Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Wallacea Plant Protection Journal

Laboratory assessment of the consumption rate of Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) on a mung bean (Vigna radiata)-based artificial diet Sulaeha, Sulaeha; Uleng, Andi Nadya Tenri; Junaid, Muhammad
Wallacea Plant Protection Journal Vol. 1 No. 1 (2025)
Publisher : Department of Plant Pest and Diseases, Faculty of Agriculture, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64128/wppj.v1i1.42067

Abstract

Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) is an invasive pest in Indonesia. Therefore, limited insect stock is a limiting factor for researchers. The aim of this research rearing insects with mung bean-based as a protein source to modify the composition of the artificial diet. The parameters observed in this research were larva period, larval survival rate, pupal size, sex ratio, pupal-stage longevity, pupal survival rate, fecundity, and nutritional index. The results showed that an artificial diet with mung bean had a significant effect on sex ratio, pupal survival rate, efficiency of conversion of ingestion (ECI) food, efficiency of conversion digested (ECD) food, approximate digestibility (AD) 96,54% 4th instar; 95.45% 5th instar: 88,35% 6th instar, fecundity 307,14 eggs/female, pupal period and significant effect on larval period though instars are longer. Artificial diet-based mung bean had high potential for use in S. frugiperda rearing.
Global trend of agricultural precision for plant pathology: Bibliometric study in Scopus database Junaid, Muhammad; Taib, Nurlaila S.; Sukmawati, Sukmawati; Zabrina, Gita
Wallacea Plant Protection Journal Vol. 1 No. 1 (2025)
Publisher : Department of Plant Pest and Diseases, Faculty of Agriculture, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64128/wppj.v1i1.42069

Abstract

This bibliometric study investigates the global trends in agricultural precision within plant pathology, utilizing data from the Scopus database. This research identifies key research hubs, influential authors, and emerging themes in the domain by analyzing publication patterns, citation metrics, and keyword co-occurrence. The study highlights the increasing integration of advanced technologies such as remote sensing, machine learning, and big data analytics in plant pathology research. The findings underscore the growing emphasis on precision agriculture to enhance disease detection, management, and crop productivity. This comprehensive analysis provides valuable insights for researchers, policymakers, and practitioners aiming to leverage technological advancements for sustainable agricultural practices.