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  • Open Access


    Blockchain-Based Flexible Double-Chain Architecture and Performance Optimization for Better Sustainability in Agriculture

    Luona Song1, Xiaojuan Wang1,*, Peng Wei1, Zikui Lu1, Xiaojun Wang2, Nicolas Merveille3

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1429-1446, 2021, DOI:10.32604/cmc.2021.016954

    Abstract Blockchain is an emerging decentralized distributed technology that can cross the boundaries and guarantee safe and trustworthy value transfers between participants. Combining the blockchain technology with the Internet of Things (IoT) technology to enhance the transparency and sustainability of agricultural supply chains, has attracted researchers from both academia and industry. This paper reviews the latest applications of the blockchain and IoT technologies in the sustainable agricultural supply chain management and explores the design and implementation of a blockchain-based sustainable solution. By placing the sustainable agricultural supply chain management at its core, a blockchain-based framework is designed. Considering the heterogeneity of… More >

  • Open Access


    Recognition and Classification of Pomegranate Leaves Diseases by Image Processing and Machine Learning Techniques

    Mangena Venu Madhavan1, Dang Ngoc Hoang Thanh2, Aditya Khamparia1,*, Sagar Pande1, Rahul Malik1, Deepak Gupta3

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2939-2955, 2021, DOI:10.32604/cmc.2021.012466

    Abstract Disease recognition in plants is one of the essential problems in agricultural image processing. This article focuses on designing a framework that can recognize and classify diseases on pomegranate plants exactly. The framework utilizes image processing techniques such as image acquisition, image resizing, image enhancement, image segmentation, ROI extraction (region of interest), and feature extraction. An image dataset related to pomegranate leaf disease is utilized to implement the framework, divided into a training set and a test set. In the implementation process, techniques such as image enhancement and image segmentation are primarily used for identifying ROI and features. An image… More >

  • Open Access


    Application of Low Cost Integrated Navigation System in Precision Agriculture

    Qi Wang1,2,3,*, Changsong Yang2,3,5, Yuxiang Wang1,2,3, Shao-en Wu4

    Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1433-1442, 2020, DOI:10.32604/iasc.2020.012759

    Abstract To improve the positioning accuracy of farming vehicle in precision agriculture, an integrated positioning system is proposed based on Global Navigation Satellite System (GNSS)/Strapdown Inertial Navigation System (SINS)/Wireless Sensor Networks (WSN) with low cost and high reliability. The principles of commonly used localization technologies in vehicle positioning are compared and the Received Signal Strength Indication (RSSI) based measurement method is chosen as the integrated positioning system for information fusion considering the complexity of the algorithm, positioning accuracy and hardware requirements in the application scenario. The research of wireless signal propagation loss model of farmland environment was conducted. A set of… More >

  • Open Access


    Deep Learning-Based Classification of Fruit Diseases: An Application for Precision Agriculture

    Inzamam Mashood Nasir1, Asima Bibi2, Jamal Hussain Shah2, Muhammad Attique Khan1, Muhammad Sharif2, Khalid Iqbal3, Yunyoung Nam4, Seifedine Kadry5,*

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1949-1962, 2021, DOI:10.32604/cmc.2020.012945

    Abstract Agriculture is essential for the economy and plant disease must be minimized. Early recognition of problems is important, but the manual inspection is slow, error-prone, and has high manpower and time requirements. Artificial intelligence can be used to extract fruit color, shape, or texture data, thus aiding the detection of infections. Recently, the convolutional neural network (CNN) techniques show a massive success for image classification tasks. CNN extracts more detailed features and can work efficiently with large datasets. In this work, we used a combined deep neural network and contour feature-based approach to classify fruits and their diseases. A fine-tuned,… More >

  • Open Access


    An Adaptive Vision Navigation Algorithm in Agricultural IoT System for Smart Agricultural Robots

    Zhibin Zhang1,2,*, Ping Li1,3, Shuailing Zhao1,2, Zhimin Lv1,2, Fang Du1,2, Yajian An1,2

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 1043-1056, 2021, DOI:10.32604/cmc.2020.012517

    Abstract As the agricultural internet of things (IoT) technology has evolved, smart agricultural robots needs to have both flexibility and adaptability when moving in complex field environments. In this paper, we propose the concept of a vision-based navigation system for the agricultural IoT and a binocular vision navigation algorithm for smart agricultural robots, which can fuse the edge contour and the height information of rows of crop in images to extract the navigation parameters. First, the speeded-up robust feature (SURF) extracting and matching algorithm is used to obtain featuring point pairs from the green crop row images observed by the binocular… More >

