Jerusalem artichoke could be an alternative feedstock for bioenergy during times when there are shortages of other raw materials for the ethanol industry. However, insufficient water under rainfed conditions is a major cause of Jerusalem artichoke losses. Genetic variation for drought tolerance is an essential prerequisite for the development of Jerusalem artichoke cultivars with improved drought tolerance. The objectives of this study were to determine the effects of drought stress on tuber dry weight and biomass and to investigate the genotypic variability in Jerusalem artichoke germplasm. The line-source sprinkler technique was used to compare moisture responses of a range of 40 Jerusalem artichoke genotypes grown using 3 water levels. Experiments were conducted on a Yasothon soil series in Northeast Thailand during 2010/11 and 2011/12 and included extended dry periods. Drought reduced tuber dry weight and biomass, and the reductions in tuber dry weight and biomass were greater under severe drought than moderate drought conditions. Over both seasons, CN 52867, HEL 53, HEL 231, HEL 335, JA 76, HEL 65, and JA 102 × JA 89 (8) had consistently high tuber dry weight (1.3 to 4.5 t ha -1 ) and HEL 53, HEL 61, HEL 231, HEL 335, JA 76, JA 15, JA 89, HEL 65, HEL 256, and JA 102 × JA 89 (8) had consistently high biomass (2.0 to 6.8 t ha -1 ). These Jerusalem artichoke genotypes are promising parents in breeding for drought tolerance.

Details on growth and yield for cassava planted on different dates are useful for determining suitable genotypes for particular growing seasons. Our aim was to study growth and yield of cassava planted on different dates. Four cassava genotypes (Kasetsart 50, Rayong 9, Rayong 11 and CMR38-125-77) were evaluated using a randomized complete block design (RCBD) with four replications in six growing periods (

Expanding the area under cultivation and increasing the productivity are two solutions to fulfil the high cassava demand. The objective was to determine the quantum efficiency of photochemistry, relative water content (RWC), growth and biomass of four cassava genotypes grown under rain‐fed upper paddy field conditions. The four cassava genotypes (Kasetsart 50, Rayong 9, Rayong 11 and CMR38–125–77) were evaluated under three environments in rain‐fed upper paddy field conditions in the Khon Kaen province, Thailand, between 2015 and 2017. The experiment used a randomized complete block design (RCBD) with four replications. Data recorded were soil characteristics prior to planting, soil moisture, leaf RWC, chlorophyll fluorescence under natural light (Fv′/Fm′) and artificial dark (Fv/Fm) conditions, total dry weight (TDW), storage root dry weight (SRDW), starch yield and weather data during crop duration. The results from combined analysis indicated that the growing environment had a greater effect than genotypes for RWC (except for RWC at 90 days after planting (DAP), Fv′/Fm′, Fv/Fm, TDW (except for TDW at 150 DAP), SRDW (except for SRDW at 150 DAP) and starch yield. There were significant interactions between genotypes and environments for TDW, SRDW and starch yield. CMR38–125–77 was the superior genotype for growing under rain‐fed upper paddy field conditions when compared to the other three cassava genotypes. This study also showed the possibility of using Fv′/Fm′ and Fv/Fm as criteria to improve the efficiency for cassava varietal selection.

The determination of optimum crop management practices for increasing soybean production can provide valuable information for strategic planning in the tropics. However, this process is time consuming and expensive. The use of a dynamic crop simulation model can be an alternative option to help estimate yield levels under various growing conditions. The objectives of this study were to evaluate the performance of the Cropping System Model (CSM)‐CROPGRO‐Soybean and to determine optimum management practices for soybean for growing conditions in the Phu Pha Man district, Thailand. Data from two soybean experiments that were conducted in 1991 at Chiang Mai University and in 2003 at Khon Kaen University were used to determine the cultivar coefficients for the cultivars CM 60 and SJ 5. The CSM‐CROPGRO‐Soybean model was evaluated with data from two experiments that were conducted at Chiang Mai University. The observed data sets from farmers’ fields located in the Phu Pha Man district were also used for model evaluation. Simulations for different management scenarios were conducted with soil property information for seven different soil series and historical weather data for the period 1972–2003 to predict the optimum crop management practices for soybean production in the Phu Pha Man district. The results of this study indicated that the cultivar coefficients of the two soybean cultivars resulted in simulated growth and development parameters that were in good agreement with almost all observed parameters. Model evaluation showed a good agreement between simulated and observed data for phenology and growth of soybean, and demonstrated the potential of the CSM‐CROPGRO‐Soybean model to simulate growth and yield for local environments, including farmers’ fields, in Thailand. The CSM‐CROPGRO‐Soybean simulations indicated that the optimum planting dates from June 15 to July 15 produced maximum soybean yield in a rainfed environment. However, the planting date December 15 produced the highest yield under quality irrigation. Soybean yield was slightly improved by applying nitrogen at a rate of 30 kg N ha−1 at planting. Soybean yield also improved when the plant density was increased from 20 to 40 plants m−2. The results from this study suggest that the CSM‐CROPGRO‐Soybean model can be a valuable tool in assisting with determining optimum management practices for soybean cropping systems in the Phu Pha Man district and might be applicable to other agricultural production areas in Thailand and southeast Asia.