バングラデシュ沿岸域におけるエビ養殖水田の作付体系に関する研究

京都大学0048新制・課程博士博士(地域研究)甲第18394号地博第163号新制||地||55(附属図書館)31252京都大学大学院アジア・アフリカ地域研究研究科東南アジア地域研究専攻(主査)准教授 安藤 和雄, 教授 小林 繁男, 准教授 竹田 晋也学位規則第4条第1項該当Doctor of Area StudiesKyoto UniversityDGA

Performance of locally discovered rice cultivar (Haridhan) in Bangladesh under urea sprays technology

The research work was conducted at the Agronomy Field Laboratory, Department of Agronomy, Bangladesh Agricultural University, Mymensingh during the period from July to November 2015 to evaluate the yield performance of BRRI dhan56 and a locally discovered rice cultivar Haridhan under foliar and traditional application of urea. The experiment included six treatments of urea application technique as T1=N0 (control), T2=N65%, T3=N50%+US (15%), T4=N50%+US (20%), T5=N60%+US (15%), T6=N100% (traditional method) and two rice varieties viz. HYV rice cultivar BRRI dhan56 and locally discovered rice cultivar Haridhan. The experiment was laid out in a randomized complete block design (RCBD) with three replications. Foliar application of urea had significant effect on yield and yield components of BRRI dhan56 and Haridhan. It has been found that the treatment N50%+US (20%) produced highest grain yield (6.14 t ha-1) which might be due to the highest number of total tillers hill-1 (15.03), effective tillers hill-1 (12.11), panicle length (26.21 cm) and grains panicle-1 (156.91) got from this treatment. From the result it can be concluded that both the varieties produced highest grain yield with 50% of the required urea applied to the soil and 20% of the required urea applied as foliar spray that can save an amount of 30% of recommended dose of urea in rice field of Banglades

Agronomic manipulation for adaptation of black rice cultivars in plain land environment to eliminate hidden hunger

Two field experiemtns were conducted at the Agronomy Field Laboratory, Bangladesh Agricultural University, Mymensingh during the period from July 2016 to December 2016 to study the effect of cultivars, date of transplanting and fertilizer dose on the yield and quality of few hilly black rice cultivars. The experiment one consisted of two factors. Factor A: Varieties, viz., i) Galong se and ii) Gelong ni and Factor B: Planting date, viz., i) July 20, ii) August 5, iii) August 20, iv) September 5, v) September 20 and vi) October 5. The experiment two also consisted with two factors. Factor A: varieties, viz., i) Kongnam ene ii) Gelong se and iii) Nazirshail rice and Factor B: Fertilizer management viz., i) No fertilizer ii) 50% of recommended dose (RD) of fertilizers of a local aman rice variety, iii) 75% of RD of fertilizers of a local aman rice variety, iv) 100% of RD of fertilizers of a local aman rice variety, v) 125% of RD of fertilizers of a local aman rice variety and vi) 150% of RD of fertilizers of a local aman rice variety. Results revealed that among varieties, the black rice cultivar Gelong se was best grain yielding potential variety than three other rice varieties, of which two are black rice cultivars (Kongnam ene and Gelong ne) and another one is plain land white rice cultivar (Nizershail). Regarding time of transplanting it has been found that all the varieties gave higher yield when they were transplanted either on July 20 or August 05. The worst transplanting time was October 5 when lowest grain yield was obtained. From the nutritional view point, it has been found that all the three black rice cultivars got higher crude protein (%), crude fibre (%), ash (%), crude fat (%), Fe (ppm) and Zn (ppm) content over white rice cultivar. Therefore, it can be concluded that black rice could be incorporated in human diet and it would be a way of eliminating hidden hunger

Assessment of soil and water quality as affected by herbicide application in the rice field of Bangladesh

Weed is a vital constraint for crop especially rice cultivation. Among several techniques herbicidal weed control is thought to be efficient and cost effective method. But herbicide may change soil or water quality in rice field. Taking this into consideration a study was conducted to assess soil and water quality in herbicide applied rice field. The study was conducted in two phases. In first phase a list of herbicide was made according to the uses by the local farmers of Mymensingh district. It was found that among the herbicides wide used two herbicides were i. Laser (Pyrazosulphuron ethyl-10 WP) and ii. Changer (Acetachlor-14% + Bensulfuron methyl-4%). In the second phase, an experiment was conducted at Agronomy Field Laboratory, Bangladesh Agricultural University, Mymensingh considering these two herbicides. It was found that the application of herbicide in the rice field did not change the nutrient content in the soil or water of rice field. But herbicide significantly reduced the microbial activity and increased the chlorine content (In case of herbicide 2 i.e. Acetachlor-14% + Bensulfuron methyl-4%) in both soil and water of rice field. Therefore, it can be concluded that though the nutrient content of the soil of rice field is not significantly affected by herbicide application but the presence of high amount of Cl content in the rice field may cause burning injury of rice leaf at the early stages of its growth which could affect the yield of rice

