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Abstract Linseed or flaxseed, native to the Indian subcontinent, had undergone domestication, edaphic selection and evolutionary processes that may have resulted in huge genetic variability in Indian genotypes. To understand the hitherto unexplored genetic diversity for sustainable flaxseed production amid challenges of climate fluctuation and identify trait-specific high-yielding genotypes, 2576 unique linseed accessions were comprehensively evaluated for 36 traits for up to six environments representing two major agroecological zones in India. A wide range of variability was recorded for days to initiation of flowering (42.86–114.99), plant height (43.31–122.88 cm), capsules/plant (64.62–375.87), seed size (6.06–14.44 cm2), thousand seed weight (2.80–11.86 g), seed yield (2.93–17.28 g/plant), oil content (30.14–45.96%) and fatty acid profile especially the key constituent omega-3 fatty acid (25.4–65.88%). Most of the traits such as plant height, flowering time, seed yield, seed and capsule size showed a high or moderately high level of variance coupled with high broad sense heritability indicating precise capturing of less heritable quantitative traits. The infraspecific classification of the tested collection revealed the seed/oil type (2498 accessions) as the dominant morphotype over dual-purpose/fiber flax (78 accessions) in the conserved collection. Correlation analysis indicated a significant positive association between flowering time, plant height, days to maturity and oil content. Trait-specific superior genotypes for earliness (50% flowering in 11 g), capsules/plant (> 350), oil content (> 45%) and fatty acid composition (> 65% alpha-linolenic acid) were identified to aid genetic improvement of linseed and to broaden the narrow genetic base.

Abstract Agricultural field experiments are costly and time-consuming, and often struggling to capture spatial and temporal variability. Mechanistic crop growth models offer a solution to understand intricate crop-soil-weather system, aiding farm-level management decisions throughout the growing season. The objective of this study was to calibrate and the Crop Environment Resource Synthesis CERES-Maize (DSSAT v 4.8) model to simulate crop growth, yield, and nitrogen dynamics in a long-term conservation agriculture (CA) based maize system. The model was also used to investigate the relationship between, temperature, nitrate and ammoniacal concentration in soil, and nitrogen uptake by the crop. Additionally, the study explored the impact of contrasting tillage practices and fertilizer nitrogen management options on maize yields. Using field data from 2019 and 2020, the DSSAT-CERES-Maize model was calibrated for plant growth stages, leaf area index-LAI, biomass, and yield. Data from 2021 were used to evaluate the model's performance. The treatments consisted of four nitrogen management options, viz., N0 (without nitrogen), N150 (150 kg N/ha through urea), GS (Green seeker-based urea application) and USG (urea super granules @150kg N/ha) in two contrasting tillage systems, i.e., CA-based zero tillage-ZT and conventional tillage-CT. The model accurately simulated maize cultivar’s anthesis and physiological maturity, with observed value falling within 5% of the model’s predictions range. LAI predictions by the model aligned well with measured values (RMSE 0.57 and nRMSE 10.33%), with a 14.6% prediction error at 60 days. The simulated grain yields generally matched with measured values (with prediction error ranging from 0 to 3%), except for plots without nitrogen application, where the model overestimated yields by 9–16%. The study also demonstrated the model's ability to accurately capture soil nitrate–N levels (RMSE 12.63 kg/ha and nRMSE 12.84%). The study concludes that the DSSAT-CERES-Maize model accurately assessed the impacts of tillage and nitrogen management practices on maize crop’s growth, yield, and soil nitrogen dynamics. By providing reliable simulations during the growing season, this modelling approach can facilitate better planning and more efficient resource management. Future research should focus on expanding the model's capabilities and improving its predictions further.

