Mohammed Benamara^1,2, Boumediene Touati³, Said Bennaceur⁴, Bendjillali Ridha Ilyas^5,*

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.072641 - 27 December 2025

Abstract This study explores the thin-layer convective solar drying of Marrubium vulgare L. leaves under conditions typical of sun-rich semi-arid climates. Drying experiments were conducted at three inlet-air temperatures (40°C, 50°C, 60°C) and two air velocities (1.5 and 2.5 m·s⁻¹) using an indirect solar dryer with auxiliary temperature control. Moisture-ratio data were fitted with eight widely used thin-layer models and evaluated using correlation coefficient (r), root-mean-square error (RMSE), and Akaike information criterion (AIC). A complementary heat-transfer analysis based on Reynolds and Prandtl numbers with appropriate Nusselt correlations was used to relate flow regime to drying performance, and an… More > Graphic Abstract

Fang Liao, Xiurong Wang^*, Muyan Xie, Lixin Duan

Phyton-International Journal of Experimental Botany, Vol.94, No.11, pp. 3667-3686, 2025, DOI:10.32604/phyton.2025.069653 - 01 December 2025

Abstract Bryophytes play important ecological roles in terrestrial ecosystems, but their growth is often influenced by environmental factors and chemical interactions with surrounding vegetation. Fallen leaves are an important source of allelopathic substances, yet little is known about their impact on mosses. This study investigates the allelopathic effects of fallen leaves from Cinnamomum camphora, Pinus massoniana, and Bambusa emeiensis on the bryophyte Thuidium kanedae in Guiyang. The litter aqueous extract (0.0125 g/mL (T1), 0.025 g/mL (T2), 0.05 g/mL (T3), 0.1 g/mL (T4) and distilled water control (CK)) was used to regularly water and culture T. kanedae. During the 120-day test period,… More >

Sheikh Showkat Ahmad¹, Chandni Garg¹, Dalia Fouad², Islam Abdulrahim Alredah³, Sandeep Kaur⁴, Satwinderjeet Kaur^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.11, pp. 3401-3426, 2025, DOI:10.32604/phyton.2025.067984 - 01 December 2025

Abstract The Tragopogon dubius is traditionally used to treat many ailments, consumed as a vegetable, and utilized as fodder for livestock. Tragopogon dubius, found in the Kashmir Himalayas, is the least explored for its bioactivity properties and has a unique geographical location. This study is the first attempt to investigate the antioxidant, anticancer, and genoprotective properties of the aqueous extracts from the leaves (AQ-TrDL) and stems (AQ-TrDS) of this plant. AQ-TrDL and AQ-TrDS demonstrated significant amounts of phenolic and flavonoid contents. GC-HRMS identified various phytochemicals belonging to different classes, like carboxylic acids, fatty acid derivatives, phenols, and triterpenoids.… More >

Guanhui Li^1,2,#, Jiati Tang^1,#, Qifang Zhang³, Guilin Ou^1,3, Yingchao Lin¹, Liping Chen⁴, Xiang Li⁴, Shengjiang Wu¹, Zhu Ren¹, Zeyu Zhao^1,2, Xuekun Zhang², Benbo Xu^2,*, Xun Liu³, Kesu Wei^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.8, pp. 2385-2398, 2025, DOI:10.32604/phyton.2025.068213 - 29 August 2025

Abstract To clarify the relationships between the main chemical components in flue-cured tobacco in Guizhou and field meteorological factors during the tobacco growing period, the contributions of meteorological factors to the chemical composition of flue-cured tobacco and related components were explored in this study. The flue-cured tobacco variety Y87 was used as the experimental material, and tobacco samples and meteorological data were collected from seven typical tobacco-growing areas in Guizhou Province. Using a random forest model and canonical correlation analysis, the impact and contribution of the monthly mean temperature, precipitation, and sunshine duration during the field… More >

Yun Wang^1,2,#, Xin-Yu Li^1,3,#, Sheng-Li Wu^1,3, Pianchou Gongpan¹, Da-Hong Li², Chang-An Geng^1,3,*

Phyton-International Journal of Experimental Botany, Vol.94, No.8, pp. 2563-2574, 2025, DOI:10.32604/phyton.2025.068185 - 29 August 2025

Abstract Twelve lignans (1–12) isolated from Amomum tsao-ko leaves were evaluated for the inhibitory effects against α-glucosidase and PTP1B. Compounds 1−4 and 10 showed inhibition on α-glucosidase with inhibitory ratios ranging from 53.8% to 90.0%, while compound 10 demonstrated 56.1% inhibition on PTP1B at 200 μM. Notably, erythro-5-methoxy-dadahol A (2) and threo-5-methoxy-dadahol A (3) displayed obvious inhibition on α-glucosidase with IC₅₀ values of 33.3 μM and 22.1 μM, significantly outperforming acarbose (IC₅₀ = 344.0 μM). Kinetic study revealed that compound 3 maintained a mixed-type mode, engaging with both free enzyme and enzyme-substrate complex via non-competitive and uncompetitive mechanisms. Molecular docking simulations further clarified its More >

