Brown spot (BS) caused by Alternaria alternata is one of the most destructive foliar diseases affecting tobacco (Nicotiana tabacum L.) production and quality in China. Breeding of BS-resistant cultivars is difficult because the resistance has proved to be quantitatively inherited. To facilitate marker-assisted selection, we carried out a study of mapping quantitative trait loci (QTLs) for BS resistance. We developed an F 2 population consisting of 213 individuals from a cross between a BS-susceptible cultivar ÔChangbohuangÕ (CBH) and a BSresistant cultivar ÔJinyehuangÕ (JYH) and constructed a genetic map consisting of 196 simple sequence repeat (SSR) markers based on this population. Using disease index (DI) as the indicator of BS resistance, we detected three QTLs located between SSR markers TM20534 and TM10737, TM10589 and TM10216, and TM10443 and PT60669, respectively. The resistant alleles of the three QTLs were all from the resistant parent JYH. The three QTLs together could explain $86% of the DI difference between the two parents in total, with $61% explained by their additive effects. Therefore, the three QTLs will be useful for BS-resistance breeding.

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Insulated gate bipolar transistor (IGBT) is widely used in power equipment, it generally works in complex circuit profiles and it is very difficult to measure or predict the thermal parameters of the module in real-time and evaluate the corresponding health status in the transient process. This paper develops a novel approach for solder-layer condition monitoring of IGBTs. In the approach a time-series nonparametric model of a power module is constructed, the current power and ambient temperature data are used to deduce the health state junction and case temperature. Three groups of time-series insulated gate bipolar transistors (IGBTs) data are used to train and verify the time-series nonparametric model for online conditions, the results show that the developed method has high accuracy. Compared with traditional methods, the time series non-parametric model method not only saves characteristic experiments but also saves the process of mathematical model construction. Besides, the proposed method also has the advantages of strong generalization and low equipment requirements which is useful for actual working conditions. Thereafter, another nonparametric model is built, the predicted junction temperature is used to estimate the collector voltage in the health state, and the percentage deviation of the measured collector voltage from the estimated voltage is used to do the state-of-health estimation of the IGBT and its accuracy is verified by the experiment result.INDEX TERMS IGBT, time-series ANN, state-of-health, junction temperature, artificial intelligence