Diffuse reflectance spectroscopy (DRS) is an emerging soil testing approach. Although several studies have validated the DRS approach, limited efforts are made to assess the applicability of calibrated DRS models on new samples collected at different locations and/or time. To test such spatio-temporal applicability of calibrated DRS models, we collected surface soil samples from 1,112 smallholder farms during 2018 (T2018) and 607 farms during 2021 (T2021) covering seven districts of the Bundelkhand region of central India. The T2018 samples covered 7 development blocks; the T2021 samples were also collected from these blocks but from different sampling locations. Additionally, a new sampling site (Jhansi-Bamour block) was added during 2021 to create an independent test dataset. Collected samples were analysed for 17 soil parameters (basic soil properties, macronutrients, and micronutrients) and spectral reflectance over the visible to near-infrared region. Corresponding soil test crop response (STCR) ratings were also estimated. The Cubist model was calibrated in the T2018 dataset and tested against the T2021 dataset using the coefficient of determination (R2), root-mean-squared error (RMSE), and percentage relative error deviation (PRED) at 30% error threshold as performance statistics. Model applicability was assessed at each block level (site-specific), by dividing the study site into their two geology-specific regions, and by treating the entire dataset as a regional-scale spectral library. Results showed that DRS models calibrated on a finer scale (site-specific) are less efficient in estimating soil parameters in broader scale (geology-specific and regional-scale) test T2021 samples although their STCR ratings may safely be estimated at local scales. When site-specific data were aggregated to broader scales and T2018 dataset was spiked with 20% samples from the T2021 dataset, model performance improved for critical soil parameters such as soil organic carbon (SOC) contents and several plant nutrients and their ratings; application of such large-scale models also improved the estimation accuracy when applied to site-specific datasets. Exchangeable Ca and Mg, clay and SOC contents were frequently well-estimated with R2 values ranging from 0.54 to 0.93. Fine sand was the next best estimated soil property with R2 values in the range of 0.40–0.75. The STCR ratings estimated in the DRS approach matched the wet chemistry-based STCR ratings to the tune of 43 to 100%. Overall, as many as 60% of all new samples could be estimated with more than 70% accuracy for 8 out of 17 parameters. With the DRS approach tested on both spatially- and temporally-independent test datasets and, specifically, with high estimation accuracy of STCR ratings, our results suggest that the DRS approach may safely be used as a viable alternative to conventional soil testing in smallholder farms.

Abstract This paper presents our findings on the recursive band gap engineering of chiral fermions in bilayer graphene doubly aligned with hBN. Using two interfering moiré potentials, we generate a supermoiré pattern that renormalizes the electronic bands of the pristine bilayer graphene, resulting in higher order fractal gaps even at very low energies. These Bragg gaps can be mapped using a unique linear combination of periodic areas within the system. To validate our findings, we use electronic transport measurements to identify the position of these gaps as a function of the carrier density. We establish their agreement with the predicted carrier densities and corresponding quantum numbers obtained using the continuum model. Our study provides strong evidence of the quantization of the momentum-space area of quasi-Brillouin zones in a minimally incommensurate lattice. It fills important gaps in the understanding of band structure engineering of Dirac fermions with a doubly periodic superlattice spinor potential.

