Crop diversity through residue incorporation is the most important method for sustaining soil health. A field study was conducted over five consecutive years (2012–2017) to see the impact of residue incorporartions in Inceptisol of eastern India. The main plot treatments had five cropping systems (CS), namely, fallow−rice−rice (FRR), jute−rice−wheat (JRW), jute−rice−baby corn (JRBc), jute−rice−vegetable pea (JRGp), jute−rice−mustard−mungbean/green gram (JRMMu), which cinsisted of four sub-plots with varied nutrient and crop residue management (NCRM) levels, namely crops with no residue +75% of the recommended dose of fertilizers (RDF) (F₁R₀), crops with the residue of the previous crops +75% RDF (F₁R₁), crops with no resiude +100% RDF (F₂R₀), and crops with residue +100% RDF (F₂R₁). The highest system productivity was obtained for JRBc (15.3 Mg·ha⁻¹), followed by JRGp (8.81 Mg·ha⁻¹) and JRMMu (7.61 Mg·ha⁻¹); however, the highest sustainability index was found with the JRGp cropping system (0.88), followed by JRMMu (0.82). Among the NCRMs, the highest productivity (8.78 Mg·ha⁻¹) and sustainability index (0.83) were recorded in F₂R₁. Five soil parameters, namely, bulk density, available K, urease activity, dehydrogenase activity, and soil microbial biomass carbon (SMBC), were used in the minimum data-set (MDS) for the calculation of the soil quality index (SQI). The best attainment of SQI was found in the JRGp system (0.63), closely followed by the JRMMu (0.61) cropping system.

Despite the growing importance of soil and water conservation and watershed development projects as an approach to rural development and natural resource management, there has been relatively little research on devising site-specific best management practice (BMP) to check the soil erosion losses within permissible limits, especially in hilly regions. For a sustainable watershed management programme and implementation, site specific BMPs assume importance and hold the promise of making conservation planning and watershed management simpler and more effective. The study was attempted to develop a methodology to obtain BMPs, aiming to reduce the erosion losses in erosion risk areas of the northwestern Himalayas by employing Analytic Hierarchy Process (AHP). The AHP technique was employed to prioritise the potential technologies and select the BMP suitable for a particular land area. The prioritization of technologies was performed with four criteria viz. soil erosion resistance, cost, benefit, maintenance and environment friendliness of conservation measures. The soil erosion scenario of the study area located in the northwestern Himalayas was generated with each selected measure in a SWAT model using DEM, land use maps, a soil map and climate data of the study area. Then, the resultant erosion scenario of the conservation measures was compared and used for the AHP analysis. However, other criteria were assessed based on the judgement of a group of experts as well as farmers. In this study, four conservation measures, viz. Bench Terraces (BT), Vegetative Barrier (VB), Contour Farming (CF) and Zero Tillage + Live Mulch (ZL), were considered for BMP selection. Three scenarios, viz. experts’ judgement, farmers’ opinions and combined expert and farmer opinion, were analyzed to uncover the BMP for the different zones. The result revealed that experts and farmers unanimously preferred ZL as a BMP because of its low-cost implementation value and lower maintenance requirement while significantly controlling the erosion level as well as being environment friendly. The BT was the second most preferred technology for the study area. However, BMP was recommended for different zones having high to very severe erosion (soil loss > 10 t/ha/yr). Therefore, ZL was recommended for the areas with low altitude, whereas BT was recommended for the areas having high slopes because of its high capability for erosion control in the high slopping area. The methodology will act as a useful strategy for decision makers to prioritize the technology and recommend the best management for any region after considering suitable criteria. Future work may consider more criteria for inclusion to thus recommend the technology for a region in a more realistic way.

