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Journal articles on the topic 'Intelligenza vegetale'

Author: Grafiati

Published: 10 March 2023

Last updated: 29 July 2025

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1

Bonato, Bianca, and Umberto Castiello. "Le piante: vita intelligente dei nostri paesaggi." Ri-Vista. Research for landscape architecture 21, no. 2 (2024): 38–51. http://dx.doi.org/10.36253/rv-15752.

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In questo saggio approfondiremo il comportamento di uno dei principali elementi che caratterizza i nostri paesaggi: le piante. La comprensione di un paesaggio non può esimersi da una profonda conoscenza del mondo vegetale e dalle dinamiche che intercorrono tra le comunità di piante che lo compongono. Lo scopo è di andare oltre la visione del verde come mero sfondo e linguaggio compositivo per considerarlo, più propriamente, come il principale attore del paesaggio, con i suoi bisogni, le sue peculiarità e la sua… intelligenza. Dopo un breve excursus sulle straordinarie abilità cognitive delle p

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Yang, Linlin, Yingluo Song, Zilin Hu, Aili Wang, Haibin Wu, and Yuji Iwahori. "Design and Implementation of Intelligent Vegetable Recognition System based on MobileNet." Embedded Selforganising Systems 9, no. 3 (2022): 82–86. http://dx.doi.org/10.14464/ess.v9i3.579.

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With the rise of food safety traceability, unmanned supermarkets and autonomous shopping, the automatic identification technology of agricultural products such as vegetables in circulation and sales has become an urgent problem. This paper designs an intelligent vegetable identification system based on MobileNet to solve intelligent identification problem of vegetable sales in supermarkets. The system includes main control core, visual processing module, pressure sensor, voice broadcasting module and display module. When the system detects that there are vegetables to be weighed, the vis

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3

Jiao, Jinkang, Ying Zang, and Chaowen Chen. "Key Technologies of Intelligent Weeding for Vegetables: A Review." Agriculture 14, no. 8 (2024): 1378. http://dx.doi.org/10.3390/agriculture14081378.

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Vegetables are an essential part of people’s daily diet, and weeds can cause serious losses in vegetable yield and quality. Intelligent weeding technology for vegetables will be one of the mainstream technologies in modern agricultural development. This article reviews the current research status of intelligent weeding technology for vegetables, including vegetable and weed detection technology, weeding actuators, and weeding robots. Firstly, the vegetable and weed detection technology was introduced in detail from three aspects: global weed detection, crop-rows detection, and vegetable/weed p

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Liang, Di, Zhongming Lin, Xiangyun Su, et al. "Intelligent Planting of Subtropical Fruits and Vegetables based on Artificial Intelligence." Frontiers in Computing and Intelligent Systems 9, no. 1 (2024): 70–74. http://dx.doi.org/10.54097/m2a57h62.

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This thesis discusses the intelligent planting system of subtropical fruits and vegetables based on artificial intelligence (AI) and visual recognition, especially the application in water and fertilizer management. In view of the problems of inaccurate and inefficient water and fertilizer management faced by fruit and vegetable planting in subtropical areas, this study implements an intelligent water and fertilizer decision support system, which integrates visual recognition, sensor data acquisition, machine learning algorithms and other technologies. Through visual recognition technology, th

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Tapia-Mendez, Enoc, Irving A. Cruz-Albarran, Saul Tovar-Arriaga, and Luis A. Morales-Hernandez. "Deep Learning-Based Method for Classification and Ripeness Assessment of Fruits and Vegetables." Applied Sciences 13, no. 22 (2023): 12504. http://dx.doi.org/10.3390/app132212504.

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Food waste is a global concern and is the focus of this research. Currently, no method in the state of the art classifies multiple fruits and vegetables and their level of ripening. The objective of the study is to design and develop an intelligent system based on deep learning techniques to classify between types of fruits and vegetables, and also to evaluate the level of ripeness of some of them. The system consists of two models using the MobileNet V2 architecture. One algorithm is for the classification of 32 classes of fruits and vegetables, and another is for the determination of the rip

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Zheng, Bowen, Guiling Sun, Zhaonan Meng, and Ruili Nan. "Vegetable Size Measurement Based on Stereo Camera and Keypoints Detection." Sensors 22, no. 4 (2022): 1617. http://dx.doi.org/10.3390/s22041617.

