Saud Yonbawi¹, Sultan Alahmari², B. R. S. S. Raju³, Chukka Hari Govinda Rao⁴, Mohamad Khairi Ishak⁵, Hend Khalid Alkahtani⁶, José Varela-Aldás^7,*, Samih M. Mostafa⁸

Computer Systems Science and Engineering, Vol.46, No.2, pp. 2319-2335, 2023, DOI:10.32604/csse.2023.036721

Abstract Artificial intelligence (AI) technologies and sensors have recently received significant interest in intellectual agriculture. Accelerating the application of AI technologies and agriculture sensors in intellectual agriculture is urgently required for the growth of modern agriculture and will help promote smart agriculture. Automatic irrigation scheduling systems were highly required in the agricultural field due to their capability to manage and save water deficit irrigation techniques. Automatic learning systems devise an alternative to conventional irrigation management through the automatic elaboration of predictions related to the learning of an agronomist. With this motivation, this study develops a modified black widow optimization with a… More >

Ruoyu Xiong¹, Liming Chen¹, Daren Jiang¹, Yingjie Zhou¹, Xueming Tan¹, Xiaohua Pan¹, Yongjun Zeng¹, Jun Zhang², Yanhua Zeng^1,*

Phyton-International Journal of Experimental Botany, Vol.91, No.7, pp. 1495-1502, 2022, DOI:10.32604/phyton.2022.018485

Abstract In order to investigate the effects of different irrigation management on the textural properties of two different double-cropping late Indica rice, the effects of three irrigation management including conventional irrigation (CK), constant irrigation (CI) and alternate wetting and drying (AWD) on textural properties has been researched under field conditions of two years. The results indicated that the firmness, cohesiveness and chewiness were decreased under AWD treatment, and the stickiness was increased compared with CK, while the textural properties under CI treatment showed the opposite trend with AWD treatment. Additionally, AWD treatment signifi- cantly improved the springiness of TY871 compared with… More >