Meng Wang¹, Jinghan Cai¹, Wenzheng Liu¹, Xue Yang¹, Jingjing Zhang¹, Qiangmin Zhou¹, Fanzhen Wang¹, Hang Zhang^1,*, Tonghai Liu^2,*

Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2025.075541 - 30 January 2026

Abstract Tomato is a major economic crop worldwide, and diseases on tomato leaves can significantly reduce both yield and quality. Traditional manual inspection is inefficient and highly subjective, making it difficult to meet the requirements of early disease identification in complex natural environments. To address this issue, this study proposes an improved YOLO11-based model, YOLO-SPDNet (Scale Sequence Fusion, Position-Channel Attention, and Dual Enhancement Network). The model integrates the SEAM (Self-Ensembling Attention Mechanism) semantic enhancement module, the MLCA (Mixed Local Channel Attention) lightweight attention mechanism, and the SPA (Scale-Position-Detail Awareness) module composed of SSFF (Scale Sequence Feature… More >

Wonkyu Yi, Jongseok Park^*

Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2026.073450 - 30 January 2026

Abstract Understanding plant responses under low-pressure conditions is important for developing closed cultivation systems that simulate space environments. This study aimed to assess the effects of different pressure levels on growth, photosynthesis, and secondary metabolite accumulation in red leaf lettuce (Lactuca sativa L. var. ‘Super Caesar’s Red’). Plants were cultivated for three weeks in sealed chambers under 101 kPa (atmospheric pressure), 66 kPa (moderate low pressure), and 33 kPa (severe low pressure). Growth analysis showed that leaf length and leaf area decreased significantly with reduced pressure, while chlorophyll content and SPAD values increased gradually. Photosynthetic measurements indicated More >

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 >