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This work focuses on the problem of non-contact measurement for vegetables in agricultural automation. The application of computer vision in assisted agricultural production significantly improves work efficiency due to the rapid development of information technology and artificial intelligence. Based on object detection and stereo cameras, this paper proposes an intelligent method for vegetable recognition and size estimation. The method obtains colorful images and depth maps with a binocular stereo camera. Then detection networks classify four kinds of common vegetables (cucumber, eggplant,

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Van Volkenburgh, Elizabeth. "Brilliant Green: The Surprising History and Science of Plant Intelligence. By Stefano Mancuso and Alessandra Viola; Foreword by Michael Pollan; translated by Joan Benham. Washington (DC): Island Press. $20.00. xiii + 173 p.; ill.; no index. ISBN: 978-1-61091-603-5. [Original title: Verde brillante: Sensibilità e intelligenza del mondo vegetale, 2013.] 2015." Quarterly Review of Biology 91, no. 1 (2016): 100–101. http://dx.doi.org/10.1086/685354.

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8

Guan, Xianping, Longyuan Shi, Hongrui Ge, Yuhan Ding, and Shicheng Nie. "Development, Design, and Improvement of an Intelligent Harvesting System for Aquatic Vegetable Brasenia schreberi." Agronomy 15, no. 6 (2025): 1451. https://doi.org/10.3390/agronomy15061451.

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At present, there is a lack of effective and usable machinery in the harvesting of aquatic vegetables. The harvesting of most aquatic vegetables such as Brasenia schreberi relies entirely on manual labor, resulting in a high labor demand and labor shortages, which restricts the industrial development of aquatic vegetables. To address this problem, an intelligent harvesting system for the aquatic vegetable Brasenia schreberi was developed in response to the challenging working conditions associated with harvesting it. The system is composed of a catamaran mobile platform, a picking device, and

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Bai, Lin, Minghao Liu, and Ying Sun. "Overview of Food Preservation and Traceability Technology in the Smart Cold Chain System." Foods 12, no. 15 (2023): 2881. http://dx.doi.org/10.3390/foods12152881.

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According to estimates by the Food and Agriculture Organization of the United Nations (FAO), about a third of all food produced for human consumption in the world is lost or wasted—approximately 1.3 billion tons. Among this, the amount lost during the storage stage is about 15–20% for vegetables and 10–15% for fruits. It is 5–10% for vegetables and fruits during the distribution stage, resulting in a large amount of resource waste and economic losses. At the same time, the global population affected by hunger has reached 828 million, exceeding one-tenth of the total global population. The impr

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10

Wang, Zhi Gang, Xiao Guang Chen, and Wen Fu Wu. "Artificial Intelligence for the Control of Northeast Region Greenhouse Base on Biomass." Applied Mechanics and Materials 48-49 (February 2011): 270–73. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.270.

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Greenhouse is used to produce vegetables in winter, the parameter of environment which suit vegetables grow is a complex and ill-defined problem. Furthermore, burning coal to heat greenhouse is expensive than carry vegetables from south region enormously, so at northeast, most greenhouse cannot produce. On the other hand, there are more than several hundred million ton biomass be burned in field. Not only waste natural resources greatly, but also caused pollution seriously. This paper presents an artificial intelligence control system of northeast region greenhouse base on biomass, peasants ca

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11

Tata, Jagannadha Swamy, Naga Karthik Varma Kalidindi, Hitesh Katherapaka, Sharath Kumar Julakal, and Mohan Banothu. "Real-Time Quality Assurance of Fruits and Vegetables with Artificial Intelligence." Journal of Physics: Conference Series 2325, no. 1 (2022): 012055. http://dx.doi.org/10.1088/1742-6596/2325/1/012055.

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Abstract Vegetables and fruits make up a major part of the human diet and finding a good grade of its quality is now a major issue in the market. To find a grade of the vegetable or fruit will be based on some parameters like size, shape, appearance, etc. The appearance is now a deciding factor for the market and affects the consumer’s choice. So, we have designed an application that will classify fruits and grade them according to their quality with appearance as a parameter. This paper will describe the process which is involved in the application. This proposed system will use image process

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Behera, TK, Jyoti Devi, JK Tiwari, and BK Singh. "Vegetable Breeding: Status and Strategies." Vegetable Science 50, Special (2023): 131–45. http://dx.doi.org/10.61180/vegsci.2023.v50.spl.01.

