Dataset on utilizing cropping system-based fertilization techniques to improve soil health and crop output while minimizing tillage.

The dataset provided details on how tillage methods and nutrient management impacted the productivity of the four crops (mustard>mungbean>Transplanting (T.) aus >Transplanting (T.) aman) cropping system and the overall soil health. The specific tillage techniques examined were minimum tillage (MT), conventional tillage (CT), and deep tillage (DT). Regarding nutrient management, NM1 utilized 100 % soil test-based (STB) fertilization following fertilizer gradient generation (FRG); NM2 applied 125 % of STB after FRG-2018; NM3 consisted of 100 % STB (with 80 % from chemical fertilizers and 20 % from cow dung); and NM4 relied on native fertility without any fertilization. Over three consecutive seasonal years (2018-19, 2019-20, and 2020-21), twelve treatments were replicated three times following a factorial totally randomized design. The comparative analysis of crop yield, rice equivalent yield, system productivity and production efficiency indicated superior performance of MT over both CT and DT. Furthermore, in relation to agricultural productivity metrics, the application of the nutrition package NM3 demonstrated performance levels exceeding the average. The adoption of MT and the incorporation of the NM3 nutrition package led to notable advancements in organic matter, field capacity, microbial biomass nitrogen, microbial biomass carbon and soil nutrient levels (N, P, K, S, Zn, and B). Consequently, the synthesis of the NM3 with MT is posited as a strategic approach for soil enhancement and the augmentation of crop productivity.

Genotypic selection and trait variation in sweet orange (Citrus sinensis L. Osbeck) dataset of Bangladesh.

The dataset primarily focused on selecting genotypes of sweet oranges based on their phenotypic performances. The dataset resulted significant variations in the best linear unbiased predictions (BLUPs) of 20 out of 21 traits, including leaves, flowers, fruits, and seeds. A strong positive correlation (r= 0.73 to 0.95) was observed among the majority of morphological traits. The sweet orange genotypes demonstrated considerable genetic variance, surpassing 65% for almost all traits, with a selection accuracy exceeding 92%. Using the multi-trait genotype-ideotype distance index (MGIDI), CS Jain-001 emerged as the top-ranked genotype, followed by BAU Malta-3 and CS Jain-002 in order of desirability. The broad sense heritability of selected traits was above 75.60%, and the selection gain reached a maximum of 12.60. These identified genotypes show promise as potential parent donors in breeding programs, leveraging their strengths and weaknesses to develop promising varieties in Bangladesh.

Selection of waterlogging tolerant sesame genotypes (Sesamum indicum L.) from a dataset using the MGIDI index.

The dataset explores the impact of waterlogging stress on sesame plants during the pre-flowering stage, recognizing its global impact on crop yield and the identification of tolerant genotypes using the MGIDI index. Carried out in Bangladesh, the research assesses the survival status, grain yield, and stress tolerance indices of 40 sesame genotypes, revealing that twelve of them demonstrated resilience under 72 h of waterlogging stress at the pre-flowering stage. There were variations in genotypic grain yield, and G15 exhibited the highest yields, recording 5.22 g/plant under normal conditions and 4.10 g/plant under waterlogging stress. The MGIDI index, evaluating waterlogging tolerance, identified G4 as the most favorable genotype, followed by G5 and G12. Factor analysis within the MGIDI index uncovered distinct tolerance and susceptibility indices, highlighting strengths and weaknesses in the selected genotypes. The selection gain percentages of these genotypes ranged from 12.9 to 37.4, indicating high broad-sense heritability (≥0.97). These results underscore the potential of genotype selection based on waterlogging stress indices, providing valuable insights for breeders addressing stress-related crop challenges in the face of changing climatic conditions.

Multi trait stability indexing and trait correlation from a dataset of sweet potato (Ipomoea batatas L.).

A study was conducted in five regions of Bangladesh, specifically Gazipur, Bogura, Jamalpur, Jashore, and Chattogram, each characterized by suitable agro-ecologies for sweet potato cultivation. The purpose of this data article was to demonstrate the correlations between traits and the selection of stable varieties based on the multi-trait stability index (MTSI). The data indicated a direct link between multiple characteristics and both the yield and factors contributing to yield. This implies that enhancing these traits might result in a higher overall production of sweet potato storage roots. Furthermore, the factor analysis for MTSI demonstrated that the desired goal for selection was achieved for all traits, except for mean vine length (VL) and storage root dry weight (DW). The broad sense heritability ranged from 0 to 0.97, and the selection gain percentage ranged from 0 to 42.8. The MTSI analysis identified the sweet potato variety BARI Mistialu-15 as the most stable among the other studied varieties.

Cropping system-based fertilizer strategies for crop productivity and soil health under minimum tillage in grey terrace soil.

A cropping system that is based on three or four crops is currently a widely favored option for augmenting crop productivity to address the escalating global food demand. However, the improper fertilizer management and undue tillage adversely impacts both the productivity of crops and the fertility of the soil. A research investigation was conducted on tillage and nutrient management within the mustard-mungbean-Transplanting aus (T.aus)-Transplanting aman (T.aman) cropping system to examine the impact of fertilizer packages and tillage techniques on the overall productivity of cropping systems, as well as the condition of the soil in grey terrace soil. The research included tillage techniques viz; minimum tillage (MT), conventional tillage (CT) and deep tillage (DT); while nutrient management; NM1: 100 % STB (Soil test based) following FRG (Fertilizer Recommendation Guide-2018), all from chemical fertilizer, NM2: 125 % of STB following FRG- 2018, all from chemical fertilizer, NM3: 100 % STB (80 % from chemical fertilizers and 20 % from cowdung), and NM4: Native fertility (no fertilization). A total of twelve treatments replicated three times following the factorial completely randomized design for three consecutive seasonal years (2018-19, 2019-20, and 2020-21). MT outperformed DT and CT in terms of crop yield, rice equivalent yield (REY), system productivity (SP), and production efficiency (PE). Moreover, NM3 exhibited enhanced performance in terms of agricultural productivity measures. Field capacity (FC), soil organic matter (OM), microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), and soil nutrients (N, P, K, S, Zn and B) observed an enhancement as a result of the implementation of tillage MT and nutrition package NM3. The investigation indicates that implementing minimum tillage (MT) coupled with an integrated plant nutrition system package (NM3) can assist in the improvement of soil and the enhancement of crop productivity.

Yield performance and trait correlation of BARI released sweet potato varieties studied under several districts of Bangladesh.

A study was carried out in five sweet potato growing regions of Bangladesh, each characterized by suitable agro-ecologies, in order to demonstrate the most favorable varietal performance and trait correlations. A completely randomized block design with three replications was used to compare the varietal performance of BARI (Bangladesh Agricultural Research Institute) released sweet potato varieties (viz. BARI Mistialu-9, BARI Mistialu-10, BARI Mistialu-12, BARI Mistialu-15 and BARI Mistialu-17). During the 2021-22 cropping season, sweet potato varieties were tested in five districts of Bangladesh, namely Gazipur, Bogura, Jamalpur, Jashore, and Chattogram. The findings revealed that the BARI Mistialu-12 variety exhibited remarkable attributes, including a high marketable storage root yield of 39.88 t/ha. Additionally, it demonstrated exceptional performance in various yield components such as vine length, average storage root weight, and dry weight of the root. Furthermore, a positive correlation was observed between several traits and yield, as well as yield-attributing characteristics. This correlation suggests that enhancing these traits could potentially contribute to an overall increase in the storage root yield of sweet potatoes.