宍戸 雅宏

Abstract Our previous study reported that three Paenibacillus strains promoted the bactericidal effect against Ralstonia pseudosolanacearum at low temperatures such as 25 °C for anaerobic soil disinfestation (ASD) (Pitti et al. 2024). The bactericidal effect against R. pseudosolanacearum was lower for ASD at 25 °C because of less production of Fe²⁺ and Mn²⁺ in the soil than ASD at 30 °C. However, the three Paenibacillus strains exhibited antagonistic activity against R. pseudosolanacearum at 25 °C, thereby suppressing the revived growth of the pathogen after ASD. Furthermore, this effect was possible because the three Paenibacillus strains were resistant to the bactericidal properties of Fe²⁺ and Mn²⁺.

Abstract We screened for bacteria that may facilitate the suppressive effect on Ralstonia pseudosolanacearum at temperatures < 30 °C after anaerobic soil disinfestation (ASD) with 1% v/v ethanol. Among 22 isolates grown anaerobically, we selected three that significantly suppressed R. pseudosolanacearum population after ASD at 25 °C. Based on the 16 S rRNA sequences, two isolates were inferred as Paenibacillus polymyxa and the other as Paenibacillus sp. Using qPCR primers designed for these strains, we found that all strains increased in the soil after ASD at 25 °C. After ASD with 1% v/v ethanol and with or without soil inoculation with these three strains in a concrete frame in the field at mean temperature of 26.3 °C, the R. pseudosolanacearum population was significantly lower in the inoculation treatment at a depth of 10 cm. These results suggest that these Paenibacillus strains have the potential to promote the ASD effect using 1% ethanol at low temperatures.

Bacterial Leaf Blight (BLB) is one of the main diseases in Indonesia that causes a 90% reduction in grain weight. Multispectral imaging may be used as a quick and effective method for damage assessment and is expected to utilize on agricultural insurance in Indonesia. Data were collected at the rainy season and dry season 2018 in Farmers rice field at Bali Province. Vegetation indices (NDVI, GNDVI, and VARI_red-edge) was analyzed using QGIS 2.18 from multispectral images. Some vegetation index shows positive correlation with SPAD and negative correlation with DSI (%). VARI_red-edge has a higher relationship with DSI (R²: 0.8443) than NDVI (R²: 0.8291) and GNDVI (R²: 0.5463) at the average value on each location, but the relation seems to be affected by that relation between SPAD and LAI. Further data and analysis are required.