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Vegetable crops are a crucial component of the global food supply chain, with a vast range of variety, flavor profiles, and nutritional value, making them a staple meal of many cultures globally. India is the second-largest producer of vegetables in the world, commercially growing over 60 different types of vegetables for fresh consumption. Breeding vegetables is a challenging and complex process due to location-specific demand for color, shape, nutrition, taste, harvest stage of product, quality issues, and demand for year-round supply of fresh product. A combination of specialized knowledge,

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13

Nie, Wenjing, and Dan Wen. "Study on the Applications and Regulatory Mechanisms of Grafting on Vegetables." Plants 12, no. 15 (2023): 2822. http://dx.doi.org/10.3390/plants12152822.

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Grafting can overcome problems with soil sensitivity, enhance plant stress tolerance, improve product quality, and increase crop yield and value. This paper reviews the various mechanisms of vegetable grafting, the graft survival process and its influencing factors, the practical applications of grafting, and the molecular regulation of grafting in vegetables. The importance of germplasm and rootstock interactions, the mechanization of vegetable grafting, and future aspects, including intelligence and digitalization, are discussed.

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14

Wang, Shouwei, Lijian Yao, Lijun Xu, Dong Hu, Jiawei Zhou, and Yexin Chen. "An Improved YOLOv7-Tiny Method for the Segmentation of Images of Vegetable Fields." Agriculture 14, no. 6 (2024): 856. http://dx.doi.org/10.3390/agriculture14060856.

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In response to the limitations of existing methods in differentiating between vegetables and all types of weeds in farmlands, a new image segmentation method is proposed based on the improved YOLOv7-tiny. Building on the original YOLOv7-tiny framework, we replace the CIoU loss function with the WIoU loss function, substitute the Leaky ReLU loss function with the SiLU activation function, introduce the SimAM attention mechanism in the neck network, and integrate the PConv convolution module into the backbone network. The improved YOLOv7-tiny is used for vegetable target detection, while the ExG

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15

Li, Shuo, Yichen Zhang, and Shijie Liu. "Design and Research of a New Type of Compound Automatic Cleaning Equipment for Vegetables." Journal of Engineering System 1, no. 2 (2023): 31–35. http://dx.doi.org/10.62517/jes.202302206.

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In order to adapt to different types of vegetable cleaning, improve the quality of cleaning work, this paper designs a home or small restaurant to use a new complex automatic cleaning equipment for vegetables. The equipment adopts the innovative structure of“Pipeline single-cavity multi-mode”. The whole equipment adopts assembly line layout, which is convenient for structural layout and makes cleaning work in order. The cleaning chamber integrates various functions, and different types of vegetables are cleaned in a single multi-function cleaning chamber, so that the volume of the equipment is

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16

K., Veerasamy, and E. J. Thomson Fredrik. "Intelligence System towards Identify Weeds in Crops and Vegetables Plantation Using Image Processing and Deep Learning Techniques." Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications 14, no. 4 (2023): 45–59. http://dx.doi.org/10.58346/jowua.2023.i4.004.

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Due to uneven spacing of the plants, identification of weeds and bushes in crops and vegetables plantations is more difficult than identification of weeds and bushes in crops. There has not been much research done on weed identification in vegetable plantations thus far. Although there is a wide variety of plant species, the traditional crop weed detection techniques are used to directly identify weeds. This research introduces a novel approach that combines image processing and deep learning techniques. Instead of directly tackling weed detection, the proposed method focuses on identifying ve

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17

ANUSHA, V. V. S. S., and S. R. PADMA. "RELATIONSHIP ANALYSIS BETWEEN MARKETING BEHAVIOUR AND PROFILE OF VEGETABLE GROWERS OF RANGA REDDY DISTRICT." JOURNAL OF RESEARCH ANGRAU 50, no. 4 (2022): 124–34. http://dx.doi.org/10.58537/jorangrau.2022.50.4.13.

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Ranga Reddy district of Telangana state tops in area and production of vegetables and was selected to study the marketing behaviour in year 2021. The profile variables were finalized after the judge’s opinion with the dependent variable was drafted as the interview schedule to collect responses from 150 farmers. The results displayed half of the respondents were middleaged, mostly (30.67%) with high school education taking up only agriculture (50.67%) as the occupation. The respondents (68.67%) were having medium experience in vegetable production with 84.67 per cent of them allocated a medium

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18

Dominic Mario, Onyeachonam, and Ujerekre Ekoko. "Leaf Disease Classification for Vegetable Farming using Artificial Intelligence." International Journal of Science and Research (IJSR) 13, no. 6 (2024): 269–73. http://dx.doi.org/10.21275/sr24601192902.

