Usman Khan¹, Muhammad Khalid Khan¹, Muhammad Ayub Latif¹, Muhammad Naveed^1,2,*, Muhammad Mansoor Alam^2,3,4, Salman A. Khan¹, Mazliham Mohd Su’ud^2,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 2967-3000, 2024, DOI:10.32604/cmc.2024.045101

Abstract Recently, there has been a notable surge of interest in scientific research regarding spectral images. The potential of these images to revolutionize the digital photography industry, like aerial photography through Unmanned Aerial Vehicles (UAVs), has captured considerable attention. One encouraging aspect is their combination with machine learning and deep learning algorithms, which have demonstrated remarkable outcomes in image classification. As a result of this powerful amalgamation, the adoption of spectral images has experienced exponential growth across various domains, with agriculture being one of the prominent beneficiaries. This paper presents an extensive survey encompassing multispectral and hyperspectral images, focusing on their… More >

Xingli Wu^{1,{{sup}}#{{/sup}}}, Huchang Liao^{1,{{sup}}#{{/sup}}}, Shuxian Sun¹, Zhengjun Wan^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3125-3146, 2024, DOI:10.32604/cmes.2023.047031

Abstract Agricultural investment project selection is a complex multi-criteria decision-making problem, as agricultural projects are easily influenced by various risk factors, and the evaluation information provided by decision-makers usually involves uncertainty and inconsistency. Existing literature primarily employed direct preference elicitation methods to address such issues, necessitating a great cognitive effort on the part of decision-makers during evaluation, specifically, determining the weights of criteria. In this study, we propose an indirect preference elicitation method, known as a preference disaggregation method, to learn decision-maker preference models from decision examples. To enhance evaluation ease, decision-makers merely need to compare pairs of alternatives with which… More >

Perla Patricia Ochoa-García¹, Jaime Sánchez-Salas², Ricardo Trejo-Calzada¹, Jesús Josafath Quezada-Rivera², Fabián García-González^1,*

Phyton-International Journal of Experimental Botany, Vol.93, No.2, pp. 371-386, 2024, DOI:10.32604/phyton.2024.048338

Abstract The genus Argemone L. (Papaveraceae) is found widely distributed in Mexico’s Chihuahuan Desert (CD). Some species of this genus are of phytochemical or ethnobotanical interest. They are inedible plants considered as scrubs. To date they have not been broadly studied; thus, their ecology is, to our knowledge, unknown. The present work was centered around carrying out a morphometric analysis and the determination of minerals in the soil and seeds of the wild populations of Argemone at sites belonging to two ecoregions of the CD in Mexico. In April 2021 and April 2022, seeds of Argemone spp., and soil samples were… More >

Thean Heng Tan¹, Najihah Mohd Hashim², Wageeh Abdulhadi Yehya Dabdawb¹, Mochamad Zakki Fahmi^3,*, Hwei Voon Lee^1,*

Journal of Renewable Materials, Vol.12, No.1, pp. 29-43, 2024, DOI:10.32604/jrm.2023.043449

Abstract The study focuses on the development of biocompatible and stable FA-functionalized nanocrystalline cellulose (NCC) as a potential drug delivery system for targeting folate receptor-positive cancer cells. The FA-functionalized NCCs were synthesized through a series of chemical reactions, resulting in nanoparticles with favorable properties for biomedical applications. The microstructural analysis revealed that the functionalized NCCs maintained their rod-shaped morphology and displayed hydrodynamic diameters suitable for evading the mononuclear phagocytic system while being large enough to target tumor tissues. Importantly, these nanoparticles possessed a negative surface charge, enhancing their stability and repelling potential aggregation. The binding specificity of FA-functionalized NCCs to folate… More > Graphic Abstract

Deepak Kumar¹, Vinay Kukreja¹, Ayush Dogra^1,*, Bhawna Goyal², Talal Taha Ali³

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2097-2121, 2023, DOI:10.32604/cmc.2023.044287

Abstract Wheat rust diseases are one of the major types of fungal diseases that cause substantial yield quality losses of 15%–20% every year. The wheat rust diseases are identified either through experienced evaluators or computerassisted techniques. The experienced evaluators take time to identify the disease which is highly laborious and too costly. If wheat rust diseases are predicted at the development stages, then fungicides are sprayed earlier which helps to increase wheat yield quality. To solve the experienced evaluator issues, a combined region extraction and cross-entropy support vector machine (CE-SVM) model is proposed for wheat rust disease identification. In the proposed… More >

