Seed coat colour as an indicator of physiological seed quality - S. Seethaladevi; M. Kathiravan; C. Vanitha; R. Umarani; G. Preetha; S. Marimuthu; M. K. Sakthi Anand (Plant Physiology Reports, 2026)

Imaging technologies for non-invasive detection of insect pest infestations in stored food grains: a review - B. Keerthana; G. Preetha; Umapathi Krishnamoorthy; V. R. Saminathan; T. Eevera; N. Anandaraja; J. Malathi (Journal of Plant Diseases and Protection, 2026)

Gonadal Stage Identification and Oocyte Size Measurement Using DL Integrated Ultrasonography in Asian Sea Bass Lates calcarifer (Bloch, 1790) - Thakkarajan Senthil Murugan; Dani Thomas; Aritra Bera; Marappan Makesh; R. Annie Uthra; J. Preetha Roselyn; Samiappan Dhanalakshmi; Saad Yunus Sait; Sani Meenakshi; Selvam Thamizhazhagan; Govindarajan Thiagarajan; Muniyandi Kailasam; et al. (New Zealand Journal of Marine and Freshwater Research, 2026)
This study investigated gonadal stages in Asian sea bass ( Lates calcarifer ) using portable ultrasonography (Sonosite Edge II, 6–13 MHz), with histological validation of female (primary oocyte, early vitellogenic, ripe) and male (ripe) stages. Distinct echogenicity patterns differentiated sexes, and ultrasound‐based gonad measurements showed strong correlations with actual dimensions (ovary length R 2 = 0.9942, ovary width R 2 = 0.9886, testis length R 2 = 0.9857, testis width R 2 = 0.9793). Deep learning models achieved 99.9% accuracy for sexual maturity prediction (DenseNet‐161) and 99.8% for sex classification (VGG16). CNN regression with L1 and L2 regularization was used to predict oocyte diameters. The MAE (mean absolute error) was 6.31 µm for minimum and 5.20 µm for maximum oocyte diameter, which is less than 1.82% of the actual oocyte diameter (256–544 µm). These results, along with averaging over 10‐fold and small confidence intervals, indicate the robustness of the classification and regression methods. This raises the possibility of automating the classification of the fish reproductive stage by combining deep learning with ultrasound technologies and further developing contactless underwater ultrasonographic assessment of gonadal maturation in commercially important fin fish species. It also reduces the dependency on experts to infer sexual maturation details from ultrasound scans. The developed machine learning model is deployed in real‐time processor, Nvidia Orin, through which real‐time testing is carried out and the results are validated.

Edible synbiotic film based on soy protein reinforced with nanocellulose synthesized from jackfruit residues and probiotic (Lactobacillus pentosus) for feta cheese packaging - B. Pooja; R. Preetha; V. Sreejit; S. Maanila Devi (Food Bioscience, 2026)

Nurses' Knowledge of Hospital Safety in A Tertiary Healthcare Setting - Athirarani M․R․; Ajayan Kamalasanan; Vinoth Raman; Jibina John; Lekshmi R․; Liji C․; Preetha S․; Rejani A․V․; Reshma S․R․; Roshni K․P․ (Next Research, 2025)

Acoustic detection of Callosobruchus maculatus (F.) (Coleoptera: Chrysomelidae) in green gram and cowpea using MEMS microphone system - B. Keerthana; G. Preetha; K. Umapathi; V. R. Saminathan; T. Eevera; J. Malathi; S. Santhi (Journal of Plant Diseases and Protection, 2025)

Anti-lipidemic and anti-diabetic properties of Gymnema sylvestre saponins: an in-silico approach - R. Archana Preetha; G. Dicky John Davis; M. Gowri Neelima; B. S. Chaitra; B. Kirankumar (In Silico Pharmacology, 2025)

Identification and comparative analysis of differential proteins expression in rice under biotic stress by protein sequencing - Subhashini Shinde; P. S. Abida; Manjesh Saakre; Haseena Bhaskar; R. Beena; R. Preetha (Cereal Research Communications, 2024)

Effect of Pulsed Light Treatment for the Preservation of Coconut Inflorescence Sap - V. Vishnu Priya; M. Balakrishnan; R. Pandiselvam; S. Karthikeyan; P. Rajkumar; M. R. Manikantan; K. Gurusamy; P. Preetha (Sugar Tech, 2024)

Discovery of novel microRNAs and their pathogenic responsive target genes in mild traumatic brain injury - Saurav Bhowmick; M. R. Preetha Rani; Shubham Singh; P. M. Abdul-Muneer (Experimental Brain Research, 2023)