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19

Xu, Lijuan, Heng Zhuang, Langqing Li, Jifei Hu, and Xuelian Liao. "Research on the Construction of Intelligent Cold Chain Logistics System for Prepared Dishes Based on AI Technology." Industry Science and Engineering 1, no. 3 (2024): 36–40. http://dx.doi.org/10.62381/i245306.

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China's prepared vegetable industry has achieved certain development, and the prepared vegetable market is huge and the market space is large, but it still faces some challenges and problems. The food quality of prepared dishes needs to be guaranteed by high-quality cold chain logistics. However, the development level of cold chain logistics in China is relatively insufficient, and the corresponding development level of cold chain logistics of prepared dishes is of low quality, which restricts the development of prepared dishes industry to a certain extent. With the development of artificial i

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20

Liu, Jun. "Tomato Yield Estimation Based on Object Detection." Journal of Advanced Computational Intelligence and Intelligent Informatics 22, no. 7 (2018): 1120–25. http://dx.doi.org/10.20965/jaciii.2018.p1120.

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At present, the vegetable yield estimation in China is performed by manual sampling and visual observation of vegetable counts. This is not only time-consuming and labor-intensive, but it also has low precision. In this study, we capture video surveillance images of the tomatoes during plant maturation, and use neural networks to identify pictures, extract growing features, identify the number of vegetables hanging from the plants, and establish an estimation model for tomato yield. We then take a sample of the vegetables to be measured. Strains are image-analyzed and processed to predict yiel

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Changdar, Chiranjit, Pravash Kumar Giri, Rajat Kumar Pal, et al. "Solving a Mathematical Model for Small Vegetable Sellers in India by a Stochastic Knapsack Problem: An Advanced Genetic Algorithm Based Approach." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 30, no. 05 (2022): 897–921. http://dx.doi.org/10.1142/s0218488522500271.

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In this paper, we have proposed a stochastic Knapsack Problem (KP) based mathematical model for small-scale vegetable sellers in India and solved it by an advanced Genetic Algorithm. The knapsack problem considered here is a bounded one, where vegetables are the objects. In this model, we have assumed that different available vegetables (objects) have different weights (that are available), purchase costs, and profits. The maximum weight of vegetables that can be transported by a seller is limited by the carrying capacity of the vegetable carrier and the business capital of the seller is also

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Du, Liuzi, Xiaowei Huang, Zhihua Li, et al. "Application of Smart Packaging in Fruit and Vegetable Preservation: A Review." Foods 14, no. 3 (2025): 447. https://doi.org/10.3390/foods14030447.

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The application of smart packaging technology in fruit and vegetable preservation has shown significant potential with the ongoing advancement of science and technology. Smart packaging leverages advanced sensors, smart materials, and Internet of Things (IoT) technologies to monitor and regulate the storage environment of fruits and vegetables in real time. This approach effectively extends shelf life, enhances food safety, and reduces food waste. The principle behind smart packaging involves real-time monitoring of environmental factors, such as temperature, humidity, and gas concentrations,

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Fedosov, A. Yu, and A. M. Menshikh. "Precision farming technologies in vegetable growing." Vegetable crops of Russia, no. 6 (December 7, 2022): 40–45. http://dx.doi.org/10.18619/2072-9146-2022-6-40-45.

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Precision farming technologies can help mitigate the environmental impact of agriculture by reducing the use of fertilizers and irrigation while reducing costs. Vegetable precision farming technology uses geographic positioning system (GPS), geographic information system (GIS), artificial intelligence (IoT), robotics, sensor technology, data-based genome editing, etc. to improve the production and quality of vegetables. Digital genome sequencing, developed over the past decade, has greatly reduced the cost and time required to map the DNA of plants and other organisms. Digital genome sequencin

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Dou, Dandan. "Sensor Vegetable Greenhouse and Agricultural Product Supply Chain Management Based on Improved Neural Network." Mobile Information Systems 2022 (August 18, 2022): 1–9. http://dx.doi.org/10.1155/2022/4139784.