Weed competitiveness of winter rice (Oryza sativa L.) under modified aerobic system

The study was conducted during winter season (February-June) of 2016 at the Agronomy Field Laboratory, Bangladesh Agricultural University, Mymensingh. Fourteen rice varieties namely, BRRI dhan28,  BRRI dhan29, BRRI dhan47, BRRI dhan50, BRRI dhan55, BRRI dhan58, BRRI dhan59, BRRI dhan67, Binadhan-5, Binadhan-6, Binadhan-8, Binadhan-10, BRRI hybriddhan3 and Agrodhan14 were grown under weedy and weed- free conditions. Plots with no rice were also maintained to study the natural growth of weed in absence of rice. Primed rice seeds were dry seeded following 25 cm ×15 cm spacing with 5 seeds hill-1 on non-puddled soil. Plots were surface irrigated as and when necessary to maintain aerobic condition (at around field capacity) up to heading stage followed by wet condition from heading to grain filling stage. The results revealed that rice varieties varied widely in yield performance and weed suppressive ability. Among varieties, BRRI dhan59 allowed the minimum weed growth (20.8 g m-2) while Binadhan-5 allowed the maximum weed growth (65.8 g m-2). Grain yield ranged from 2.2 t ha-1 (BRRI dhan55) to 4.67 t ha-1 (Binadhan-5) under weed-free condition and from 0.62 t ha-1 (BRRI dhan55) to 2.48 t ha-1 (BRRI dhan59) under weedy condition. Weed infected relative yield loss ranged from 40.1% to 78.2% among varieties. BRRI dhan59 incurred the least yield penalty (40.1%) while Binadhan-5 performed the best in terms of grain yield (4.67 t ha-1) but its weed inflicted relative yield loss was higher (76.4%) than any other variety with low yield potential. BRRI dhan59, on the other hand, appeared as the most weed competitive variety (only 40.1% relative yield loss) with yield of 4.19 t ha-1. Present study confirms that the varieties tested under study varied widely in terms of weed suppressive ability and yield performance. Considering both yield and weed competitiveness, BRRI dhan59 can be recommended for cultivation following modified aerobic system

Effect of biofertilizer and weeding regimes on yield performance of bush bean (Phaseolus vulgaris L.)

In order to assess the effect of biofertilizer and weeding regimes and their interaction on the performance of bush bean (Phaseolus vulgaris L.), a field experiment was conducted at the Agronomy Field Laboratory, Bangladesh Agricultural University, Mymensingh following randomize complete block design (RCBD) with three replications during winter season, in 2017. The experiment consisted of five treatments of biofertilizer (B0 = no biofertilizer, B1 = 1.0 Kg biofertilizer ha-1, B2 = 1.5 Kg biofertilizer ha-1, B3 = 2.0 Kg biofertilizer ha-1, B4 = 2.5 Kg biofertilizer ha-1) and four level of weeding W0 = No weeding, W1 = One weeding at 15 DAS, W2 = Two weeding at 15 DAS and 30 DAS, W3 = Three weeding at 15 DAS, 30 DAS and 45 DAS. Yield contributing characters were significantly influenced by biofertilizer and weeding regimes. In case of attributes affected by yield factor for biofertilizer the highest plant height, weight of seed plant-1, grain and stover yield in 1.5 Kg biofertilizer ha-1, number of seed plant-1 in 1.0 Kg biofertilizer ha-1, weight of 1000 seeds in no biofertilizer  and harvest index in 2.0 Kg biofertilizer ha-1 treatments were observed. Considering yield attributes against weeding regimes, the highest plant height, grain yield, stover yield and harvest index in three weeding, weight of seeds plant-1 and weight of 1000 seeds in two weeding were found. In case of interaction effect highest plant height in B2W3, weight of seeds plant-1 in B4W2, weight of 1000 seeds in B1W3, grain yield in B3W3, stover yield in B3W3 and harvest index in B0W3 were observed. The results obtained in experiment indicate that there is ample scope to increase the yield of bush bean by applying proper dose of biofertilizer and management of weeding regimes

Effect of variety and spacing on the yield performance of maize (Zea mays L.) in old Brahmaputra floodplain area of Bangladesh