Abstract Global trends show that the rapid increase in maize production is associated more with the expansion of maize growing areas than with rapid increases in yield. This is possible through achieving possible higher productivity through maize production practices intensification to meet the sustainable production. Therefore, a field experiment on “Ecological intensification of climate-resilient maize–chickpea cropping system” was conducted during consecutive three years from 2017–2018 to 2019–2020 at Main Agricultural Research Station, Dharwad, Karnataka, India. Results of three years pooled data revealed that ecological intensification (EI) treatment which comprises of all best management practices resulted in higher grain yield (7560 kg/ha) and stover yield compared to farmers’ practice (FP) and all other treatments which were deficit in one or other crop management practices. Similarly, in the succeeding winter season, significantly higher chickpea yield (797 kg/ha) was recorded in EI. Further EI practice recorded significant amount of soil organic carbon, available nitrogen, phosphorus, potassium, zinc, and iron after completion of third cycle of experimentation (0.60%, 235.3 kg/ha,21.0 kg/ha,363.2 kg/ha,0.52 ppm and 5.2 ppm respectively). Soil enzymatic activity was also improved in EI practice over the years and improvement in each year was significant. Lower input energy use was in FP (17,855.2 MJ/ha). Whereas total output energy produced was the highest in EI practice (220,590 MJ ha−1) and lower output energy was recorded in EI–integrated nutrient management (INM) (149,255 MJ/ha). Lower energy productivity was noticed in EI-INM. Lower specific energy was recorded in FP and was followed by EI practice. Whereas higher specific energy was noticed is EI–INM. Each individual year and pooled data showed that EI practice recorded higher net return and benefit–cost ratio. The lower net returns were obtained in EI-integrated weed management (Rs. 51354.7/ha), EI-recommended irrigation management (Rs. 56,015.3/ha), integrated pest management (Rs. 59,569.7/ha) and farmers’ practice (Rs. 67,357.7/ha) which were on par with others.

Abstract A 3-year field experiment was setup to address the threat of underground water depletion and sustainability of agrifood systems. Subsurface drip irrigation (SDI) system combined with nitrogen management under conservation agriculture-based (CA) maize-wheat system (MWS) effects on crop yields, irrigation water productivity (WPi), nitrogen use efficiency (NUE) and profitability. Grain yields of maize, wheat, and MWS in the SDI with 100% recommended N were significantly higher by 15.8%, 5.2% and 11.2%, respectively, than conventional furrow/flood irrigation (CT-FI) system. System irrigation water savings (~ 55%) and the mean WPi were higher in maize, wheat, and MWS under the SDI than CT-FI system. There was saving of 25% of fertilizer N in maize and MWS whereas no saving of N was observed in wheat. Net returns from MWS were significantly higher (USD 265) under SDI with 100% N (with no subsidy) than CT-FI system despite with higher cost of production. The net returns were increased by 47% when considering a subsidy of 80% on laying SDI system. Our results showed a great potential of complementing CA with SDI and N management to maximize productivity, NUE, and WPi, which may be economically beneficial and environmentally sound in MWS in Trans-IGP of South Asia.

Abstract Corn-leaf aphid (CLA-Rhopalosiphum maidis) is a major insect pest of barley (Hordeum vulgare) causing yield loss upto 30% under severe infestation. Keeping in view of the availability of very few sources of CLA resistance in barley, the present investigation was framed to assess the genetic diversity and population structure of 43 wild barley (H. vulgare subsp. spontaneum) genotypes using eight microsatellite markers against R. maidis. Three statistical methods viz. multivariate-hierarchical clustering, Bayesian clustering and PCoA, unanimously grouped genotypes into three subpopulations (K = 3) with 25.58% (SubPop1-Red), 39.53% (SubPop2-Green) and 34.88% (SubPop3-Blue) genotypes including admixtures. Based on Q ≥ 66.66%, 37.20% genotypes formed a superficial “Mixed/Admixture” subpopulation. All polymorphic SSR markers generated 36 alleles, averaging to 4.5 alleles/locus (2–7 range). The PIC and H were highest in MS31 and lowest in MS28, with averages of 0.66 and 0.71. MAF and mean genetic diversity were 0.16 and 89.28%, respectively. All these parameters indicated the presence of predominant genetic diversity and population structure amongst the studied genotypes. Based on AII, only 6 genotypes were found to be R. maidis resistant. SubPop3 had 91.66% (11) of the resistant or moderately resistant genotypes. SubPop3 also had the most pure genotypes (11), the least aphid infestation (8.78), and the highest GS (0.88), indicating its suitability for future R. maidis resistance breeding initiatives.