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In recent years, people have begun to collect environmental data in vegetable greenhouses. Therefore, this article studies the current internal control technology of vegetable greenhouses, and improves the sensor application in vegetable greenhouses, in a targeted manner by combining with the improved neural network algorithm. The model has more accurate prediction accuracy than traditional BP. By using the Android client and ZigBee artificial intelligence control technology it creates the most suitable living conditions for the vegetables, fruits, and other crops in the vegetable greenhouse b

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Tan, Yarong, Xin Liu, Jinmeng Zhang, Yigang Wang, and Yanxiang Hu. "A Review of Research on Fruit and Vegetable Picking Robots Based on Deep Learning." Sensors 25, no. 12 (2025): 3677. https://doi.org/10.3390/s25123677.

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Fruit and vegetable picking robots are considered an important way to promote agricultural modernization due to their high efficiency, precision, and intelligence. However, most of the existing research has sporadically involved single application areas, such as object detection, classification, and path planning, and has not yet comprehensively sorted out the core applications of deep learning technology in fruit and vegetable picking robots, the current technological bottlenecks faced, and future development directions. This review summarizes the key technologies and applications of deep lea

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Xu, Lijuan, Heng Zhuang, Huameng Min, Jia Song, and Huilin Huang. "Review on the Application of Intelligent Logistics Technology in Cold Chain Logistics." Journal of Big Data and Computing 2, no. 3 (2024): 6–10. https://doi.org/10.62517/jbdc.202401302.

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The development of intelligent logistics technology has greatly promoted the development of intelligent logistics. The special environmental requirements of cold chain logistics make smart logistics technology play a huge role in the field of cold chain logistics. Starting from the construction of cold chain logistics system, this paper reviews the relevant literature on the application of smart logistics technology, including artificial intelligence technology, RFID technology and Internet of Things technology, in the field of cold chain logistics, and summarizes the application research of s

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Dubey, Shiv Ram, and Anand Singh Jalal. "Application of Image Processing in Fruit and Vegetable Analysis: A Review." Journal of Intelligent Systems 24, no. 4 (2015): 405–24. http://dx.doi.org/10.1515/jisys-2014-0079.

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AbstractImages are an important source of data and information in the agricultural sciences. The use of image-processing techniques has outstanding implications for the analysis of agricultural operations. Fruit and vegetable classification is one of the major applications that can be utilized in supermarkets to automatically detect the kinds of fruits or vegetables purchased by customers and to determine the appropriate price for the produce. Training on-site is the underlying prerequisite for this type of arrangement, which is generally caused by the users having little or no expert knowledg

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Hou, Guangyu, Haihua Chen, Mingkun Jiang, and Runxin Niu. "An Overview of the Application of Machine Vision in Recognition and Localization of Fruit and Vegetable Harvesting Robots." Agriculture 13, no. 9 (2023): 1814. http://dx.doi.org/10.3390/agriculture13091814.

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Intelligent agriculture imposes higher requirements on the recognition and localization of fruit and vegetable picking robots. Due to its unique visual information and relatively low hardware cost, machine vision is widely applied in the recognition and localization of fruit and vegetable picking robots. This article provides an overview of the application of machine vision in the recognition and localization of fruit and vegetable picking robots. Firstly, the advantages, disadvantages, and the roles of different visual sensors and machine vision algorithms in the recognition and localization

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Sarma, Dhrubajit, and D. C. Kalita. "Constraint Analysis of Vegetable Production and Marketing in Darrang and Barpeta Districts of Assam, India." Environment and Ecology 43, no. 2 (2025): 542–46. https://doi.org/10.60151/envec/ubbc7584.

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India is the second largest vegetables producer in worls with production of 200.445 million tonnes during 2020-21. Assam is in the 11th position among all states of India in vegetable production. Production and marketing of vegetables faces various obstacles due to their seasonality, various factors of production, high degree of perishability. Major parts of production are sold by the farmers to middlemen or commission agents, who dominate the trade and earn huge profits. A large nos. of people in Assam are associated with vegetable farming as well as with trading and their lives and livelihoo

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Huang, Yi, Junze Xu, and Yida An. "Intelligent integrated multifunctional vegetable cutter system." Journal of Physics: Conference Series 1865, no. 3 (2021): 032073. http://dx.doi.org/10.1088/1742-6596/1865/3/032073.

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Xuehan, Gao, Xu Jianjun, and Yan Limei. "Vegetable Greenhouses Intelligent Temperature Control System." Advance Journal of Food Science and Technology 10, no. 1 (2016): 43–48. http://dx.doi.org/10.19026/ajfst.10.1750.