  • Open Access


    Image Recognition of Citrus Diseases Based on Deep Learning

    Zongshuai Liu1, Xuyu Xiang1,2,*, Jiaohua Qin1, Yun Tan1, Qin Zhang1, Neal N. Xiong3

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 457-466, 2021, DOI:10.32604/cmc.2020.012165

    Abstract In recent years, with the development of machine learning and deep learning, it is possible to identify and even control crop diseases by using electronic devices instead of manual observation. In this paper, an image recognition method of citrus diseases based on deep learning is proposed. We built a citrus image dataset including six common citrus diseases. The deep learning network is used to train and learn these images, which can effectively identify and classify crop diseases. In the experiment, we use MobileNetV2 model as the primary network and compare it with other network models in the aspect of speed,… More >

  • Open Access


    Dynamic growth of squash (Cucurbita pepo L.) on a substrate based on vermicompost in the greenhouse

    Orozco V JA1, E Galindo P2, MA Segura C1, M Fortis H1, P Preciado R1, P Yescas C1, JA Montemayor T1

    Phyton-International Journal of Experimental Botany, Vol.85, pp. 117-124, 2016, DOI:10.32604/phyton.2016.85.117

    Abstract The aim of this study was to establish the dynamics of growth and allocation of photosynthates in squash (Cucurbita pepo L.) cultivated in a semiarid region under greenhouse conditions and in an organic substrate. Squash seeds were sown in two substrates (one mineral and other organic). The first consisted of a mixture of sand and pumice on a volume basis, while the organic consisted of sand and pumice mixed with vermicompost, both in plastic pots. The substrates were for two treatments [Inorganic (IT) and Organic Treatment (OT)] with sixteen repetitions on a completely randomized design. After emergence, plants were fertilized… More >

  • Open Access


    Impacts of sewage irrigation on soil properties of a farmland in China: A review

    Li QK1, J Tang2, T Wang3, D Wu2, CA Busso4, RF Jiao2, XJ Ren2

    Phyton-International Journal of Experimental Botany, Vol.87, pp. 40-50, 2018, DOI:10.32604/phyton.2018.87.040

    Abstract Fresh water is a valuable nonrenewable resource and plays an important role in maintaining economic and social development. Considering its large population and consumption potential, water resource deficits will certainly not allow a sustainable development of basic industries in China in the near future. Application of sewage irrigation, to some extent, was regarded as an alternative way to solve the problem of agricultural water shortage in some areas (such as North China). However, accompanied with an extensive implementation of sewage irrigation, some problems with sewage irrigation became gradually obvious in agriculture, especially those related with pollution and destruction of farmlands.… More >

  • Open Access


    Changes in soil phosphorus fractions caused by cropping without nutrient reposition. A case study

    Barresi O1,2, VM Chiocchio1,2, RS Lavado2

    Phyton-International Journal of Experimental Botany, Vol.87, pp. 14-17, 2018, DOI:10.32604/phyton.2018.87.014

    Abstract Previous studies in soils of the Pampas region indicate the prevalence of calcium phosphates within the very complex mix of phosphorus (P) compounds in the soils. We studied the changes in P fractions in a punctual situation in the Pampas region. The sampling was carried out in a farm located near the city of Junín (-34.585; -60.9589) and the soil was Junín series Typic Hapludoll. The farm was devoted to grazing and sporadic crops, but from the last 30 years changed to continuous agriculture. At no time fertilization matched nutrients removal by crops. The soil P fractions were determined using… More >

  • Open Access


    Research on the Relationship Between Garlic and Young Garlic Shoot Based on Big Data

    Feng Guo1, Pingzeng Liu1,*, Wanming Ren2, Ning Cao3, Chao Zhang1, Fujiang Wen1, Helen Min Zhou4

    CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 363-378, 2019, DOI:10.32604/cmc.2019.03794

    Abstract In view of the problems such as frequent fluctuation of garlic price, lack of efficient forecasting means and difficulty in realizing the steady development of garlic industry, combined with the current situation of garlic industry and the collected data information. Taking Big Data platform of garlic industry chain as the core, using the methods of correlation analysis, smoothness test, co-integration test, and Granger causality test, this paper analyzes the correlation, dynamic, and causality between garlic price and young garlic shoot price. According to the current situation of garlic industry, the garlic industry service based on Big Data is put forward.… More >

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