Browsing by Author "AKTER, MAHMUDA"

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EFFECT OF BIOCHAR ON THE GROWTH AND YIELD OF WHEAT (Triticum aestivum L) UNDER REDUCED IRRIGATED CONDITION
(DEPT. OF SOIL SCIENCE, 2017) AKTER, MAHMUDA
An experiment was conducted at the research field of Sher-e-Bangla Agricultural University, Dhaka-1207, to evaluate the effect of biochar on the growth and yield of wheat ii 1 = 0 t ha , B 3 = 4 t ha -1 , B 5 = 6 t ha -1 , B 6 = 8 t ha -1 -1 , B and three levels of water stress such as W = Regular irrigation, W 2 = Irrigation skipped at booting stage, W =Irrigation skipped at heading and flowering stage. There were 45-unit plots and the size of the plot was 2m × 1.5m i.e. 3m 2 3 . There were 15 treatments combination. Wheat seed of cv. BARI Gom-29 was sown as planting material. The tallest plant -1 2 = 2 t ha 3 B 1 B 1 3 3 B 3 1 B treatment combination. However, it can be concluded that application of biochar can reduce the irrigation frequency without reducing wheat yield significantly. Biochar application in soil can enrich soil organic matter as well as improve soil properties resulting improved aeration and better water holding capacity of soil.
EFFECT OF SOWING DATES ON THE YIELD CONTRIBUTING CHARACTERS AND YIELD OF MUSTARD (Brassica campestris)
(Department of Agricultural Botany, Sher-e-Bangla Agricultural University, Dhaka-1207, 2014-12) AKTER, MAHMUDA
The experiment was conducted in the experimental field of Sher-e-Bangla Agricultural University, Sher-e-Bangla Nagar, Dhaka during the period from November, 2013 to February, 2014 to find out the effect of sowing dates on the yield contributing characters and yield of mustard. The experiment comprised of two factors- Factors A: Sowing date (3 times)- S1: Sowing at 13 November, 2013, S2: Sowing at 20 November, 2013, S3: Sowing at 27 November, 2013, Factor B: Mustard varieties (5 mustard varieties)- V1: SAU Sarisha-14, V2: SAU Sarisha-15, V3: SAU Sarisha-16,V4: SAU Sarisha-18 and V5: BARI Sarisha-15. The two factors experiment was laid out in a Randomized Complete Block Design (RCBD) with three replications. Data on different yield contributing characters and yield were recorded and significant variation was recorded for different treatments. For different sowing dates, at 30, 40, 50, 60 DAS and at harvest, the tallest plant (33.39, 54.89, 71.88, 88.83 and 93.07 cm) was recorded from S2, while the shortest plant (29.46, 50.45, 67.75, 83.79 and 88.30 cm) from S3. The highest number of siliqua per plant was found from S2 (89.27), whereas the lowest number from S3 (80.47). The longest siliqua was observed from S2 (5.07 cm), while the shortest siliqua from S3 (3.91 cm). The highest seed yield was recorded from S2 (1.70 t per ha) and the lowest from S3 (1.37 t per ha). The highest stover yield was found from S2 (2.59 t per ha), while the lowest from S3 (2.16 t per ha). In case of different varieties of mustard, at 30, 40, 50, 60 DAS and at harvest, the tallest plant (34.34, 55.96, 72.76, 89.82 and 93.68 cm) was observed from V4, whereas the shortest plant (29.06, 48.03, 65.59, 81.69 and 86.26 cm) from V1. The highest number of siliqua per plant was obtained from V4 (89.78), while the lowest number from V1 (80.44). The longest siliqua was obtained from V4 (5.00 cm), whereas the shortest siliqua from V1 (4.13 cm). The highest seed yield was recorded from V4 (1.68 t / ha), while the lowest from V1 (1.42 t / ha). The highest stover yield was observed from V4 (2.55 t per ha) and the lowest from V1 (2.25 t per ha). Due to the interaction effect of sowing dates and mustard varieties, at 30, 40, 50, 60 DAS and at harvest, the tallest plant (39.57, 62.60, 76.46, 96.87 and 98.86 cm) was observed from S2V4, while the shortest plant (27.87, 46.20, 63.85, 79.83 and 85.25 cm) from S3V1. The highest number of siliqua per plant was observed from S2V4 (97.67) and the lowest number from S3V1 (76.00). The longest siliqua was observed from S2V4 (6.40 cm), while the shortest siliqua from S3V1 (3.47 cm). The highest seed yield was recorded from S2V4 (1.89 t/ ha), whereas the lowest from S3V1 (1.27 t/ ha). The highest stover yield was observed from S2V4 (2.84 t per ha) and the lowest from S3V1 (2.08 t / ha). Sowing on 20 November and SAU Sarisha-18 was more potential in regards to yield contributing characters and yield of mustard.
