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

Some Boletes of Thailand

The objective of this study was to collect and identify some Boletes of Thailand. Through periodical excursions in woodland area in the north, northeast and south of Thailand, and regular visits to markets inthe areas during 1995-2005, 20 species of Boletes were collected and identified. These were Boletellus ananas (M.A.Curtis) Murrill, Boletellus emodensis (Berk.) Singer, Boletellus sp. 1, Boletellus sp. 2, Boletellus sp. 3,Boletinus sp., Boletus griseipurpureus Corner, Boletus bicolor Peck, Boletus nanus (Massee.) Singer, Boletus sp. 1, Boletus sp. 2, Boletus sp. 3, Heimiella retispora (Pat. & C.F. Baker) Boedijn, Phlebopus colossus (R.Heim) Singer, Phylloporus pelletieri (Lev.) Quel., Pulveroboletus ravenelii (Berk. & M.A.Curtis) Murrill, Pulveroboletus sp., Strobilomyces confusus Singer, Strobilomyces floccopus (Vahl) P. Karst., and Tylopilusalbo - ater (Schwein) Murrill

Screening of antagonistic bacteria against the green mold disease (Trichoderma harzianum Rifai) of Grey Oyster Mushroom (Pleurotus pulmonarius (Fr.) Quel.)

A total of 174 strains of bacteria antagonistic against the green mold (Trichoderma harzianum), isolated from cultivating bags and fruiting bodies of the mushrooms, were screened for effects on mushroom mycelia and ability to control the green mold disease. Twenty-eight of them promoted the primodia formation of the Pleurotus pulmonarius mycelia on agar plates. Twenty-two isolates were selected and further tested in a mushroom house. Cell suspension of each isolate was prepared and sprayed onto the spawn surface of P. pulmonarius. Fifteen isolates shortened the times required from watering to 2nd and 3rd flushing and increased yield of the basidiocarps by 1.1-34.3% over 30 days. Six isolates of bacteria which showed an inhibitory effect against T. harzianum, enhanced primordia formation and increased yield of P. pulmonarius were selected and used for control testing in a cultivation house. The suspension of each isolate was sprayed onto the spawn surface immediately after exposure to the air in the mushroom house, followed by spore suspension of T. harzianum two days later. The number of infected bags was counted at 30 days after inoculation and the cumulative yield was compared after 60 days. The results showed that bacteria isolate B012-022 was highly effective in suppressing the green mold disease.Only 6.7% of the cultivating bags were found to be infected by T. harzianum when bacteria isolate B012-022 was applied. Cumulative yield obtained from 900 g of 94% sawdust + 5% rice bran + 1% Ca(OH)2 was 300.0 g/bag after 60 days, 71.1% higher than the bags infected by the green mold and without bacterial spraying. Identification of the six bacterial isolates showed all to be Bacillus spp

Fitting pareto distribution with hyperexponential to evaluate the arl for cusum chart

Explicit formulas for the Average Run Length (ARL) of Cumulative Sum (CUSUM) chart are very complicated in regarding the analytical derivation when observations are Long-tailed distributions. The objective of this paper is to fitting Pareto distribution with the hyperexponential distribution to evaluate ARL of CUSUM procedure. The numerical results obtained from analytical solution for the ARL and from numerical approximations are derived and we compared the result with integral equations approach. © 2012 Academic Publications, Ltd