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Han, Chongyang, Jinhong Lv, Chengju Dong, et al. "Classification, Advanced Technologies, and Typical Applications of End-Effector for Fruit and Vegetable Picking Robots." Agriculture 14, no. 8 (2024): 1310. http://dx.doi.org/10.3390/agriculture14081310.

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Fruit- and vegetable-harvesting robots are a great addition to Agriculture 4.0 since they are gradually replacing human labor in challenging activities. In order to achieve the harvesting process accurately and efficiently, the picking robot’s end-effector should be the first part to come into close contact with the crops. The design and performance requirements of the end-effectors are affected by the fruit and vegetable variety as well as the complexity of unstructured surroundings. This paper summarizes the latest research status of end-effectors for fruit- and vegetable-picking robots. It

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Kalyan, Kumar Jena, and Prasad K. Krishna. "A Machine Intelligent Based Approach for the Classification and Analysis of Tomato Leaf Disease Images." International Journal of Health Sciences and Pharmacy (IJHSP) 6, no. 2 (2022): 1–19. https://doi.org/10.5281/zenodo.7051022.

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<strong>Purpose: </strong><em>Vegetable production plays a vital role for the existence of human society. It is very much essential for the proper care of vegetable plants for better production of vegetables. However, vegetable plant leaf disease is a major concern in the current scenario. Tomato leaf disease is one of them. So, preventive measures should be taken to avoid the rise of tomatoes and other leaf diseases at the earliest for better production of vegetables.   </em> <strong>Approach: </strong><em>In this work, a machine intelligent (MI) based approach is proposed for the c

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Dziallas, Kristina. "Gender stereotyping." Metaphor and the Social World 9, no. 2 (2019): 199–220. http://dx.doi.org/10.1075/msw.18007.dzi.

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Abstract Across languages, the head and sexualized body parts (i.e., vagina, breasts, penis, testicles) are conceptualized in a number of ways, for example as fruits and vegetables: heads are conceptualized as cabbages, vaginas as figs, breasts as melons, penises as carrots, and testicles as olives, to only name a few. The present study draws on the theories of conceptual metaphor and metonymy by Lakoff & Johnson (1980) to analyze the conceptualizations of the five body parts as fruits and vegetables in English, Spanish and French. For this purpose, a slang dictionary-based database of 184

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V., M. Chaudhari1* D. C. Barot1 and N. K. Patel2. "Robotic Technologies: Tools for advance vegetable productions." Science World a monthly e magazine 3, no. 8 (2023): 1996–2000. https://doi.org/10.5281/zenodo.8253248.

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Robotic technology has revolutionized various industries, and the field of vegetable production is no exception. With the increasing demand for fresh and high-quality vegetables, farmers are turning to robots to improve efficiency and productivity in their operations. One of the main advantages of using robotic technology in vegetable production is the ability to automate tedious and repetitive tasks. Robots can be programmed to perform activities such as planting, watering, and harvesting, reducing the need for manual labor. This not only saves time but also minimizes the risk of human error,

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Wang, Gao, Shuang Xu, Zixu Chen, and Youzhu Li. "A Hybrid Model Integrating Variational Mode Decomposition and Intelligent Optimization for Vegetable Price Prediction." Agriculture 15, no. 9 (2025): 919. https://doi.org/10.3390/agriculture15090919.

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In recent years, China’s vegetable market has faced frequent and drastic price fluctuations due to factors such as supply–demand relationships and climate change, which significantly affect government bodies, farmers, consumers, and other participants in the vegetable industry and supply chain. Traditional forecasting methods demonstrate evident limitations in capturing the nonlinear characteristics and complex volatility patterns of price series, underscoring the necessity of developing high-precision prediction models. This study proposes a hybrid forecasting model integrating variational mo

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Li, Xiao Di, Wei Ping Hu, and Xiao Ping Yang. "Thinking on the Water System Design Method of Intelligent Civil Ecological Agriculture Residential Buildings." Applied Mechanics and Materials 357-360 (August 2013): 487–91. http://dx.doi.org/10.4028/www.scientific.net/amm.357-360.487.

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The intelligent civil ecological agriculture residential building is the authors creative idea. The design of its water system, as one of the important contents, means providing water according to the demand of the vegetables and flowers growth intelligently, instead of watering by labors. In this way, humans planting experience and intelligence will be endowed with building facilities, thus constructing a small automatic family farming system with the symbiosis of man, machine and plant. Based on new achievements of modern science and technology, a reasonable energy-conservative and artistic

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Cheng, Chen, Liping Feng, Chaoyang Dong, et al. "Vegetable Commodity Organ Quality Formation Simulation Model (VQSM) in Solar Greenhouses." Agriculture 14, no. 9 (2024): 1531. http://dx.doi.org/10.3390/agriculture14091531.