Unremitting decline in crop productivity and nutrient recovery are resulted due to dearth of need based fertilizer recommendation over blanket application apart from nitrogen pollution in several means. An advance nutrient management tactic, GreenSeeker (GS) has developed and used in many field crops following the principle of four "R" (right source, right amount at right time, and place) nutrients stewardship technologies. But no studies have been conducted for evaluation of GS in mustard for improving productivity, profitability and nutrient use efficiency (NUE) while minimizing environmental risks. With this objective, a study was planned to conduct an experiment in rabi season of 2021-22 and 2022-23 to assess optical sensor based nitrogen management in mustard over blanket recommendation. The experiment was comprised of ten N treatments including control in randomized block design in triplicates. Research findings indicated that application of GreenSeeker based N significantly improved all growth traits and yield parameters in Brassica juncea L. Per cent enhancement in seed yield, net monetary returns and benefit-cost ratio was higher as 19.3 and 64.5%, 125.1 & 36.2% and 58.8 & 24.4%, respectively under GS based multi split N application over RDF and control. Further, real time N management with GS acquired higher crop production efficiency (CPE) (19.9 kg/day) with lesser cost/kg production (Rs 15.7/kg). Split application of N using GS increased oil yield by 79.9 and 26% over control and recommended dose of fertilizer (RDF) with maximum oil content (42.3%), and increases soil organic carbon (SOC) content by 16.1% from its initial value. Moreover, GS crop sensor could be the probable solution to minimize the crop nitrogen requirement by 15-20% with a yield enhancement of about 18.7% over RDF.

Factors controlling organic carbon stabilization are elusive in neutral-to-alkaline soils, thereby hindering the assessment of carbon sequestration potential across vast agricultural regions like the Indo-Gangetic Plain (IGP). This study investigated controls over mineralization and stabilization of added organic matter in tropical neutral-to-alkaline soils with low organic carbon (SOC). Using topsoil and subsoil samples from 12 sites of upper-to-lower IGP, we conducted a one-year incubation with and without adding 13C-labeled maize material. We tracked CO2 release and residual C remaining in soil organic matter fractions (free, occluded particulate (oPOM), and mineral-associated organic matter (MAOM)) and analyzed organic matter molecular compositions in incubated soils using pyrolysis-GC/MS. Our results revealed that 48 ± 7 % of added maize C was mineralized, mostly within the first 70 days. Higher active Al/Fe, notably Al, retarded primary maize mineralization by facilitating aggregation. High SOC content and SOC saturation degree resulted in more maize mineralization. The disappearance of maize-unique compounds (e.g., neophytadiene) revealed substantial degradation of added maize. Regarding SOC composition, maize addition increased the relative abundance of fatty acids and decreased that of N-containing compounds. Most residual maize-derived C was found in stabilized fractions, MAOM (77 ± 15 % of residual maize C) and oPOM (8 ± 4 %). Clay fraction contributed to most maize-derived C stabilization as MAOM (path coefficient (β) = 0.81**). Moreover, the significant correlation (P

