Sana Parez¹, Naqqash Dilshad², Turki M. Alanazi³, Jong Weon Lee^1,*

Computer Systems Science and Engineering, Vol.47, No.1, pp. 515-536, 2023, DOI:10.32604/csse.2023.037992

Abstract A country’s economy heavily depends on agricultural development. However, due to several plant diseases, crop growth rate and quality are highly suffered. Accurate identification of these diseases via a manual procedure is very challenging and time-consuming because of the deficiency of domain experts and low-contrast information. Therefore, the agricultural management system is searching for an automatic early disease detection technique. To this end, an efficient and lightweight Deep Learning (DL)-based framework (E-GreenNet) is proposed to overcome these problems and precisely classify the various diseases. In the end-to-end architecture, a MobileNetV3Small model is utilized as a backbone that generates refined, discriminative,… More >

Sultan Alahmari¹, Saud Yonbawi², Suneetha Racharla³, E. Laxmi Lydia⁴, Mohamad Khairi Ishak⁵, Hend Khalid Alkahtani^6,*, Ayman Aljarbouh⁷, Samih M. Mostafa⁸

Computer Systems Science and Engineering, Vol.47, No.1, pp. 375-391, 2023, DOI:10.32604/csse.2023.036362

Abstract Hyperspectral imaging instruments could capture detailed spatial information and rich spectral signs of observed scenes. Much spatial information and spectral signatures of hyperspectral images (HSIs) present greater potential for detecting and classifying fine crops. The accurate classification of crop kinds utilizing hyperspectral remote sensing imaging (RSI) has become an indispensable application in the agricultural domain. It is significant for the prediction and growth monitoring of crop yields. Amongst the deep learning (DL) techniques, Convolution Neural Network (CNN) was the best method for classifying HSI for their incredible local contextual modeling ability, enabling spectral and spatial feature extraction. This article designs… More >

Ling Wang, Jingchi Jiang^*, Jingwen Song, Jie Liu

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 833-848, 2023, DOI:10.32604/iasc.2023.036402

Abstract It is significant for agricultural intelligent knowledge services using knowledge graph technology to integrate multi-source heterogeneous crop and pest data and fully mine the knowledge hidden in the text. However, only some labeled data for agricultural knowledge graph domain training are available. Furthermore, labeling is costly due to the need for more data openness and standardization. This paper proposes a novel model using knowledge distillation for a weakly supervised entity recognition in ontology construction. Knowledge distillation between the target and source data domain is performed, where Bi-LSTM and CRF models are constructed for entity recognition. The experimental result is shown… More >

Saud Yonbawi¹, Sultan Alahmari², T. Satyanarayana murthy³, Ravuri Daniel⁴, E. Laxmi Lydia⁵, Mohamad Khairi Ishak⁶, Hend Khalid Alkahtani^7,*, Ayman Aljarbouh⁸, Samih M. Mostafa⁹

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3847-3864, 2023, DOI:10.32604/csse.2023.036552

Abstract Crop insect detection becomes a tedious process for agronomists because a substantial part of the crops is damaged, and due to the pest attacks, the quality is degraded. They are the major reason behind crop quality degradation and diminished crop productivity. Hence, accurate pest detection is essential to guarantee safety and crop quality. Conventional identification of insects necessitates highly trained taxonomists to detect insects precisely based on morphological features. Lately, some progress has been made in agriculture by employing machine learning (ML) to classify and detect pests. This study introduces a Modified Metaheuristics with Transfer Learning based Insect Pest Classification… More >

Imran Ali¹, Zohaib Mushtaq², Saad Arif³, Abeer D. Algarni^4,*, Naglaa F. Soliman⁴, Walid El-Shafai^5,6

Computer Systems Science and Engineering, Vol.46, No.1, pp. 303-319, 2023, DOI:10.32604/csse.2023.034374

Abstract Hyperspectral imaging is gaining a significant role in agricultural remote sensing applications. Its data unit is the hyperspectral cube which holds spatial information in two dimensions while spectral band information of each pixel in the third dimension. The classification accuracy of hyperspectral images (HSI) increases significantly by employing both spatial and spectral features. For this work, the data was acquired using an airborne hyperspectral imager system which collected HSI in the visible and near-infrared (VNIR) range of 400 to 1000 nm wavelength within 180 spectral bands. The dataset is collected for nine different crops on agricultural land with a spectral… More >