IMPACTS OF CLIMATE FACTORS INFLUENCING RICE PRODUCTION IN BANGLADESH
(DEPARTMENT OF AGRICULTURAL STATISTICS, 2019) AKTER, MAHMUDA
The world is under pressure to provide food for its more than 7 billion of citizen right now and by 2050 it is expected that the world will be the home to around 9 billion people. Bangladesh is a densely populated country and home to more than 160 million people which is struggling to manage the sufficient production of rice and wheat. Besides over population burden, climate change has been threatening to food security in Bangladesh as well as in the world. This study was aimed to determine the specific effects of variable on rice production. Climate data has been procured from the Bangladesh Meteorological Department (year 2011-2018) and rice production data were collected from DAE (Department of Agricultural Extension) and BBS (Bangladesh Bureau of Statistics). These data were analyzed using Ordinary Least Squares (OLS), Generalized Least Squares (GLS) and Feasible Generalized Least Squares (FGLS) methods. The results showed that increased climate variability, climate extremes in particular exacerbate risk. Rice yields are sensitive to rainfall extremes, with both deficient and surplus rainfall increasing variability. Additionally, climate inputs, non-climate input, normally, high yielding variety seeds are found to be increasing average in agricultural yield. The results of this study, has shown important policy implication. The higher variability in agricultural production has tendency to greater variability in the earnings of the rural poor who have been experiencing severe financial and credit constraints. Suitable policies are needed to be installed to mitigate climate impacts on agriculture sector to the highest extent.
INFLUENCE OF HUMIC ACID AND NITROGEN ON GROWTH, YIELD AND ECONOMIC RETURN OF ONION
(DEPARTMENT OF HORTICULTURE, 2022) AKTER, MAHMUDA
A field experiment was conducted at Horticulture Farm of Sher-e-Bangla Agricultural University, Dhaka from September 2021 to January 2022 to find out the effect of different level of nitrogen and humic acid on growth, yield and economic return of onion. BARI Piaz-5 was used as test crop material. Three different doses of nitrogen viz., N 0 = 0 kg/ha, N 1 = 80 kg/ha, N 2 = 100 kg/ha and four different doses of humic acid; H 0 = 0 kg/ha, H 1 = 12 kg/ha, H 2 = 14kg/ha, H 3 =16 kg/ha were used to conduct this experiment in a two-factor Randomized Complete Block Design (RCBD) with three replications. Data on growth and yield parameters were gathered and experimental results revealed that different levels of nitrogen and humic acid significantly influenced the growth, yield and economic return of onion. From results it was found that the highest marketable bulb yield (14.60 t/ha) was obtained from N 2 (100 kg/ha nitrogen) treatment while the lowest marketable bulb yield (11.99 t/ha) was obtained from N 0 (0 kg/ha nitrogen). The highest marketable bulb yield (16.82 t/ha) was obtained from H 2 (14 kg/ha humic acid) treatment while the lowest marketable bulb yield (11.81 t/ha) was obtained from H 0 (0 kg/ha humic acid). The highest marketable bulb yield (17.91 t/ha) with the highest Benefit cost ratio (BCR) of 3.11 from N 2 H 2 (100 kg/ha Nitrogen; 14 kg/ha humic acid) treatment combination whereas the lowest marketable bulb yield (9.82 t/ha) with the lowest benefit cost ratio (BCR) of 1.75 from N 0 (0 kg/ha Nitrogen; 0 kg/ha humic acid) treatment combination. From economic point of view, it was apparent from the above results that the combination of N 2 H 2 (100 kg/ha Nitrogen; 14 kg/ha humic acid) treatment was more economically profitable. So, the cultivation of onion with N 2 H 2 (100 kg/ha Nitrogen; 14 kg/ha humic acid) treatment combination was the most suitable treatment combination which promoted the plant growth, yield and economic return.
SPECIES IDENTIFICATION AND MITOCHONDRIAL GENOME SEQUENCING OF FEATHERBACK CHITAL FISH (Chitala chitala)
(DEPARTMENT OF BIOTECHNOLOGY, 2022) AKTER, MAHMUDA
The purpose of this study was to characterize the mitochondrial genome sequencing of Chitala chitala. The complete mitogenome of C. chitala was 16248 bp long and contains 37 mitochondrial genes, including 13 typical protein coding genes, 22 tRNA genes, two ribosomal RNAs (12SrRNA and 16SrRNA), and two non-coding areas (control region, D-loop, and origin of light strand, OL). The heavy (H) strand encoded 28 genes, while the light (L) strand encoded the remaining 9 genes. A total of 31 bp of overlapped area was discovered across the C. chitala mitogenome in 13 distinct places. The mitogenome contained six intergenic spacers totaling 24 bp in length. The longest spacer was an 8-bp nucleotide sequence located between the tRNA and ND1 genes. The 13 protein-coding genes (PCGs) were 11,423 bp in length and accounted for 70.30% of the mitogenome. The base composition was 25.16% T, 29.84% C, 31.4% A, and 13.5% G. C. chitala's circular genome had a short subunit of rRNA (12S rRNA) and a large subunit of rRNA (16S rRNA), both of which were 956 bp and 1702 bp in length, respectively. The 12S rRNA gene had an overall base composition of A = 32.74%, T = 21.75%, C = 25%, and G = 20.50%, while the 16S rRNA gene had an overall base composition of A = 36.13%, T = 19.03%, C = 24.61%, and G = 20.21%. tRNA genes ranged in length from 67 to 76 bp, for a total length of 1,570 bp (9.6% of the total mitogenome). Fourteen tRNA genes were transcribed on the H-strand, while the remaining eight tRNA genes were transcribed on the L-strand. C. chitala's largest non-coding region (control region) consists of 572 nucleotides, accounting for 3.5% of the total mitogenome. The morphologically detected fish species shared 99% of their DNA with C. ornate (Accession No. AP008923.1). Since there is no verified complete mitogenome of Chitala chitala. Currently, it has been considering as a provisional reference sequence (NC_070068.1).