Abstract Indo-Gangetic plains (IGP) of South Asia have supported bulk of human and bovine population in the region since ages, and a spectacular progress has been made in food production. However, malnutrition, diminishing total factor productivity, and natural resource degradation continue to plague this cereal-dominated region, which is also vulnerable to climate change. Addressing these challenges would require a transition towards diversifying cereal rotations with agroecological cropping systems. A study was, therefore, conducted at the experimental farm of ICAR-CSSRI, Karnal on crop diversification and sustainable intensification options using agro-ecological approaches such as Conservation Agriculture (CA) and diversified cropping systems to ensure food and nutritional security while sustaining the natural resources. On 2 years mean basis, CA-based cropping system management scenarios (mean of Sc2–Sc7) using diversified crop rotations; increased the system yield by 15.4%, net return by 28.7%, protein yield by 29.7%, while using 53.0% less irrigation water compared to conventional tillage (CT)-based rice–wheat system (Sc1). Maize-mustard-mungbean on permanent beds (PBs) (Sc4) recorded the highest productivity (+ 40.7%), profitability (+ 60.1%), and saved 81.8% irrigation water compared to Sc1 (11.8 Mg ha−1; 2190 USD ha−1; 2514 mm ha−1). Similarly, Sc5 (maize-wheat-mungbean on PBs) improved productivity (+ 32.2%), profitability (+ 57.4%) and saved irrigation water (75.5%) compared to Sc1. In terms of nutritional value, Sc5 was more balanced than other scenarios, and produced 43.8, 27.5 and 259.8% higher protein, carbohydrate and fat yields, respectively, compared to Sc1 (0.93, 8.55 and 0.14 Mg ha−1). Scenario 5 was able to meet the nutrient demand of 19, 23 and 32 additional persons ha−1 year−1 with respect to protein, carbohydrate and fat, respectively, compared to Sc1. The highest protein water productivity (~ 0.31 kg protein m−3 water) was recorded with CA-based soybean-wheat-mungbean (Sc6) system followed by maize-mustard-mungbean on PBs (Sc4) system (~ 0.29 kg protein m−3) and lowest under Sc1. Integration of short duration legume (mungbean) improved the system productivity by 17.2% and profitability by 32.1%, while triple gains in irrigation water productivity compared to CT-based systems. In western IGP, maize-wheat-mungbean on PBs was found most productive, profitable and nutritionally rich and efficient system compared to other systems. Therefore, diversification of water intensive cereal rotations with inclusion of legumes and CA-based management optimization can be potential option to ensure nutritious food for the dwelling communities and sustainability of natural resources in the region.

Abstract Delayed sowing of maize hybrids could exacerbate the capability of maximizing the yield potential through poor crop stand, root proliferation, nutrient uptake, and dry matter accumulation coupled with the inadequate partitioning of the assimilates. This study appraised the performance of five recent maize hybrids viz., PMH-1, PJHM-1, AH-4158, AH-4271, and AH-8181 under timely and late sown conditions of the irrigated semi-arid ecologies. Timely sowing had the grain and stover yields advantage of 16–19% and 12–25%, respectively over the late sown maize hybrids. The advanced hybrids AH-4271 and AH-4158 had higher grain yields than the others. During the post-anthesis period, a greater dry matter accumulation and contribution to the grain yield to the tune of 16% and 10.2%, respectively, was observed under timely sown conditions. Furthermore, the nutrient acquisition and use efficiencies also improved under the timely sown. The nutrient and dry matter remobilization varied among the hybrids with AH-4271 and PMH-1 registering greater values. The grain yield stability index (0.85) was highest with AH-4158 apart from the least yield reduction (15.2%) and stress susceptibility index (0.81), while the maximum geometric mean productivity was recorded with the AH-4271 (5.46 Mg ha−1). The hybrids AH-4271 and PJHM-1 exhibited improved root morphological traits, such as root length, biomass, root length density, root volume at the V5 stage (20 days after sowing, DAS) and 50% flowering (53 DAS). It is thus evident that the timely sowing and appropriate hybrids based on stress tolerance indices resulted in greater yields and better utilization of resources.

Abstract Intensive tillage operations, indiscriminate use of irrigation water, chemical fertilizers, and pesticides and crop biomass burning have made the conventional rice–wheat (RW) system highly energy-intensive and inefficient. In the recent past, portfolios of climate-smart agricultural practices (CSAP) have been promoted as a potential alternative to improve the energy efficiency in conventional RW system. Therefore, to evaluate the energy input–output relation, energy flow and economic efficiency in various combinations of crop management options, a 3-year (2014–2017) on-farm study was conducted at Karnal, India. Various portfolio of management practices; Sc1-Business as usual (BAU) or Conventional tillage (CT) without residue, Sc2-CT with residue, Sc3-Reduce tillage (RT) with residue + recommended dose of fertilizer (RDF), Sc4-RT/Zero tillage (ZT) with residue + RDF, Sc5-ZT with residue + RDF + GreenSeeker + Tensiometer, Sc6-Sc5 + Nutrient expert were investigated. Present study results revealed that net energy, energy use efficiency and energy productivity were 11–18, 31–51 and 29–53% higher under CSAP (mean of Sc4, Sc5 and Sc6) in RW system than Sc1, respectively. However, renewable and non-renewable energy inputs were 14 and 33% higher in Sc1 compared to CSAP (4028 and 49,547 MJ ha−1), respectively, it showed that BAU practices mostly dependents on non-renewable energy sources whereas CSAP dependents on renewable energy sources. Similarly, the adoption of CSAP improved the biomass yield, net farm income and economic efficiency by 6–9, 18–23 and 42–58%, respectively compared to Sc1. Overall, the adoption of CSAP could be a viable alternative for improving energy use efficiency, farm profitability and eco-efficiency in the RW system.