Yousef Alhwaiti^1,*, Muhammad Hameed Siddiqi¹, Irshad Ahmad²

Computer Systems Science and Engineering, Vol.47, No.3, pp. 3011-3031, 2023, DOI:10.32604/csse.2023.042110

Abstract Weeds are one of the utmost damaging agricultural annoyers that have a major influence on crops. Weeds have the responsibility to get higher production costs due to the waste of crops and also have a major influence on the worldwide agricultural economy. The significance of such concern got motivation in the research community to explore the usage of technology for the detection of weeds at early stages that support farmers in agricultural fields. Some weed methods have been proposed for these fields; however, these algorithms still have challenges as they were implemented against controlled environments. Therefore, in this paper, a… More >

Abdelwahed Berguiga^1,2,*, Ahlem Harchay^1,2, Ayman Massaoudi^1,2, Mossaad Ben Ayed³, Hafedh Belmabrouk⁴

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 379-402, 2023, DOI:10.32604/cmc.2023.041667

Abstract Smart Agriculture, also known as Agricultural 5.0, is expected to be an integral part of our human lives to reduce the cost of agricultural inputs, increasing productivity and improving the quality of the final product. Indeed, the safety and ongoing maintenance of Smart Agriculture from cyber-attacks are vitally important. To provide more comprehensive protection against potential cyber-attacks, this paper proposes a new deep learning-based intrusion detection system for securing Smart Agriculture. The proposed Intrusion Detection System IDS, namely GMLP-IDS, combines the feedforward neural network Multilayer Perceptron (MLP) and the Gaussian Mixture Model (GMM) that can better protect the Smart Agriculture… More >

Tauqeer Ahmad Yasir^1,2, Muhammad Ateeq^1,3, Allah Wasaya^1,2,*, Mubshar Hussain², Naeem Sarwar², Khuram Mubeen⁴, Mudassir Aziz⁴, Muhammad Aamir Iqbal⁵, Chukwuma C. Ogbaga⁶, Ibrahim Al-Ashkar⁷, Md Atikur Rahman⁸, Ayman El Sabagh^9,10,*

Phyton-International Journal of Experimental Botany, Vol.92, No.11, pp. 3113-3131, 2023, DOI:10.32604/phyton.2023.029502

Abstract Drought is one of the critical limitations to agricultural soils and crop plants. Scarcity of water is increasing due to climate change that lead to increasing threats to global food security. Therefore, ecofriendly and cost effective strategies are highly desirable for mitigating drought stress along with sustainable and smart agricultural production. The aim of the study was to mitigate DS using seed priming and exogenous supplementation of β-aminobutyric acid (BABA) in linseed (Linum usitatissimum L.). Different doses (0, 50, 100 and 150 µM) of BABA were used for seed priming agent and foliar spraying under three soil moisture levels viz.,… More >

Feng Yang¹, Zhong Wu^2,*, Xiaoyan Teng¹

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 719-738, 2024, DOI:10.32604/cmes.2023.028699

Abstract The low efficiency and high cost of fresh agricultural product terminal distribution directly restrict the operation of the entire supply network. To reduce costs and optimize the distribution network, we construct a mixed integer programming model that comprehensively considers to minimize fixed, transportation, fresh-keeping, time, carbon emissions, and performance incentive costs. We analyzed the performance of traditional rider distribution and robot distribution modes in detail. In addition, the uncertainty of the actual market demand poses a huge threat to the stability of the terminal distribution network. In order to resist uncertain interference, we further extend the model to a robust… More > Graphic Abstract

Asmaa Salah¹, Hoda Sany¹, Abo El-Khair B. El-Sayed², Reham M. El-Bahbohy¹, Heba I. Mohamed^3,*, Ayman Amin^1,*

Phyton-International Journal of Experimental Botany, Vol.92, No.10, pp. 2875-2890, 2023, DOI:10.32604/phyton.2023.031064

Abstract Water is the most essential natural resource for the future development. Agriculture production is extensively water-dependent and a significant polluter of water resources. So, this work investigated the effect of two different preparation media [Bold’s Basal Medium (BBM) and Domiati cheese whey (DCW)] for agricultural drainage water (ADW) remediation. All treatments were incubated for 6 days. According to the results of biomass productivity, specific growth rate, photosynthetic pigments, and biochemical composition, Desmodesmus sp. can grow in drainage water without dilution. The two treatments significantly reduced the concentration of nitrate, phosphate, chemical oxygen demand, and sodium in ADW. Finally, using cheese… More >