Vijaya Choudhary^1,2,3,*, Paramita Guha^1,2, Giovanni Pau⁴

Journal on Big Data, Vol.7, pp. 1-14, 2025, DOI:10.32604/jbd.2025.065122 - 12 August 2025

Abstract Crop phenotyping plays a critical role in precision agriculture by enabling the accurate assessment of plant traits, supporting improved crop management, breeding programs, and yield optimization. However, cowpea leaves present unique challenges for automated phenotyping due to their diverse shapes, complex vein structures, and variations caused by environmental conditions. This research presents a deep learning-based approach for the classification of cowpea leaf images to support crop phenotyping tasks. Given the limited availability of annotated datasets, data augmentation techniques were employed to artificially expand the original small dataset while preserving essential leaf characteristics. Various image processing More >

Urfa Gul^#, M. Junaid Gul^#, Gyu Sang Choi, Chang-Hyeon Park^*

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3811-3834, 2025, DOI:10.32604/cmc.2025.063789 - 03 July 2025

Abstract Spiking Neural Network (SNN) inspired by the biological triggering mechanism of neurons to provide a novel solution for plant disease detection, offering enhanced performance and efficiency in contrast to Artificial Neural Networks (ANN). Unlike conventional ANNs, which process static images without fully capturing the inherent temporal dynamics, our approach represents the first implementation of SNNs tailored explicitly for agricultural disease classification, integrating an encoding method to convert static RGB plant images into temporally encoded spike trains. Additionally, while Bernoulli trials and standard deep learning architectures like Convolutional Neural Networks (CNNs) and Fully Connected Neural Networks… More >

Lucas Leal Lima¹, Angélica Souza Gouveia¹, Analice Martins Duarte¹, Filipe Schitini Salgado², Nathália Silva Oliveira¹, Monique da Silva Bonjour¹, Iana Pedro da Silva Quadros¹, Maria Goreti Almeida Oliveira¹, Flavia Maria Silva Carmo², Elizabeth Pacheco Batista Fontes¹, Humberto Josué de Oliveira Ramos^1,3,*

Phyton-International Journal of Experimental Botany, Vol.94, No.6, pp. 1787-1810, 2025, DOI:10.32604/phyton.2025.064068 - 27 June 2025

Abstract Sound contains mechanical signals that can promote physiological and biochemical changes in plants. Insects produce different sounds in the environment, which may be relevant to plant behavior. Thus, we evaluated whether signaling cascades are regulated differently by ecological sounds and whether they trigger molecular responses following those produced by herbivorous insects. Soybean plants were treated with two different sounds: chewing herbivore and forest ambient. The responses were markedly distinct, indicating that sound signals may also trigger specific cascades. Enzymes involved in oxidative metabolism were responsive to both sounds, while salicylic acid (SA) was responsive only… More >

Sameera V Mohd Sagheer¹, Orwel P V², P M Ameer³, Amal BaQais⁴, Shaeen Kalathil^5,*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1329-1349, 2025, DOI:10.32604/cmc.2025.063961 - 09 June 2025

Abstract The precise identification of date palm tree diseases is essential for maintaining agricultural productivity and promoting sustainable farming methods. Conventional approaches rely on visual examination by experts to detect infected palm leaves, which is time intensive and susceptible to mistakes. This study proposes an automated leaf classification system that uses deep learning algorithms to identify and categorize diseases in date palm tree leaves with high precision and dependability. The system leverages pretrained convolutional neural network architectures (InceptionV3, DenseNet, and MobileNet) to extract and examine leaf characteristics for classification purposes. A publicly accessible dataset comprising multiple… More >

Bouslamti Mohammed¹, Nouioura Ghizlane¹, Tbatou Widad¹, Mohamed Chebaibi^2,3, Abdulsalam Alhalmi⁴, Najoua Soulo¹, Sulaiman Mohammed Alnasser⁵, Fahad M Alshabrmi⁶, Amine Elbouzidi^7,*, Lyoussi Badiaa¹, Benjelloun Ahmed Samir¹

Phyton-International Journal of Experimental Botany, Vol.94, No.5, pp. 1505-1518, 2025, DOI:10.32604/phyton.2025.063896 - 29 May 2025

Abstract The Solanum genus is known for its diverse bioactive compounds, yet its diuretic potential remains understudied. This research commenced with an analysis of polyphenol and flavonoid content in Solanum elaeagnifolium leaf extract (SEFE) using colorimetric techniques, followed by HPLC-DAD to delineate its chemical composition. The aqueous extract revealed prominent constituents: naringin (12.38%), quercetin 3-O-B-D-Glucoside (27.25%), and flavone (15.26%). A 15-day study on normal rats investigated the diuretic potential of SEFE at repeated doses. SEFE significantly increased urine volume and urinary sodium/potassium levels without inducing hypokalaemia, contrasting with furosemide, a standard diuretic that induced hypokalaemia. Conversely, furosemide, a… More >