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Cucumber (Cucumis sativus L.) and celery (Apium graveolens L.) are among the most widely cultivated vegetable crops, belonging to the melon and leafy vegetable categories, respectively. This study aims to provide predictions for the quality formation of greenhouse cucumber and celery, as well as technical support for intelligent vegetable production management. Based on the light and temperature response characteristics of cucumber and celery growth and development and using the experimental varieties ‘Jinsheng 206’ for cucumber and ‘Juventus’ for celery, the observational data from a five-cro

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Farooq, Omer, and Jasmeen Gill. "Vegetable Grading and Sorting using Artificial Intelligence." International Journal for Research in Applied Science and Engineering Technology 10, no. 3 (2022): 13–21. http://dx.doi.org/10.22214/ijraset.2022.40407.

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Abstract: Agriculture and food industry are the backbone of any country. Food industry is the prime contributor in agricultural sector. Thus, automation of vegetable grading and sorting is the need of the hour. Since, artificial neural networks are best suited for automated pattern recognition problems; they are used as a classification tool for this research. Back propagation is the most important algorithm for training neural networks. But, it easily gets trapped in local minima leading to inaccurate solutions. Therefore, some global search and optimization techniques were required to hybrid

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MENSHIKH, A. M., A. YU FEDOSOV, V. A. YANCHENKO, V. A. FARTUKOV, and M. I. IVANOVA. "INTELLIGENT IRRIGATION SYSTEM: DIGITAL SOLUTIONS IN VEGETABLE GROWING." Rice Growing 63, no. 2 (2024): 76–84. http://dx.doi.org/10.33775/1684-2464-2024-63-2-76-84.

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Volison-Klimentiev, Anastasiya, Lucas Cullari, Gal Shachar-Michaely, et al. "Vegetable-Oil-Based Intelligent Ink for Oxygen Sensing." ACS Sensors 5, no. 10 (2020): 3274–80. http://dx.doi.org/10.1021/acssensors.0c01777.

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Pereira, Maria Luiza Andrade, and Célia Regina Simonetti Barbalho. "Prospecção Tecnológica da Copaíba como Insumo Vegetal: explorando aplicações específicas nas indústrias de alimentos, cosméticos e farmacêutica." Cadernos de Prospecção 17, no. 3 (2024): 946–61. http://dx.doi.org/10.9771/cp.v17i3.59331.

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Este artigo aborda a importância da prospecção tecnológica para a inovação. Destaca-se que as atividades econômicas recentes aceleraram a extinção de espécies e de ecossistemas, resultando em perdas significativas de biodiversidade com impactos econômicos e sociais a longo prazo. A pesquisa utilizou estudos prospectivos para analisar o desenvolvimento científico e tecnológico de insumos vegetais, especialmente considerando a biodiversidade brasileira como fonte crucial de ativos biológicos. Metodologicamente, a busca de dados de patentes foi realizada utilizando a plataforma Orbit Intelligence

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Akhter, Afroza, Ambreen Nabi, Sumati Narayan, et al. "Digital Technology: A Game Changer in Vegetable Cultivation." Annual Research & Review in Biology 39, no. 2 (2024): 30–52. http://dx.doi.org/10.9734/arrb/2024/v39i230631.

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Vegetables are important constituents of Indian agriculture and nutritional security due to their short duration, high yielding capacity, nutritional richness, economic viability and ability to generate on farm and off farm employment. Increasing per capita income, health consciousness, urbanisation, increasing working women, shifting of farmers to high value vegetables are also important ingredients for fuelling vegetable growth in India. But we are still not getting the required /capita vegetables/day.so the answer to increasing the production of various vegetables employing various digital

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Kargin, Vitaliy, Rostislav Kravchenko, Dmitriy Sokhinov, and Konstantin Usanov. "THE SYSTEM OF INTELLIGENT FRUIT QUALITY CONTROL IN INDUSTRIAL FRUIT AND VEGETABLE PRODUCTION." Elektrotekhnologii i elektrooborudovanie v APK 72, no. 1 (2025): 90–96. https://doi.org/10.22314/2658-4859-2025-72-1-90-96.