Abstract Fostering a culture of continuous improvement through regular monitoring of genetic trends in breeding pipelines is essential to improve efficiency and increase accountability. This is the first global study to estimate genetic trends across the International Maize and Wheat Improvement Center (CIMMYT) tropical maize breeding pipelines in eastern and southern Africa (ESA), South Asia, and Latin America over the past decade. Data from a total of 4152 advanced breeding trials and 34,813 entries, conducted at 1331 locations in 28 countries globally, were used for this study. Genetic trends for grain yield reached up to 138 kg ha−1 yr−1 in ESA, 118 kg ha−1 yr−1 South Asia and 143 kg ha−1 yr−1 in Latin America. Genetic trend was, in part, related to the extent of deployment of new breeding tools in each pipeline, strength of an extensive phenotyping network, and funding stability. Over the past decade, CIMMYT’s breeding pipelines have significantly evolved, incorporating new tools/technologies to increase selection accuracy and intensity, while reducing cycle time. The first pipeline, Eastern Africa Product Profile 1a (EA-PP1a), to implement marker-assisted forward-breeding for resistance to key diseases, coupled with rapid-cycle genomic selection for drought, recorded a genetic trend of 2.46% per year highlighting the potential for deploying new tools/technologies to increase genetic gain.

Abstract Field experiments were conducted to evaluate eight different integrated crop management (ICM) modules for 5 years in a maize-wheat rotation (MWR); wherein, ICM1&2-ˈbusiness-as-usualˈ (conventional flatbed maize and wheat, ICM3&4-conventional raised bed (CTRB) maize and wheat without residues, ICM5&6-conservation agriculture (CA)-based zero-till (ZT) flatbed maize and wheat with the residues, and ICM7&8- CA-based ZT raised bed maize and wheat with the residues. Results indicated that the ICM7&8 produced significantly (p

Abstract There is an urgent need to develop disease-modifying therapies to treat neurodegenerative diseases which pose increasing challenges to global healthcare systems. Prion diseases, although rare, provide a paradigm to study neurodegenerative dementias as similar disease mechanisms involving propagation and spread of multichain assemblies of misfolded protein (“prion-like” mechanisms) are increasingly recognised in the commoner conditions such as Alzheimer’s disease. However, studies of prion disease pathogenesis in mouse models showed that prion propagation and neurotoxicity can be mechanistically uncoupled and in vitro assays confirmed that highly purified prions are indeed not directly neurotoxic. To aid development of prion disease therapeutics we have therefore developed a cell-based assay for the specific neurotoxicity seen in prion diseases rather than to simply assess inhibition of prion propagation. We applied this assay to examine an anti-prion protein mouse monoclonal antibody (ICSM18) known to potently cure prion-infected cells and to delay onset of prion disease in prion-infected mice. We demonstrate that whilst ICSM18 itself lacks inherent neurotoxicity in this assay, it potently blocks prion disease-associated neurotoxicity.

