Rice is the most important human food crop in the world. In Bangladesh rice is cultivated throughout the year as Aus, Aman and Boro. Among them boro rice is generally cultivated in November to March. More than half of the total production (55.5%) is obtained in this season. Generally, farmers use more than the recommended number of seedlings during transplanting. The number of seedlings plays a vital role in the growth, development and yield of rice. The aim of this experiment was to determine the number of seedling(s) during transplanting for boro rice varieties for higher growth and yield. This investigation was carried out at the research field of BINA sub-station under Khagrachari sadar upazila in Bangladesh during December 2017 to May 2018. The experiment tested three seedling numbers; S1 (Single), S2 (double), S3 (triple) and four varieties V1 (BRRI dhan-28), V2 (Binadhan-14), V3 (Heera-1), V4 (Shakti-2) in a factorial RCB design with three replications. Results revealed that significantly highest plant height was obtained with treatment S1´V3 (110.30 cm) and S3´V4 (109.4 cm) while the maximum number of tillers/hill from S3´V1 (16.93) and S2´V1 (16.07). In terms of production, treatment combination S3´V4 gave the highest grain (10.40 t/ha), straw (10.40 t/ha) and biological yield (10.40 t/ha). Harvest index was the highest in treatment S1´V4 (59.48). From the above findings it was observed that single seedling performed better than two and three seedlings per hill in terms of getting optimum yield of boro rice varieties. Hence, the rice growing farmers should avoid the use of extra seedlings during transplanting to save labor, time and money.

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The main assets of universities are students. The performance of students plays a vital role in producing excellent graduate students who will be the future viable leader and manpower in charge of a country's financial and societal progress. The purpose of this research is to develop a "University Students Result Analysis and Prediction System" that can help the students to predict their results and to identify their lacking so that they can put concentration to overcome these lacking and get better outcomes in the upcoming semesters. The prediction system can help not only the current students but also the upcoming students to find out exactly what they should do so that students can avoid poor achievement that will help to increase their academic results and other skills. To train the system, we collected data from the university student's database and directly from students by survey using Google form containing information, such as gender, extracurricular activities, no of tuition, programming skills, class test mark, assignment mark, attendance, and previous semester Grade Point Average (GPA), where the main aim is to relate to student performances and Cumulative GPA (CGPA). We use Weka tools to train the system and to develop the decision tree. In decision tree, the acquired knowledge can be expressed in a readable form and produced classification rules that are easy to understand than other classification techniques. These rules used to develop a web-based system that can predict the grade points of students from their previous records. Moreover, the system notifies students' lack and gives suggestions to improve their results. Finally, we compared the performance of three (J48, REPTree, and Hoeffding Tree) different decision tree algorithms, and comparative analysis shows that for our system, the J48 algorithm achieves the highest accuracy.

Background: Bangladesh is one of the densely populated countries in the world. To meet up the increasing food demand there’s no alternative to increase the cropping intensity through high yielding and short duration crop varieties. Currently, cropping system of Bangladesh is mostly rice based which is also the staple food. Therefore, farmers which follow rice-rice based cropping patterns are gaining less profit day by day. Contrary, intensive rice culture is depleting soil properties gradually. Thus, to preserve soil health and increase profit pulse and oil seed based cropping patterns are crucial for sustaining a cropping pattern. This study was undertaken to find out a cropping pattern with higher yield and profit in the context of Magura district.Methods: Five cropping patterns, CP1 = Transplanted Aman rice (cv. Binadhan-7)- Mustard (cv. Binasarisha-9)- Boro rice (cv. Binadhan-14); CP2 = T.Aman (cv. Binadhan-16)-Mustard (cv. Binasarisha-10)- Boro (cv. Binadhan-14); CP3 = T.Aman (cv. Binadhan-17) -Mustard (cv. Binasarisha-10)- Boro (cv. Binadhan-14); CP4 = T.Aman (cv. Binadhan-17)- Lentil (cv. Binamasur-8)- Sesame (cv. Binatil-3) and CP5 (Control) - Aman (cv. Shorna) – Boro (cv. Heera) - fallow were assessed to identify the most suitable and profitable pattern as well as to enhance the cropping intensity by adding a pulse or oil seed crop between two rice crops. The investigation was conducted at farmer’s field of Magura during 2018-19. Block farming method was followed for experiment set up. Result: It was revealed that, maximum rice equivalent yield (REY) was obtained from CP1 (14.46 t/ha) followed by CP4 (13.52 t/ha), CP3 (13.35 t/ha), CP2 (13.09 t/ha) and CP5 (11.33 t/ha) during one year crop cycle. Highest gross margin (Tk. 1,90,189) and MBCR (1.83) was obtained from the cropping pattern CP4 and the lowest gross margin (Tk. 69,271) and MBCR (1.24) was found with the pattern CP5. Based on the above results it can be suggested that, Aman rice-Lentil-Sesame pattern i.e. CP4 may be a best choice for the farmers of Magura region for the maximum utilization of their land and gaining more profit compared to the other studied cropping patterns.

Rice is one of the frontline cereals in the world and the major cultivated crop in Bangladesh. A total of eleven simple sequence repeats (SSRs) and thirteen sequence-tagged site (STS) markers were used to characterize twenty-four rice cultivars in Bangladesh. Twenty-four markers generated 60 alleles with 2.5 alleles per locus. The average polymorphism information content (PIC) value was 0.40, while the mean value of heterozygosity, gene diversity, and major allele frequency were recorded as 0.10, 0.48 and 0.62, respectively. However, the SSR markers showed more specificity and a higher discrimination power than the STS markers. The cluster analysis displayed four major clusters with a genetic similarity coefficient value of 0.73. The morphological analyses of the grain identified that Binadhan-20 and BRRI dhan34 had the longest and the shortest seed size, respectively, with a variable correlation between the seed length, width and length/width ratio. The phenol reaction test distinguished seven cultivars as japonica and seventeen cultivars as indica or an intermediate type. All these results regarding the phenotypic data and marker information will be useful for parental selection in modern rice breeding programmes.