Usage pattern of chemicals, biologicals and veterinary medicinal products in Indian aquaculture - Prasanna K. Patil; Sudhansu S. Mishra; Pravata K. Pradhan; Sanjib K. Manna; Jawahar T. Abraham; Haresh G. Solanki; Neetu Shahi; Priyabrata Swain; Satya N. Sahoo; Satheesha Avunje; Krupesha S. R. Sharma; Rajamanickam Geetha; et al. (Reviews in Aquaculture, 2022)
The use of chemicals, biologicals and veterinary medicinal products (VMPs) helps in healthy and sustainable fish production. Information on the use of these products is essential for assessing farming practices, potential human health and environmental risks. A questionnaire‐based nationwide survey covering aquaculture farms ( n = 2936) producing carps, tilapia, pangasius and rainbow trout in freshwater and shrimp in brackishwater estimated the use of 52 different types of inputs which included disinfectants (597 g t −1 ), probiotics (2.28 kg t −1 ), environmental modifiers (22.82 kg t −1 ), nutritional supplements (1.96 kg t −1 ), natural anti‐infective agents (293 g t −1 ), herbicide and piscicides (844 g t −1 ), antibiotics (2 mg PCU −1 ), antifungal (4 mg PCU −1 ), and antiparasitic (14 mg PCU −1 ) agents. The bulk of these inputs was used for soil and water quality improvement and had low environmental and human safety concerns. The multivariate analysis revealed significant variation in the frequency and quantity of compounds use among farm groups. Redundancy analysis revealed a significant association between the number of products used and stocking density. The survey also showed a considerable influence of education and farming experience on the usage pattern of aquaculture inputs. Results of the study indicated greater reliance of farmers on the use of disinfectants for biosecurity, nutritional supplements for enhanced growth and environmental modifiers for maintaining soil and water quality in culture systems. Though there was no use of restricted antibiotics and antiparasitic agents, the development and implementation of standard regulatory guidelines are essential for safe and effective use of inputs for sustainable aquaculture.

Overfishing and Climate Drives Changes in Biology and Recruitment of the Indian Oil Sardine Sardinella longiceps in Southeastern Arabian Sea - Vasant Kripa; Kolliyil S. Mohamed; K. P. Said Koya; R. Jeyabaskaran; D. Prema; Shelton Padua; Somy Kuriakose; P. S. Anilkumar; Preetha G. Nair; T. V. Ambrose; A. M. Dhanya; K. S. Abhilash; et al. (Frontiers in Marine Science, 2018)

Optimization of Culture Conditions for Mass Production of the Probiotics Pseudomonas MCCB 102 and 103 Antagonistic to Pathogenic Vibrios in Aquaculture - R. Preetha; K. K. Vijayan; N. S. Jayapraksh; S. V. Alavandi; T. C. Santiago; I. S. Bright Singh (Probiotics and Antimicrobial Proteins, 2015)

Oral Cancer Knowledge, Behavior, and Attitude Among Osteopathic Medical Students - Zachary R. McCready; Preetha Kanjirath; Bruno C. Jham (Journal of Cancer Education, 2015)

Characterizing trophic interactions of a catfish dominated tropical reservoir ecosystem to assess the effects of management practices - Preetha Panikkar; M. Feroz Khan; V. R. Desai; N. P. Shrivastava; A. P. Sharma (Environmental Biology of Fishes, 2015)

Why conservationists should be concerned about natural resource legislation affecting indigenous peoples’ rights: lessons from Peninsular Malaysia - Sheema A. Aziz; Gopalasamy R. Clements; D. M. Rayan; Preetha Sankar (Biodiversity and Conservation, 2013)

Diazotrophic diversity in the rhizosphere of two exotic weed plants, Prosopis juliflora and Parthenium hysterophorus - B. Cibichakravarthy; R. Preetha; S. P. Sundaram; K. Kumar; D. Balachandar (World Journal of Microbiology and Biotechnology, 2012)

Toxicity of selected insecticides to Trichogramma chilonis: Assessing their safety in the rice ecosystem - G. Preetha; J. Stanley; S. Suresh; S. Kuttalam; R. Samiyappan (Phytoparasitica, 2009)

Impact of Tropical Ecosystem on the Migrational Behavior of K-40, Cs-137, Th-232 U-238 in Perennial Plants - Ajay Kumar; R. K. Singhal; J. Preetha; K. Rupali; U. Narayanan; Sughandhi Suresh; Manish K. Mishra; A. K. Ranade (Water, Air, & Soil Pollution, 2008)

Effect of Fluidizing Agents on Paclitaxel Penetration in Cervical Cancerous Monolayer Membranes - A. Preetha; N. Huilgol; R. Banerjee (The Journal of Membrane Biology, 2007)

Determination of Ultra Trace Level of Uranium in Ground Water of Different Geo-Chemical Environment by Adsorptive Stripping Voltammetry - R. K. Singhal; V. M. Joshi; J. Preetha; Rupali Karpe; Ajay Kumar; A. G. Hegde (Water, Air, & Soil Pollution, 2007)

Purification and characterization of a milk clotting protease from Rhizomucor miehei - S. Preetha; R. Boopathy (World Journal of Microbiology and Biotechnology, 1997)