Seerat Singla¹, Gunjan Shandilya¹, Ayman Altameem², Ruby Pant³, Ajay Kumar⁴, Ateeq Ur Rehman^5,*, Ahmad Almogren^6,*

Phyton-International Journal of Experimental Botany, Vol.94, No.12, pp. 4021-4057, 2025, DOI:10.32604/phyton.2025.073354 - 29 December 2025

Abstract Turmeric Leaf diseases pose a major threat to turmeric cultivation, causing significant yield loss and economic impact. Early and accurate identification of these diseases is essential for effective crop management and timely intervention. This study proposes DenseSwinGNNNet, a hybrid deep learning framework that integrates DenseNet-121, the Swin Transformer, and a Graph Neural Network (GNN) to enhance the classification of turmeric leaf conditions. DenseNet121 extracts discriminative low-level features, the Swin Transformer captures long-range contextual relationships through hierarchical self-attention, and the GNN models inter-feature dependencies to refine the final representation. A total of 4361 images from the… More >

Jie Jin¹, Tianci Wang¹, Yaning Wang¹, Jingqi Yao², Jinxiu Song^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.11, pp. 3611-3632, 2025, DOI:10.32604/phyton.2025.070680 - 01 December 2025

Abstract In plant factory with artificial lighting, precise regulation of environmental and nutritional factors is essential to optimize both growth and quality of leafy vegetables. This study systematically evaluated the combined effects of light intensity (150, 200, 250 μmol/(m²·s)) and calcium supply in the nutrient solution (0.5, 1.0, 1.5 mmol/L) on lettuce morphology, photosynthesis, quality indices, and tipburn incidence. Elevating light from 150 to 200 μmol/(m²·s) significantly enhanced leaf number, area, photosynthetic rate, biomass, and foliar calcium. These gains plateaued at 250 μmol/(m²·s), where tipburn incidence surged to 76.5%. Photosynthetic pigments progressively rose with light intensity. Calcium supply… More >

Heng Zhang^1,#, Meng Wang^1,#, Dong Zeng^1,2, Yunbo Xu¹, Dongyuan Guo¹, Xuanchen Liu^1,3, Zhanqi Ren⁴, Jinzi Zhang¹, Yuhang Liu¹, Qiuyu Wang¹, Shuo Yu¹, Guanzheng Qu^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.10, pp. 3205-3216, 2025, DOI:10.32604/phyton.2025.069994 - 29 October 2025

Abstract Hybridization remains an important method for breeding new poplar varieties. It results in significant variation in leaf phenotype among parents and offspring, and among offspring themselves. This study aimed to investigate whether leaf shape variations were similar in offspring produced from reciprocal crosses. Specifically, two hybrid combinations were produced: the direct cross with Populus ussuriensis as the maternal parent and P. simonii × P. nigra as the paternal parent (HY53), and the reciprocal cross with P. simonii × P. nigra as the maternal parent and P. ussuriensis as the paternal parent (HY268). Using 3-month-old rooted cuttings from 40 clones (36 F₁ hybrids… More >

Nameer Baht^1,*, Enrique Domínguez^1,2,*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4441-4455, 2025, DOI:10.32604/cmc.2025.069528 - 23 October 2025

Abstract Coffee is an important agricultural commodity, and its production is threatened by various diseases. It is also a source of concern for coffee-exporting countries, which is causing them to rethink their strategies for the future. Maintaining crop production requires early diagnosis. Notably, Coffee Leaf Miner (CLM) Machine learning (ML) offers promising tools for automated disease detection. Early detection of CLM is crucial for minimising yield losses. However, this study explores the effectiveness of using Convolutional Neural Networks (CNNs) with transfer learning algorithms ResNet50, DenseNet121, MobileNet, Inception, and hybrid VGG19 for classifying coffee leaf images as… More >

Qiang Peng^1,2, Jia-Yu Yang¹, Xu-Yu Xiang^1,*

Journal on Artificial Intelligence, Vol.7, pp. 437-450, 2025, DOI:10.32604/jai.2025.072332 - 20 October 2025

Abstract Camellia oleifera is one of the four largest oil tree species in the world, and also an important economic crop in China, which has overwhelming economic benefits. However, Camellia oleifera is invaded by various diseases during its growth process, which leads to yield reduction and profit damage. To address this problem and ensure the healthy growth of Camellia oleifera, the purpose of this study is to apply the lightweight network to the identification and detection of camellia oleifolia leaf disease. The attention mechanism was combined for highlighting the local features and improve the attention of the model to the More >

Deepti Rekha Sahoo, Trinath Biswal^*

Journal of Polymer Materials, Vol.42, No.3, pp. 811-835, 2025, DOI:10.32604/jpm.2025.067022 - 30 September 2025

