Nitrogen requirements of cassava in selected soils of Thailand

Cassava (Manihot esculenta) is one of the most important export crops in Thailand, yet the nitrogen requirement is unknown and not considered by growers and producers. Cassava requirements for N were determined in field experiments during a period of four years and four sites on the Satuk (Suk), Don Chedi (Dc), Pak Chong (Pc),and Ban Beung (BBg) soil series in Lopburi, Supanburi, Nakhon Ratchasima, and Chonburi sites, respectively. The fertilizer treatment structure comprised 0, 62.5, 125, 187.5, 250 and 312.5 kg N ha^(-1) as urea. At each site cassava was harvested at nine months and yield parameters and the minimum datasets were taken. The fertilizer rate which resulted in maximum yield ranged from 187.5 kg N ha^(-1) in Supanburi and Chonburi (fresh weight yield of 47,500 and 30,000 kg ha^(-1) respectively) to 250 kg N ha^(-1) in Lopburi and Nakhon Ratchasima (fresh weight yield of 64,100 and 46,700 kg ha^(-1) respectively). Yield appeared to decrease at the higher, 312 kg ha^(-1), at Supanburi and Lopburi, and 250 kg ha^(-1) (Chonburi) fertilizer N rates. Net revenue was 70.4 and 72.9 % higher than where no N was appliedLopburi and Nakhon Ratchasima sites. Net revenue at the Supanburi and Chonburi sites were 53.8 and 211.0 % higher than that where no N was applied. This study suggests that at all sites improved cassava production and net revenue could be obtained with the judicious application of higher quantities of N. The results provide needed guidance to nitrogen fertilization of the important industrial crop cassava in Thailand.

The prediction of seasonal and inter-annual climate variations and their impacts on the water resources in the eastern seaboard of Thailand

The research of this thesis dissertation covers developments and applications of short-and long-term climate predictions. The short-term prediction emphasizes monthly and seasonal climate, i.e. forecasting from up to the next month over a season to up to a year or so. The long-term predictions pertain to the analysis of inter-annual- and decadal climate variations over the whole 21st century. These two climate prediction methods are validated and applied in the study area, namely, Khlong Yai (KY) water basin located in the eastern seaboard of Thailand which is a major industrial zone of the country and which has been suffering from severe drought and water shortage in recent years. Since water resources are essential for the further industrial development in this region, a thorough analysis of the potential climate change with its subsequent impact on the water supply in the area is at the heart of this thesis research. The short-term forecast of the next-season climate, such as temperatures and rainfall, offers a potential general guideline for water management and reservoir operation. To that avail, statistical models based on autoregressive techniques, i.e., AR-, ARIMA- and ARIMAex-, which includes additional external regressors, and multiple linear regression- (MLR) models, are developed and applied in the study region. Teleconnections between ocean states and the local climate are investigated and used as extra external predictors in the ARIMAex- and the MLR-model and shown to enhance the accuracy of the short-term predictions significantly. However, as the ocean state – local climate teleconnective relationships provide only a one- to four-month ahead lead time, the ocean state indices can support only a one-season-ahead forecast. Hence, GCM- climate predictors are also suggested as an additional predictor-set for a more reliable and somewhat longer short-term forecast. For the preparation of “pre-warning” information for up-coming possible future climate change with potential adverse hydrological impacts in the study region, the long-term climate prediction methodology is applied. The latter is based on the downscaling of climate predictions from several single- and multi-domain GCMs, using the two well-known downscaling methods SDSM and LARS-WG and a newly developed MLR-downscaling technique that allows the incorporation of a multitude of monthly or daily climate predictors from one- or several (multi-domain) parent GCMs. The numerous downscaling experiments indicate that the MLR- method is more accurate than SDSM and LARS-WG in predicting the recent past 20th-century (1971-2000) long-term monthly climate in the region. The MLR-model is, consequently, then employed to downscale 21st-century GCM- climate predictions under SRES-scenarios A1B, A2 and B1. However, since the hydrological watershed model requires daily-scale climate input data, a new stochastic daily climate generator is developed to rescale monthly observed or predicted climate series to daily series, while adhering to the statistical and geospatial distributional attributes of observed (past) daily climate series in the calibration phase. Employing this daily climate generator, 30 realizations of future daily climate series from downscaled monthly GCM-climate predictor sets are produced and used as input in the SWAT- distributed watershed model, to simulate future streamflow and other hydrological water budget components in the study region in a multi-realization manner. In addition to a general examination of the future changes of the hydrological regime in the KY-basin, potential future changes of the water budgets of three main reservoirs in the basin are analysed, as these are a major source of water supply in the study region. The results of the long-term 21st-century downscaled climate predictions provide evidence that, compared with the past 20th-reference period, the future climate in the study area will be more extreme, particularly, for SRES A1B. Thus, the temperatures will be higher and exhibit larger fluctuations. Although the future intensity of the rainfall is nearly constant, its spatial distribution across the region is partially changing. There is further evidence that the sequential rainfall occurrence will be decreased, so that short periods of high intensities will be followed by longer dry spells. This change in the sequential rainfall pattern will also lead to seasonal reductions of the streamflow and seasonal changes (decreases) of the water storage in the reservoirs. In any case, these predicted future climate changes with their hydrological impacts should encourage water planner and policy makers to develop adaptation strategies to properly handle the future water supply in this area, following the guidelines suggested in this study.