Rainfall serves as a lifeline for crop cultivation in many agriculture-dependent countries including India. Being spatio-temporal data, the forecasting of rainfall becomes a more complex and tedious process. Application of conventional time series models and machine learning techniques will not be a suitable choice as they may not adequately account for the complex spatial and temporal dependencies integrated within the data. This demands some data-driven techniques that can handle the intrinsic patterns such as non-linearity, non-stationarity, and non-normality. Space–Time Autoregressive Moving Average (STARMA) models were highly known for its ability to capture both spatial and temporal dependencies, offering a comprehensive framework for analyzing complex datasets. Spatial Weight Matrix (SWM) developed by the STARMA model helps in integrating the spatial effects of the neighboring sites. The study employed a novel dataset consisting of annual rainfall measurements spanning over 50 (1970–2019) years from 119 different locations (grid of 0.25 × 0.25 degree resolution) of West Bengal, a state of India. These extensive datasets were split into testing and training groups that enable the better understanding of the rainfall patterns at a granular level. The study findings demonstrated a notable improvement in forecasting accuracy by the STARMA model that can exhibit promising implications for agricultural management and planning, particularly in regions vulnerable to climate variability.

Ramie (Boehmeria nivea) is a perennial herbaceous plant which produces strong and lustrous bast fibre. It is native to East Asia and is mainly grown in china, India, Taiwan, Philippines, Thailand, Brazil, and South Korea (Sarkar et al. 2012). In May 2013, ramie plants exhibiting yellow mosaic symptoms were noted in experimental fields of the CRIJAF research farm, Barrackpore, India. In young green leaves vein-clearing was prominent, whereas the older leaves showed complete yellowing. Plants were stunted and bushy. The incidence of the disease varied from 2% to 10 %. Five symptomatic and five asymptomatic samples were collected from the field and DNA was extracted by using CTAB method (Biswas et al. 2013). DNA samples were tested for begomovirus infection by PCR using universal primer pair PAL1v1978B/PAR1c715H (Rojas et al. 1993). Only the symptomatic samples showed amplification of a 1.5 kb product suggesting that plants were infected by a begomovirus. Furthermore, circular DNA was amplified by rolling circle amplification (RCA) with Illustra TempliPhi Kit (GE Healthcare, UK) according to the manufacturer’s instructions. RCA product was digested with EcoRI, BamHI, EcoRI, KpnI, Hind III and PstI (New England Biolabs) respectively. The fragments of 2.1 kbp (with BamHI digestion) and 1.5 kbp (with KpnI digestion) were cloned and sequenced. The sequence of the 2.1 kbp fragment showed similarity with published sequences of begomovirus DNA-A component. From 2.1 kbp sequence a pair of primers was designed to obtain full length DNA -A component viz. JAF1 (5′-CTTCATCGTTTCTCAGCATCAT-3′) and JAR1 (5′-CACTTGCACACGATCTCTAAGA-3′). The full-length DNA-A was 2686 bp nucleotides and encoded six putative ORFs (GenBank Accession No. KF962542). The sequence of the 1.5 kbp fragment shared similarity with DNA-B. The begomoviral circular DNA-B was amplified using the pair of primers JBF1 (5′-GTAACACCCGAAGTGCACG-3′) and JBR1 (5′-AAAGGAGAGACACCAGTCTGCC-3′) designed from the 1.5-kbp sequence. PCR yielded full-length DNA-B sequence of 2666 bp nucleotides and encoded two putative ORFs (GenBank Accession No. KF962543). BLASTn analysis revealed that DNA-A from the ramie begomovirus isolate has 100% nucleotide sequence identity with complete sequence of DNA-A component of Corchorus golden mosaic virus (Accession no: FJ463902). Similarly, DNA-B also has 100% identity with complete sequence of CoGMV DNA-B component (Accession no: FJ455448). Based on BLASTn analysis and sequence analysis using MEGALIGN (DNASTAR), the virus causing symptoms in ramie appears to be CoGMV which is a New World begomovirus from the Old World infecting jute (Corchorus capsularis) (Ha et al. 2006). To the best of our knowledge this is the first report that CoGMV infects ramie plants. The incidence of CoGMV in ramie is relatively low but in future it may negatively affect the yield. References: Biswas, C. et al., 2013. Lett. Appl. Microbiol. 56:105. Ha, C. et al., 2006. J.Gen. Virol. 87:997. Rojas, M R. et al., 1993. Plant Dis. 77:340. Sarkar, D. et al., 2012. Curr. Sci. 98:1570.