Abstract In water scarce regions of South Asia, diversification of rice with maize is being advocated towards sustainability of cereal-based cropping systems. Adoption of innovative agronomic management practices, i.e., conservation agriculture (CA) and sub-surface drip irrigation (SSDI) are considered as key strategies for much needed interventions to address the challenges of water scarcity under projected climate change. Benefits from CA and SSDI concerning water economy are well-established, however, information about their complementarity and water budgeting in cereal-based systems are lacking. A field study was conducted with process-based model (HYDRUS-2D) to understand water transport, root water uptake and components of soil water balance in maize grown in rotation with wheat after five years of continuous adoption of conservation agriculture. In this study, altogether eight treatments comprising of 6 CA+ treatments (CA coupled with SSDI); permanent beds using sub-surface drip (PB-SSD) with (WR) and without (WOR) crop residue at different N rates, 0, 120 and 150 kg N ha−1 were compared with CA (PB using furrow irrigation-FI with crop residue-120 kg N ha−1) and conventional tillage practices (CT) (CT using FI without crop residue-120 kg N ha−1). Results showed that the model could simulate the daily changes in profile soil water content with reasonable accuracy in all the treatments. Simulated soil water balance indicated higher cumulative root water uptake (CRWU), lower cumulative evaporation (CE) and higher soil water retention in CA+ (PB-SSD+ crop residue at 150 and 120 kg N ha−1) than CA and CT plots. Hydrus-2D model efficiency > 0, RMSE between 0.009–0.026 and R2 value between 0.80–0.92 at P

Abstract Climate-smart agriculture (CSA)-based management practices are getting popular across South-Asia as an alternative to the conventional system for particular weed suppression, resources conservation and environmental quality. An 8-year study (2012–2013 to 2019–2020) was conducted to understand the shift in weed density and diversity under different CSA-based management practices called scenarios (Sc). These Sc involved: Sc1, conventional tillage (CT)-based rice–wheat system with flood irrigation (farmers’ practice); Sc2, CT-rice, zero tillage (ZT)-wheat–mungbean with flood irrigation (partial CA-based); Sc3, ZT rice–wheat–mungbean with flood irrigation (partial CSA-based rice); Sc4, ZT maize–wheat–mungbean with flood irrigation (partial CSA-based maize); Sc5, ZT rice–wheat–mungbean with subsurface drip irrigation (full CSA-based rice); and Sc6, ZT maize–wheat–mungbean with subsurface drip irrigation (full CSA-based maize). The most abundant weed species were P. minor > A. arvensis > M. indicus > C. album and were favored by farmers’ practice. However, CSA-based management practices suppressed these species and favored S. nigrum and R. dentatus and the effect of CSAPs was more evident in the long-term. Maximum total weed density was observed for Sc1, while minimum value was recorded under full CSA-based maize systems, where seven weed-species vanished, and P. minor density declined to 0.33 instead of 25.93 plant m−2 after 8-years of continuous cultivation. Full CSA-based maize–wheat system could be a promising alternative for the conveniently managed rice–wheat system in weed suppression in north-west India.

Abstract Micronutrient malnutrition or hidden hunger remains a major global challenge for human health and wellness. The problem results from soil micro- and macro-nutrient deficiencies combined with imbalanced fertilizer use. Micronutrient-embedded NPK (MNENPK) complex fertilizers have been developed to overcome the macro- and micro-element deficiencies to enhance the yield and nutritive value of key crop products. We investigated the effect of foliar applications of an MNENPK fertilizer containing N, P, K, Fe, Zn and B in combination with traditional basal NPK fertilizers in terms of eggplant yield, fruit nutritive quality and on soil biological properties. Applying a multi-element foliar fertilizer improved the nutritional quality of eggplant fruit, with a significant increases in the concentration of Fe (+ 26%), Zn (+ 34%), K (+ 6%), Cu (+ 24%), and Mn (+ 27%), all of which are essential for human health. Increasing supply of essential micronutrients during the plant reproductive stages increased fruit yield, as a result of improved yield parameters. The positive effect of foliar fertilizing with MNENPK on soil biological parameters (soil microbial biomass carbon, dehydrogenase, alkaline phosphatase) also demonstrated its capacity to enhance soil fertility. This study suggests that foliar fertilizing with a multi-nutrient product such as MNENPK at eggplant flowering and fruiting stages, combined with the recommended-doses of NPK fertilizers is the optimal strategy to improve the nutritional quality of eggplant fruits and increase crop yields, both of which will contribute to reduce micronutrient malnutrition and hunger globally.

