Stability of Four New Sources of Bacterial Leaf Blight Resistance in Thailand Obtained From Indigenous Rice Varieties

Bacterial leaf blight (BLB) disease caused by Xanthomonas oryzae pv. oryzae (Xoo) is one of the most serious diseases in rice production. Breeding varieties specifically for their resistance to BLB disease is therefore an efficient and cost-effective strategy. However, the resistance gene for BLB can be race and non-race specific, meaning it is often overcome by the pathogen. The identification of new sources of resistance genes for Xoo is crucial in rice breeding programmes. In this study, six rice varieties were assessed using six Xoo isolates in multiple screening conditions. The GGE biplot analysis considers both genotype (G) and genotype environment (GE) interaction effects and demonstrates GE interaction. The first two principal components (PCs) accounted for 95.46% of the total GE variation in the data. Based on lesion length and stability performance, Phaladum was the most ideal genotype against all Xoo isolates in the four screening conditions. The results relayed that Phaladum indigenous rice varieties could be considered as new sources of bacterial leaf blight resistance in Thailand. In the future, the BLB resistance gene in this variety will be identified in regard to mode of inheritance and used as parental line in rice breeding programmes for resistance to BLB

Machine learning for estimation of building energy consumption and performance:a review

Ever growing population and progressive municipal business demands for constructing new buildings are known as the foremost contributor to greenhouse gasses. Therefore, improvement of energy eciency of the building sector has become an essential target to reduce the amount of gas emission as well as fossil fuel consumption. One most eective approach to reducing CO2 emission and energy consumption with regards to new buildings is to consider energy eciency at a very early design stage. On the other hand, ecient energy management and smart refurbishments can enhance energy performance of the existing stock. All these solutions entail accurate energy prediction for optimal decision making. In recent years, articial intelligence (AI) in general and machine learning (ML) techniques in specic terms have been proposed for forecasting of building energy consumption and performance. This paperprovides a substantial review on the four main ML approaches including articial neural network, support vector machine, Gaussian-based regressions and clustering, which have commonly been applied in forecasting and improving building energy performance

Politics and Practice in Second Language Writing Assessment: International Perspectives

Though writing remains an essential means of expressing people’s minds, writing assessment has turned into a politically charged form of social action impacting both individuals and society. Five ESL writing teachers from China, Thailand, and the United States address this concern, discussing the culture of accountability from international perspectives

Politics and Practice in Second Language Writing Assessment: International Perspectives

Though writing remains an essential means of expressing people’s minds, writing assessment has turned into a politically charged form of social action impacting both individuals and society. Five ESL writing teachers from China, Thailand, and the United States address this concern, discussing the culture of accountability from international perspectives