Abstract The purpose of this research work is to determine the removal efficiency of Cu²⁺ and Pb²⁺ ions using polyvinyl alcohol/neem leaf extract/chitosan (PVA/NLE/CS) composite films as adsorbent materials from an aqueous medium, with respect to pH, contact time, and adsorbent dosage. The synthesized composite material was characterized using Fourier Transform Infrared (FTIR) spectroscopy, thermogravimetric analysis-Derivative Thermogravimetry (TGA-DTG), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy-Energy Dispersive X-ray Spectroscopy (SEM-EDX). The antibacterial activity and swelling response of the material were studied using suitable methodologies. The FTIR study confirmed the interactions among PVA, chitosan, and… More >

Sadia Alam Shammi^1,2, Yanbo Huang^1,*, Weiwei Xie^1,2, Gary Feng¹, Haile Tewolde¹, Xin Zhang³, Johnie Jenkins¹, Mark Shankle⁴

Phyton-International Journal of Experimental Botany, Vol.94, No.9, pp. 2745-2766, 2025, DOI:10.32604/phyton.2025.068955 - 30 September 2025

Abstract Crop leaf area index (LAI) and biomass are two major biophysical parameters to measure crop growth and health condition. Measuring LAI and biomass in field experiments is a destructive method. Therefore, we focused on the application of unmanned aerial vehicles (UAVs) in agriculture, which is a cost and labor-efficient method. Hence, UAV-captured multispectral images were applied to monitor crop growth, identify plant bio-physical conditions, and so on. In this study, we monitored soybean crops using UAV and field experiments. This experiment was conducted at the MAFES (Mississippi Agricultural and Forestry Experiment Station) Pontotoc Ridge-Flatwoods Branch… More >

Zhong Ren^1,2,3,#, Shuiming Zhang^1,#, Yuzhi Fei¹, Zhu Chen³, Yue Zhao³, Xin Meng³, Hongfei Zhao^2,*, Jie Ren^3,*

Phyton-International Journal of Experimental Botany, Vol.94, No.9, pp. 2927-2947, 2025, DOI:10.32604/phyton.2025.067310 - 30 September 2025

Abstract Acer paxii belongs to the evergreen species of Acer, but it exhibits a unique feature of reddish leaves in fall in subtropical regions. Although the association of AP2/ERF transcription factors with color change has been well-documented in prior research, molecular investigations focusing on AP2/ERF remain notably lacking in Acer paxii. This research focuses on performing an extensive genome-wide investigation to identify and characterize the AP2/ERF gene family in Acer paxii. As a result, 123 ApAP2/ERFs were obtained. Phylogenetic analyses categorized the ApAP2/ERF family members into 15 subfamilies. The evolutionary traits of the ApAP2/ERFs were investigated by analyzing their… More >

Geoffry Mutiso^*, John Ndia

Journal on Artificial Intelligence, Vol.7, pp. 275-288, 2025, DOI:10.32604/jai.2025.069768 - 05 September 2025

Abstract Tomato leaf diseases significantly reduce crop yield; therefore, early and accurate disease detection is required. Traditional detection methods are laborious and error-prone, particularly in large-scale farms, whereas existing hybrid deep learning models often face computational inefficiencies and poor generalization over diverse environmental and disease conditions. This study presents a unified U-Net-Vision Mamba Model with Hierarchical Bottleneck Attention Mechanism (U-net-Vim-HBAM), which integrates U-Net’s high-resolution segmentation, Vision Mamba’s efficient contextual processing, and a Hierarchical Bottleneck Attention Mechanism to address the challenges of disease detection accuracy, computational complexity, and efficiency in existing models. The model was trained on More >

Lina Song¹, Caijie Yi¹, Shiwei Zhao¹, Yuxin Peng¹, Zijing Li¹, Yuqiang Zhang ², Hua Zhang¹, Helan Qin¹, Huali Zhang^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.8, pp. 2593-2613, 2025, DOI:10.32604/phyton.2025.068133 - 29 August 2025

Abstract Naturally occurring yellow leaf mutants are an important resource for studying pigment content and biosynthesis, as well as related gene expression. In our ongoing cultivation of Rehmannia chingii H. L. Li, we found an off-type yellow plant. The yellowing started with the new leaves and gradually spread downward until the entire plant exhibited a stable shade of yellow. We studied the differences in the chlorophyll and carotenoid content, carotenoid profile, and transcriptome of this yellow-leaf mutant (P2). Compared to the wild-type R. chingii plant (P1), P2 leaves had significantly lower chlorophyll and carotenoid content. LC-MS/MS analysis revealed More >