Inzamam Mashood Nasir¹, Asima Bibi², Jamal Hussain Shah², Muhammad Attique Khan¹, Muhammad Sharif², Khalid Iqbal³, Yunyoung Nam⁴, Seifedine Kadry^5,*

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 >

Zhibin Zhang^1,2,*, Ping Li^1,3, Shuailing Zhao^1,2, Zhimin Lv^1,2, Fang Du^1,2, Yajian An^1,2

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 >

Zongshuai Liu¹, Xuyu Xiang^1,2,*, 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 >

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 >

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 >

Barresi O^1,2, VM Chiocchio^1,2, 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 >

Feng Guo¹, Pingzeng Liu^1,*, 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 >