Khalid A. Al-Gaadi^1,2, Ahmed M. Zeyada¹, ElKamil Tola^2,*, Abdullah M. Alhamdan^1,3, Khalid A.M. Ahmed^3,4, Rangaswamy Madugundu², Mohamed K. Edrris²

Phyton-International Journal of Experimental Botany, Vol.93, No.6, pp. 1311-1323, 2024, DOI:10.32604/phyton.2024.049535

Abstract From economic and nutritional points of view, tomato is, historically, considered one of the most important crops. Without significant yield reduction, most commercial cultivars of tomato crops are sensitive to moderate levels of salinity. However, high levels of salt stress can negatively affect the yield and quality of tomato fruits. Therefore, this study was conducted to evaluate the yield and fruit quality of three tomato cultivars (Forester, Ghandowra-F1, and Feisty-Red) cultivated hydroponically, under three different levels of nutrient solution salinity. Evaluation of tomato fruits was performed based on quantity (number and weight of fruits, and… More >

Md. Parvez Anwar^*, Masuma Akhter, Sharmin Aktar, Sinthia Afsana Kheya, A. K. M. Mominul Islam^*, Sabina Yeasmin, Ahmed Khairul Hasan, Md. Harun Or Rashid

Phyton-International Journal of Experimental Botany, Vol.93, No.6, pp. 1159-1177, 2024, DOI:10.32604/phyton.2024.049073

Abstract Seed priming is a pre-germinated technique that can enhance seed germination percentage, faster and synchronized germination, better seedling growth, and yield under stress conditions. To ascertain the most effective seed priming method that would ensure the potential yield of wheat in Bangladesh, two experiments were carried out from December 2021 to March 2022 at the Department of Agronomy, Bangladesh Agricultural University. Two wheat varieties namely BARI Gom-28 and BWMRI Gom-1 were subjected to a range of priming chemicals in both lab and pot tests. These compounds included the following: control (no priming), hydropriming (distilled water),… More >

Md. Abdul Quddus¹, Md. Ataur Rahman¹, Razu Ahmed¹, Mohammad Eyakub Ali², Khokan Kumer Sarker³, Md. Alamgir Siddiky⁴, Mohibur Rahman⁴, Lamya Ahmed Alkeridis⁵, Samy Sayed^6,7, Ahmed Gaber^8,9, Akbar Hossain^10,*

Phyton-International Journal of Experimental Botany, Vol.93, No.5, pp. 901-922, 2024, DOI:10.32604/phyton.2024.049226

Abstract Garden pea productivity and qualities are hampered in zinc (Zn), boron (B), and molybdenum (Mo) deficient soil. Thus, the combination of micronutrients (i.e., Zn, B, and Mo) and rhizobium is necessary to increase the productivity and quality of garden peas, since this management for garden peas is neglected in Bangladesh. Therefore, the present study was made to assess the effectiveness of rhizobium inoculant singly or in combination with the micronutrients (i.e., Zn, B, and Mo) on growth, yield, nutrient uptake, and quality of garden peas. Treatments were: T = Control, T = Rhizobium inoculation at 50… More >

Anindita Das¹, Kanu Murmu², Biplab Mitra³, Pintoo Bandopadhyay², Ritesh Kundu⁴, Moupiya Roy⁵, Saleh Alfarraj⁶, Mohammad Javed Ansari⁷, Marian Brestic⁸, Akbar Hossain^9,*

Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 763-776, 2024, DOI:10.32604/phyton.2024.049473

Abstract Nutrient management plays a crucial role in the yield and quality of sweet corn. A field experiment was conducted in consecutive two kharif seasons in 2018 and 2019 to investigate the effect of various organic sources of nutrients in combination with inorganic sources on the yield and quality of sweet corn under new alluvial soils of West Bengal, India. Treatments were: T: Control (without fertilizers); T: 100% recommended dose (RDF) of chemical fertilizers (CF) (RDF CF); T: 100% recommended dose of N (RDN) through vermicompost (VC) (RDN VC); T: 50 RDN through CF + 50%… More >

Jiana Chen^1,2, Fangbo Cao^1,2, Min Huang^1,2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 807-817, 2024, DOI:10.32604/phyton.2024.048299