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Industrial cultivation of fruit and vegetable products in open or protected ground is an integral strategy in achieving a multiple increase in production volumes and ensuring the country’s food security. The distribution of industrial volumes of harvested crops by commodity varieties and the gradation of fruits according to established quality indicators, including the maturity, is impossible without replacing the traditional visual assessment of this indicator with modern digital intelligent systems that reduce costs and increase production efficiency. (Research purpose) The research purpose

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Mortazavi, Alireza, Helia Yarbaksh, Batool Faegheh Bahaaddini Baigy Zarandi, et al. "Cultivation of Vitamin C-Rich Vegetables for Space-Radiation Mitigation." Radiation 4, no. 1 (2024): 101–14. http://dx.doi.org/10.3390/radiation4010008.

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Space exploration introduces astronauts to challenges, such as space radiation and microgravity. Researchers have investigated vitamin C as a potential radiation mitigator, as well as antioxidants for sustaining astronaut health. Our own studies demonstrate vitamin C’s life-saving radioprotective effects and its potential as a radiation mitigator, thus highlighting promise, even when administered 24 h post-exposure. This is particularly relevant in scenarios where astronauts may be exposed to sudden large solar particle events, potentially resulting in lethal doses of space radiation. The succ

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Zargham, Abdullah, Ihtisham Ul Haq, Tamara Alshloul, et al. "Revolutionizing Small-Scale Retail: Introducing an Intelligent IoT-based Scale for Efficient Fruits and Vegetables Shops." Applied Sciences 13, no. 14 (2023): 8092. http://dx.doi.org/10.3390/app13148092.

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In the bustling streets of Pakistan, small-scale fruits and vegetables shops stand as vital hubs of daily life. These humble establishments are where people flock to satisfy their everyday needs. However, the traditional methods employed by shopkeepers using manual weighing scales have proven to be time-consuming and limit the shopkeepers’ ability to serve multiple customers simultaneously. But in a world rapidly embracing automation and propelled by the wonders of artificial intelligence, a revolution is underway. In this visionary paper, we introduce the concept of an intelligent scale that

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Burak, L. Ch. "Modern methods of blanching and their influence on the process of drying fruits and vegetables." Vestnik MGTU 28, no. 2 (2025): 273–95. https://doi.org/10.21443/1560-9278-2025-28-2-273-295.

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Traditional methods of drying fruits and vegetables are effective ways to preserve and increase the shelf life of fruit and vegetable raw materials. However, the drying process often leads to undesirable changes in the physicochemical, organoleptic properties and nutritional value of dried products. Blanching as a method of preliminary preparation of fruit and vegetable raw materials before drying has a significant impact on both the drying process and the quality of the finished product. The purpose of this study is to analyze modern blanching methods, the effectiveness of their impact on the

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Gong, Chengsheng, and Weiping Diao. "Artificial intelligence in vegetable crops: recent advances and prospects." Vegetable Research 5, no. 1 (2025): 0. https://doi.org/10.48130/vegres-0025-0012.

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Li, Dawei, Lin Bai, Rong Wang, and Sun Ying. "Research Progress of Machine Learning in Extending and Regulating the Shelf Life of Fruits and Vegetables." Foods 13, no. 19 (2024): 3025. http://dx.doi.org/10.3390/foods13193025.

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Fruits and vegetables are valued for their flavor and high nutritional content, but their perishability and seasonality present challenges for storage and marketing. To address these, it is essential to accurately monitor their quality and predict shelf life. Unlike traditional methods, machine learning efficiently handles large datasets, identifies complex patterns, and builds predictive models to estimate food shelf life. These models can be continuously refined with new data, improving accuracy and robustness over time. This article discusses key machine learning methods for predicting shel

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Chen, Chaowen, Ying Zang, Jinkang Jiao, et al. "An Efficient Group Convolution and Feature Fusion Method for Weed Detection." Agriculture 15, no. 1 (2024): 37. https://doi.org/10.3390/agriculture15010037.

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Weed detection is a crucial step in achieving intelligent weeding for vegetables. Currently, research on vegetable weed detection technology is relatively limited, and existing detection methods still face challenges due to complex natural conditions, resulting in low detection accuracy and efficiency. This paper proposes the YOLOv8-EGC-Fusion (YEF) model, an enhancement based on the YOLOv8 model, to address these challenges. This model introduces plug-and-play modules: (1) The Efficient Group Convolution (EGC) module leverages convolution kernels of various sizes combined with group convoluti

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