper position coordinates control mechanical joint arm, shearing assembly and walking mechanism collaborative action shearing mature green pepper.The present application is automatically identified and positioned green pepper by intelligent identification module, then by controller cooperates walking mechanism, mechanical joint arm and shearing assembly automatically completes green pepper picking, reduces manual labor intensity.

The application discloses a YOLOv5l green pepper intelligent detection method based on NSGA-II pruning, which comprises the following steps: collecting field green pepper image data; marking green pepper fruits in the image by using LabelIMG; preparing a green pepper dataset and dividing the dataset into a training set and a test set; obtaining a green pepper detection model by adopting a pruning YOLOv5l model method based on NSGA-II; detecting the reliability and accuracy of the pruning YOLOv5l green pepper detection model of NSGA-II in the field, and evaluating the model; if the reliability and accuracy meet the set requirements, the next step is carried out; if the reliability and accuracy do not meet the set requirements, the above steps are re-performed, and the number of green pepper images is increased and the network is modified; and the model is deployed to a green pepper phenotype monitoring and green pepper robot picking production application scene, so that the parameter quantity, model size and GFlops of the green pepper detection model are greatly reduced, and the detection speed is significantly improved.