Evaluation of the agricultural vocational training programmes conducted by the Krishi Vigyan Kendras (Farm Science Centres) in Indian Punjab

Krishin Vigyan Kendras-KVKs (Farm Science Centres) have been established by the Indian Council of Agricultural Research in 569 districts. The trust areas of KVKs are refinement and demonstration of technologies, and training of farmers and extension functionaries. Imparting vocational trainings in agriculture and allied fields for the rural youth is one of its mandates. The study was undertaken to do a formative and summative (outcome and impact) evaluation of the beekeeping and mushroom growing vocational training programmes in the Indian state of Punjab. One-group pre and post evaluation design was employed for conducting a formative and outcome evaluation. The knowledge tests were administered to 35 beekeeping and 25 mushroom cultivation trainees, before and after the training programmes organized in 2004. The trainees significantly gained in knowledge. A separate sample of 640 trainees, trained prior to 2004, was selected for finding the adoption status. Out of 640, a sample of 200 was selected by proportionate sampling technique out of three categories, namely: non-adopters, discontinued-adopters and continued-adopters for evaluating the long-term impact of these training programmes. Ex-post-facto one-shot case study design was applied for this impact analysis. The vocational training programmes have resulted in continued-adoption of beekeeping and mushroom cultivation enterprises by 20% and 51% trained farmers, respectively. Age and trainee occupation had significant influence on the adoption decision of beekeeping vocation, whereas education and family income significantly affected the adoption decision of mushroom cultivation. The continued adopters of beekeeping and mushroom growing had increased their family income by 49% and 24%, respectively. These training programmes are augmenting the dwindling farm income of the farmers in Indian Punjab.

Farmers’ knowledge and perceptions of potato pests and their management in Uganda

As we initiate entomological research on potato (Solanum tuberosum L.) in Uganda, there is need to understand farmers’ knowledge of existing insect pest problems and their management practices. Such information is important for designing a suitable intervention and successful integrated pest management (IPM) strategy. A farm household survey using a structured questionnaire was conducted among 204 potato farmers in six districts of Uganda (i.e., Kabale, Kisoro, Mbale, Kapchorwa, Mubende, and Kyegegwa) during August and September 2013. Diseases, insect pests, price fluctuations, and low market prices were the four highest ranked constraints in potato production, in order of decreasing importance. Cutworms (Agrotis spp.), aphids (Myzus persicae (Sulzer)), and potato tuber moth (Phthorimaea operculella (Zeller)) were the three most severe insect pests. Ants (Dorylis orantalis Westwood), whiteflies (Bemisia tabaci (Gennadius)), and leafminer flies (Liriomyza huidobrensis (Blanchard)) were pests of moderate importance. Major yield losses are predominantly due to late blight (Phytophthora infestans (Mont.) de Bary) and reached 100% without chemical control in the districts of Kabale, Kisoro, Mbale, and Kapchorwa. On average, farmers had little to moderate knowledge about pest characteristics. The predominant control methods were use of fungicides (72% of respondents) and insecticides (62% of respondents). On average, only 5% of the 204 farmers knew about insect pests and their natural enemies. This lack of knowledge calls for training of both farmers and extension workers in insect pest identification, their biology, and control. Empowering farmers with knowledge about insect pests is essential for the reduction of pesticide misuse and uptake of more environmentally friendly approaches like IPM. Field surveys would need follow-up in order to assess the actual field infestation rates and intensities of each insect pest and compare the results with the responses received from farmers.