Sumit Sow^1,#, Shivani Ranjan^1,#,*, Mahmoud F. Seleiman^2,3, Hiba M. Alkharabsheh^4,*, Mukesh Kumar¹, Navnit Kumar¹, Smruti Ranjan Padhan⁵, Dhirendra Kumar Roy¹, Dibyajyoti Nath⁶, Harun Gitari⁷, Daniel O. Wasonga⁸

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1569-1598, 2024, DOI:10.32604/phyton.2024.052241 - 30 July 2024

Abstract Agriculture plays a crucial role in the economy, and there is an increasing global emphasis on automating agricultural processes. With the tremendous increase in population, the demand for food and employment has also increased significantly. Agricultural methods traditionally used to meet these requirements are no longer adequate, requiring solutions to issues such as excessive herbicide use and the use of chemical fertilizers. Integration of technologies such as the Internet of Things, wireless communication, machine learning, artificial intelligence (AI), and deep learning shows promise in addressing these challenges. However, there is a lack of comprehensive documentation… More >

Yu Zuo¹, Wenwen Li^2,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4413-4431, 2024, DOI:10.32604/cmc.2024.049805 - 20 June 2024

Abstract In cornfields, factors such as the similarity between corn seedlings and weeds and the blurring of plant edge details pose challenges to corn and weed segmentation. In addition, remote areas such as farmland are usually constrained by limited computational resources and limited collected data. Therefore, it becomes necessary to lighten the model to better adapt to complex cornfield scene, and make full use of the limited data information. In this paper, we propose an improved image segmentation algorithm based on unet. Firstly, the inverted residual structure is introduced into the contraction path to reduce the… More >

Tao Yin¹, Changgen Peng^2,*, Weijie Tan³, Dequan Xu⁴, Hanlin Tang⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 827-843, 2024, DOI:10.32604/cmes.2023.029039 - 22 September 2023

Abstract In the assessment of car insurance claims, the claim rate for car insurance presents a highly skewed probability distribution, which is typically modeled using Tweedie distribution. The traditional approach to obtaining the Tweedie regression model involves training on a centralized dataset, when the data is provided by multiple parties, training a privacy-preserving Tweedie regression model without exchanging raw data becomes a challenge. To address this issue, this study introduces a novel vertical federated learning-based Tweedie regression algorithm for multi-party auto insurance rate setting in data silos. The algorithm can keep sensitive data locally and uses… 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 - 09 November 2023

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.… More >

Jigna Patel¹, Anand Ruparelia¹, Sudeep Tanwar^1,*, Fayez Alqahtani², Amr Tolba³, Ravi Sharma⁴, Maria Simona Raboaca^5,6,*, Bogdan Constantin Neagu⁷

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1281-1301, 2023, DOI:10.32604/cmc.2023.038796 - 31 October 2023

Abstract The overgrowth of weeds growing along with the primary crop in the fields reduces crop production. Conventional solutions like hand weeding are labor-intensive, costly, and time-consuming; farmers have used herbicides. The application of herbicide is effective but causes environmental and health concerns. Hence, Precision Agriculture (PA) suggests the variable spraying of herbicides so that herbicide chemicals do not affect the primary plants. Motivated by the gap above, we proposed a Deep Learning (DL) based model for detecting Eggplant (Brinjal) weed in this paper. The key objective of this study is to detect plant and non-plant… More >

B. Keerthi Samhitha^*, R. Subhashini

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3125-3142, 2023, DOI:10.32604/iasc.2023.040643 - 11 September 2023

Abstract Accurate and rapid detection of fish behaviors is critical to perceive health and welfare by allowing farmers to make informed management decisions about recirculating the aquaculture system while decreasing labor. The classic detection approach involves placing sensors on the skin or body of the fish, which may interfere with typical behavior and welfare. The progress of deep learning and computer vision technologies opens up new opportunities to understand the biological basis of this behavior and precisely quantify behaviors that contribute to achieving accurate management in precision farming and higher production efficacy. This study develops an… More >

Bimal Kumar Ghimire¹, Chang Yeon Yu², Seung Hyun Kim¹, Ill Min Chung^1,*

Phyton-International Journal of Experimental Botany, Vol.92, No.5, pp. 1439-1467, 2023, DOI:10.32604/phyton.2023.023076 - 09 March 2023

Abstract Miscanthus, is a promising bioenergy crop, considered superior to other bioenergy crops because of its higher water and nutrient use efficiency, cold tolerance, and higher production of biomass. Broadleaf weeds and grass weeds, cause major problems in the Miscanthus field. A field experiment was conducted in 2018 and 2019, to assess the effects of pre-emergence (alachlor and napropamide) and post-emergence herbicides (nicosulfuron, dicamba, bentazon, and glufosinate ammonium) on broadleaf and grass weeds in M. sinensis and M. sacchariflorus fields. The weed control efficiency and phytotoxicity of pre- and post-emergence herbicides were evaluated at 30 days after treatment (DAT) and… More >

Saud Yonbawi¹, Sultan Alahmari², T. Satyanarayana Murthy³, Padmakar Maddala⁴, E. Laxmi Lydia⁵, Seifedine Kadry^6,7,8,*, Jungeun Kim⁹

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1533-1547, 2023, DOI:10.32604/csse.2023.036296 - 09 February 2023

Abstract Precision agriculture includes the optimum and adequate use of resources depending on several variables that govern crop yield. Precision agriculture offers a novel solution utilizing a systematic technique for current agricultural problems like balancing production and environmental concerns. Weed control has become one of the significant problems in the agricultural sector. In traditional weed control, the entire field is treated uniformly by spraying the soil, a single herbicide dose, weed, and crops in the same way. For more precise farming, robots could accomplish targeted weed treatment if they could specifically find the location of the… More >

Yuzhi Wu¹, Cunzhen Geng^1,*, Chaochao Cui², Zhefeng Xin², Yanzhi Xia¹, Zhixin Xue^1,*

Journal of Renewable Materials, Vol.11, No.3, pp. 1199-1208, 2023, DOI:10.32604/jrm.2022.022976 - 31 October 2022

Abstract The sulfate groups in agar structure played a good role in the formation of fiber. However, commercially available agar is usually extracted from red algae by alkali treatment to decrease the content of sulfate group for the purpose of high gel strength. In this paper, an alkali-free method of agar extraction from Gracilaria lemaneiformis was proposed for the wet-spinning purpose. This method is environmentally friendly, reduces the extraction steps, saves energy, and reduces the production cost of agar fiber. The improved agar preparation process not only has higher agar yield, but also has higher molecular weight More > Graphic Abstract

Ge Chen^1,2, Yuling Kang¹, Fangbo Cao¹, Jiana Chen¹, Min Huang^1,*

Phyton-International Journal of Experimental Botany, Vol.92, No.1, pp. 71-77, 2023, DOI:10.32604/phyton.2022.022313 - 06 September 2022

Abstract Weeds occurred during the fallow season can well perform the function of carbon (C) capture due to receiving little human disturbance. This study aimed to evaluate the C capture potential of fallow weeds in rice (Oryza sativa L.) cropping systems. A six-region, two-year on-farm investigation and a three-year tillage experiment were conducted to estimate C capture in fallow weeds in rice cropping systems. The on-farm investigation showed that the average mean C capture by fallow weeds across six regions and two years reached 112 g m^–2. The tillage experiment indicated that no-tillage practices increased C capture by More >