The experiments were conducted at the Agronomy Field Laboratory, Agricultural University, Mymensingh in Bangladesh during December 2015 to April 2016 to investigate the effect of variety and plant spacing on yield attributes and yield of maize. The experiment comprised of five varieties viz., Khoi bhutta, BARI hybrid maize 7, BARI hybrid maize 9, C-1921, P-3396 and five plants spacing viz., 75 cm × 20 cm, 75 cm × 25 cm, 75 cm × 30 cm, 75 cm × 35 cm and 75 cm × 40 cm. The experiment was laid out in a randomized complete block design with three replications.  Results revealed that variety and plant spacing had significant effect on the studied crop characters and yield. The highest plant height, highest number of leaves plant-1, longest cob, maximum diameter of cob, highest number of kernel cob-1, the highest 1000-grain weight, maximum grain yield and stover yield were observed in BARI hybrid maize 7. On the other hand, the shortest plant, lowest number of cob, diameter of cob, lowest number of grains cob-1, 1000-grain weight, grain yield and stover yield were observed in Khoi bhutta. The longest plant, highest cob, maximum diameter of cob, highest number of kernel cob-1 the highest 1000-grain weight, maximum grain yield and stover yield was observed in the spacing of 75 cm × 25 cm. In contrast, the spacing of 75 cm × 30 cm produced the lowest values of the above mentioned plant parameters and also showed the lowest grain yield. In regard to interaction effect of variety and spacing, the highest plant height (232.67 cm), maximum number of cob plant-1 (1.73), maximum diameter of cob (4.60 cm), highest number of kernel cob-1 (34), maximum stover yield (12.38 t ha-1) were observed at the spacing of 75 cm × 25 cm with BARI hybrid maize 7 and resulting in the highest grain yield (9.04 t ha-1). The lowest values of the above parameters were recorded in the narrowest plant spacing of 75 cm × 35 cm with Khoi bhutta. Based on the experimental results, it may be concluded that maize (cv. BARI hybrid maize 7) can be cultivated with a spacing of 75 cm × 25 cm for appreciable grain yield

Improving spatial agreement in machine learning-based landslide susceptibility mapping

Despite yielding considerable degrees of accuracy in landslide predictions, the outcomes of different landslide susceptibility models are prone to spatial disagreement; and therefore, uncertainties. Uncertainties in the results of various landslide susceptibility models create challenges in selecting the most suitable method to manage this complex natural phenomenon. This study aimed to propose an approach to reduce uncertainties in landslide prediction, diagnosing spatial agreement in machine learning-based landslide susceptibility maps. It first developed landslide susceptibility maps of Cox’s Bazar district of Bangladesh, applying four machine learning algorithms: K-Nearest Neighbor (KNN), Multi-Layer Perceptron (MLP), Random Forest (RF), and Support Vector Machine (SVM), featuring hyperparameter optimization of 12 landslide conditioning factors. The results of all the four models yielded very high prediction accuracy, with the area under the curve (AUC) values range between 0.93 to 0.96. The assessment of spatial agreement of landslide predictions showed that the pixel-wise correlation coefficients of landslide probability between various models range from 0.69 to 0.85, indicating the uncertainty in predicted landslides by various models, despite their considerable prediction accuracy. The uncertainty was addressed by establishing a Logistic Regression (LR) model, incorporating the binary landslide inventory data as the dependent variable and the results of the four landslide susceptibility models as independent variables. The outcomes indicated that the RF model had the highest influence in predicting the observed landslide locations, followed by the MLP, SVM, and KNN models. Finally, a combined landslide susceptibility map was developed by integrating the results of the four machine learning-based landslide predictions. The combined map resulted in better spatial agreement (correlation coefficients range between 0.88 and 0.92) and greater prediction accuracy (0.97) compared to the individual models. The modelling approach followed in this study would be useful in minimizing uncertainties of various methods and improving landslide predictions

Innovation activities in developing countries

Innovation is crucial for a country’s economic growth and development as it stimulates productivity and enhances the competitiveness of the firms. R&D investments are one of the most significant inputs to a firm’s ability to innovate. Many studies of firms in developed countries have verified the R&D to innovation relationship; however, there is a void in the literature of studies focusing on the R&D to innovation relationship in developing countries. This dissertation explores and compares the effect of R&D relationships among firms in two developing countries: Bangladesh and Malaysia. Using probit models, I estimate the marginal effect of R&D on the likelihood of a firm being innovative. I find that R&D affects Bangladeshi firms’ innovative behavior more than Malaysian firms. This finding is consistent with the law of diminishing marginal returns and the theory of economic convergence. Namely, this finding implies that after reaching a certain optimum level of innovative capacity, an additional level of R&D input can produce a smaller increase in innovation output, which happens to Malaysian firms. Additionally, the study also finds that larger-sized firms are more innovative. The dissertation concludes with some policy suggestions for Bangladesh’s public sector to consider for the country to be more innovative