International Seminar on Plant Protection

Attractiveness of Fruit Flies (Diptera: Tephritidae) to Eco-Enzyme and Tape Yeast Mixtures on Cayenne Pepper (Capsicum frutescens L.)

2026-11-02T05:01:26+00:00

Fruit flies (Diptera: Tephritidae) are important pests of cayenne pepper that can reduce fruit quality and yield. This study aimed to evaluate the effectiveness of eco-enzyme and ragi tape mixtures as attractants for fruit flies on cayenne pepper (Capsicum frutescens L.) cv. ORI 212. The experiment was conducted from February to July 2026 at the Experimental Field Faculty of Agriculture Lambung Mangkurat University Banjarbaru Indonesia. A completely randomized design was used with six treatments and four replications. The treatments consisted of methyl eugenol (P0), eco-enzyme and ragi tape mixtures at ratios of 1:1 (P1), 1:2 (P2) and 2:1 (P3), eco-enzyme alone (P4) and ragi tape plus sugar (P5). Data were subjected to analysis of variance followed by the least significant difference test at the 5% level. Methyl eugenol (P0) produced the highest mean fruit fly catch (39.46 flies) and the longest attractant longevity (6.75 days). Among the fermentation-based treatments, P3 showed the best overall performance with a mean catch of 32.39 flies, the lowest mean infestation intensity (17.90%) and the highest total fruit yield (394.25 g). Four fruit fly species were identified with Bactrocera dorsalis being the dominant species, accounting for 67.07% of the total catch. These findings indicate that the 2:1 eco-enzyme and ragi tape mixture has potential as a fermentation-based attractant for integration into fruit fly management in cayenne pepper production.

AI-Assisted Detection of Major Pests in Red Chili Plants: Accuracy–Efficiency Trade-offs of YOLO11 Variants

2026-11-02T04:10:33+00:00

Reliable and timely pest detection is essential for protecting red chili plants and supporting effective pest monitoring. However, automated detection remains challenging because agricultural pests are often small, densely distributed, visually similar, and observed against complex natural backgrounds. This study evaluates the accuracy–efficiency trade-offs of three YOLO11 model variants—YOLO11n, YOLO11s, and YOLO11m—for detecting major pests in red chili plants. Experiments were conducted using 4,957 annotated images containing 10,561 bounding boxes representing four pest classes: Bemisia tabaci, caterpillar, Myzus persicae, and thrips. All models were initialized with pretrained weights and trained under a controlled experimental protocol using identical data splits, an input resolution of 640 × 640 pixels, a maximum of 100 epochs, and early stopping. Detection performance was evaluated using precision, recall, mAP50, and mAP50–95. YOLO11n achieved the highest test mAP50 of 0.700 and mAP50–95 of 0.310 with only 2.591 million parameters. YOLO11s obtained an mAP50–95 of 0.298 at 81.31 frames per second, whereas YOLO11m achieved 0.283 at 34.23 frames per second despite producing the highest recall of 0.754. The results demonstrate that increasing model capacity does not necessarily improve pest localization performance. Among the evaluated variants, YOLO11n provides the most favorable balance between detection accuracy and computational efficiency, indicating its potential as a lightweight model for real-time AI-assisted pest monitoring in red chili cultivation.

Species Composition of Rice Stem Borers in Bone Regency, South Sulawesi

2026-11-02T03:20:11+00:00

Rice stem borers are one of the important pest groups in rice plants that can cause damage during both the vegetative and generative stages and potentially reduce yield. Information on the species composition of rice stem borers in a given region is needed to determine the presence and dominance of species as a basis for effective pest management. The purpose of this study is to determine the species composition of rice stem borers collected from rice fields in Bone Regency, South Sulawesi. Adult insects were collected using two methods: confining rice plants showing deadheart symptoms for approximately 15 days and setting up light traps for one growing season. The adults collected were identified based on their morphological characteristics, and the proportion of each species was then calculated. The results of the plant enclosure experiment showed two species: Scirpophaga innotata (70%) and Scirpophaga incertulas (30%). Meanwhile, the light traps yielded three species: S. innotata (57.39%), S. incertulas (36.45%), and Chilo suppressalis (6.16%). Overall, the species composition of rice stem borer pests in Bone Regency consists of S. innotata, S. incertulas, C. suppressalis and Sesamia inferens. Scirpophaga innotata is the most dominant species based on the proportion of adults collected through plant trapping and light traps.