Abstract Transplanting rice varieties grown in different seasons can lead to different yields due to different dry matter production. Early-season rice varieties transplanted in the late season can obtain high yields with short-growth duration and higher yields driven by higher dry matter production. To make clear the variations in dry matter production across seasons, four early-season rice varieties were chosen for late-season transplantation. The grain yield, dry matter accumulation, leaf photosynthetic, and leaf stomatal properties were studied. It was observed that the average yields of these four varieties in the late season were 33% greater, despite… More >

Huiqin Li, Mingzhi Zhang^*, Na Xiao, Haijian Yang

Phyton-International Journal of Experimental Botany, Vol.92, No.12, pp. 3211-3236, 2023, DOI:10.32604/phyton.2023.031003

Abstract To determine suitable thresholds for deficit irrigation of winter wheat in the well-irrigated area of the Huang-Huai-Hai Plain, we investigated the effects of different deficit irrigation lower limits and quotas on the photosynthetic characteristics and grain yield of winter wheat. Four irrigation lower limits were set for initiating irrigation (i.e., light drought (LD, 50%, 55%, 60% and 50% of field holding capacity (FC) at the seedling-regreening, jointing, heading and filling-ripening stages, respectively), medium drought (MD, 40%, 50%, 55% and 45% of FC at the same stages, respectively), adequate moisture (CK1, 60%, 65%, 70% and 60%… More >

Hongxia Wang^1,2, Zhiqiang Duan², Qingwei Guo², Yongmei Zhang^1,2,*, Yuhong Zhao^2,3,4,*

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1393-1409, 2023, DOI:10.32604/cmc.2023.045871

Abstract Due to the large unexplored compositional space, long development cycle, and high cost of traditional trial-anderror experiments, designing high strength aluminum-lithium alloys is a great challenge. This work establishes a performance-oriented machine learning design strategy for aluminum-lithium alloys to simplify and shorten the development cycle. The calculation results indicate that radial basis function (RBF) neural networks exhibit better predictive ability than back propagation (BP) neural networks. The RBF neural network predicted tensile and yield strengths with determination coefficients of 0.90 and 0.96, root mean square errors of 30.68 and 25.30, and mean absolute errors of More >

Ziwei Li^1,2, Lifen Huang^1,2, Zhongyang Huo^1,2, Min Jiang^1,2,*

Phyton-International Journal of Experimental Botany, Vol.92, No.11, pp. 2999-3019, 2023, DOI:10.32604/phyton.2023.030627

Abstract The canopy temperature of rice is an important index that directly reflects the growth and physiological state of rice, and affects the yield of rice plants to a great extent. The correlation between the temperatures of different rice organs and canopy in different growth stages and the grain yield is complex. The stability and universality of these correlations must be verified. We conducted a pot experiment using two rice varieties and two temperature treatments (high temperature treatment was carried out at the beginning of heading stage for 10 days). We measured rice organ temperature during… More >

Long Wang¹, Qingyun Shen¹, Gui Wang^2,*

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.11, pp. 2877-2890, 2023, DOI:10.32604/fdmp.2023.029206

Abstract Drill cuttings are broken bits of solid material removed from a borehole drilled by rotary, percussion, or auger methods and brought to the surface in the drilling mud. When these cuttings enter the annulus, they have an effect on the drilling fluid rheology and density, which is, in general, quite difficult to evaluate. By introducing an empirical correlation for the rheological properties of cuttings-laden drilling fluids, this study proposes a pressure-loss prediction method for an extended-reach well (ERW). After verifying the accuracy of this method, a case study is considered and a sensitivity analysis is More >

Anas Bilal^1,*, Xiaowen Liu¹, Haixia Long^1,*, Muhammad Shafiq², Muhammad Waqar³

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2401-2426, 2023, DOI:10.32604/cmc.2023.037857

Abstract Farming is cultivating the soil, producing crops, and keeping livestock. The agricultural sector plays a crucial role in a country’s economic growth. This research proposes a two-stage machine learning framework for agriculture to improve efficiency and increase crop yield. In the first stage, machine learning algorithms generate data for extensive and far-flung agricultural areas and forecast crops. The recommended crops are based on various factors such as weather conditions, soil analysis, and the amount of fertilizers and pesticides required. In the second stage, a transfer learning-based model for plant seedlings, pests, and plant leaf disease More >