Xiao Ya Ma^1,2,*, Jin Tong^1,2, Fei Jiang³, Min Xu⁴, Li Mei Sun¹, Qiu Yan Chen¹

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6145-6159, 2023, DOI:10.32604/cmc.2023.034833

Abstract Production prediction is an important factor influencing the realization of an intelligent agricultural supply chain. In an Internet of Things (IoT) environment, accurate yield prediction is one of the prerequisites for achieving an efficient response in an intelligent agricultural supply chain. As an example, this study applied a conventional prediction method and deep learning prediction model to predict the yield of a characteristic regional fruit (the Shatian pomelo) in a comparative study. The root means square error (RMSE) values of regression analysis, exponential smoothing, grey prediction, grey neural network, support vector regression (SVR), and long short-term memory (LSTM) neural network… More >

Ahmed Abdu Alattab^1,*, Mohammed Eid Ibrahim¹, Reyazur Rashid Irshad¹, Anwar Ali Yahya², Amin A. Al-Awady³

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2397-2413, 2023, DOI:10.32604/cmc.2023.030924

Abstract This research proposes a machine learning approach using fuzzy logic to build an information retrieval system for the next crop rotation. In case-based reasoning systems, case representation is critical, and thus, researchers have thoroughly investigated textual, attribute-value pair, and ontological representations. As big databases result in slow case retrieval, this research suggests a fast case retrieval strategy based on an associated representation, so that, cases are interrelated in both either similar or dissimilar cases. As soon as a new case is recorded, it is compared to prior data to find a relative match. The proposed method is worked on the… More >

Shahid Hussain^*

Phyton-International Journal of Experimental Botany, Vol.91, No.12, pp. 2687-2697, 2022, DOI:10.32604/phyton.2022.021158

Abstract Heavy metal(loid) accumulation in agricultural soils is a threat to the soil capacity, quality, and productivity. It also increases human exposure to heavy metal(loid)s via consumption of contaminated plant-based foods. The detrimental effects of soil contamination also deteriorate the environment of plants and animals. For sustainable agriculture, therefore, the soil must be protected from toxic levels of heavy metal(loid)s. Studies on heavy metal(loid) balances in agricultural soils are important in predicting future risks to sustainable production from agro-ecological zones and human exposure to heavy metal(loid)s. The latest and continuous indexing of the problem seems a prerequisite for sustainable agriculture. This… More >

Yueqiang Yu¹, Tingang Ma¹, Suling Wang^1,*, Minzheng Jiang¹, Yanling Guo^2,3, Ting Jiang^1,*, Shuaiqi Huang¹, Ziming Zheng¹, Bo Yan¹, Jiyuan Lv¹

Journal of Renewable Materials, Vol.11, No.1, pp. 333-347, 2023, DOI:10.32604/jrm.2022.022296

Abstract A calculation model of stress field in laser additive manufacturing of walnut shell composite powder (walnut shell/Co-PES powder) was established. The DFLUX subroutine was used to implement the moveable application of a double ellipsoid heat source by considering the mechanical properties varying with temperature. The stress field was simulated by the sequential coupling method, and the experimental results were in good accordance with the simulation results. In addition, the distribution and variation of stress and strain field were obtained in the process of laser additive manufacturing of walnut shell composite powder. The displacement of laser additive manufacturing walnut shell composite… More > Graphic Abstract

Kittikorn Sasujit^1,*, Nigran Homdoung¹, Nakorn Tippayawong²

Energy Engineering, Vol.119, No.5, pp. 2149-2167, 2022, DOI:10.32604/ee.2022.022069

Abstract Biomass is becoming one of the most popular renewable energy sources, especially from agricultural wastes. These wastes can be gasified and utilized in various industries. This experimental study investigated producer gas generation from densified agricultural fuels such as corncobs, rice husks, wood chips, and oil palm fronds in a 50 kW_th throatless downdraft gasifier. This system produced combustible gases such as H₂, CO, and CH₄, which were utilized as a substitute for diesel fuel in a small diesel engine for power generation. The results showed that the gasifier performs successfully and seems to prefer pellets to briquettes. Producer gas contains 18%–20%… More >