Various faulty farming practices and low-performance cultivars selection are reducing crop yields, factor productivity, and soil fertility. Therefore, there is an urgent need to achieve better nutrient dynamics and sustainable production by selecting more nutrient-responsive cultivars using efficient nutrient management. The present experiment aimed to enhance crop productivity, seed quality, nutrient efficiency, and soil nutrient dynamics through efficient nutrient management under different lentil cultivars. The experiment was laid out in a split-plot design, assigning three cultivars (viz. Sapna, Garima, and HM-1) in the main plots and ten nutrient management practices in the sub-plots, replicating them thrice. Results revealed that cultivar HM-1 recorded significantly higher seed yield (1.59-1.61 Mg ha-1) and the uptake of N (67.2-67.6 kg ha-1), P (6.8-7.0 kg ha-1), K (13.8-13.9 kg ha-1), Zn (60.4-61.1 g ha-1), and Fe (162.5-165.2 g ha-1) in seed compared to Sapna and Garima. Also, the cultivar HM-1 was more efficient in terms of partial factor productivity for NPK (PFP; 24.27-24.59 kg kg-1), partial nutrient balance (PNB; 2.09-2.13 kg kg-1) and internal utilisation efficiency (IUE; 11.64-11.85 kg kg-1). The study showed that the lentil cultivar HM-1 could be successfully grown by substituting 50% RDN with organic manures, i.e., vermicompost, without compromising crop productivity and soil fertility, thereby sustaining soil-human-environment health.

Flocculated suspended sediments (flocs) are found in a variety of environments globally, and their transport and behavior bear substantial importance to several industries including fisheries, aquaculture, and shipping. Additionally, the modelling of their behavior is important for estuarine and coastal flood prediction and defence, and the process of flocculation occurs in other unrelated industries such as paper and chemical production. Floc porosity is conventionally assessed using inferential indirect or proxy data approaches. These methods underestimate floc porosity % by c. 30% and cannot measure the micro-scale complexity of these pore spaces and networks, rendering inputs to models sub-optimal. This study introduces a novel 3D porosity and pore space quantification protocol, that produces directly quantified porosity % and pore space data. • 3D floc data from micro-CT scanning is segmented volumetrically • This segmented volume is quantified to extract porosity and several pore space parameters from the floc structure

Abstract Conservation agriculture (CA)-based practices have been promoted and recouped, as they hold the potential to enhance farm profits besides a consistent improvement in soil properties. A 7 years' field experiment consisting of three crop establishment practices viz., zero-till flatbed (ZTFB), permanent beds (PNB), conventional system (CT) along with the three-nutrient management; nutrient expert-based application (NE), recommended fertilization (RDF), and farmers’ fertilizer practice (FFP), was carried out from 2013 to 2020. The CA-based practices (ZTFB/PNB) produced 13.9–17.6% greater maize grain-equivalent yield (MGEY) compared to the CT, while NE and RDF had 10.7–20% greater MGEY than the FFP. PNB and ZTFB gave 28.8% and 24% additional net returns than CT, while NE and RDF had 22.8% and 17.4% greater returns, respectively over FFP. PNB and ZTFB had 2.3–4.1% (0.0–0.20 m soil layers) lower bulk density than the CT. Furthermore, microbial biomass carbon (MBC) increased by 8–19% (0.0–0.50 m soil layers) in ZTFB/PNB over the CT, and by 7.6–11.0% in NE/RDF over FFP. Hence, CA-based crop establishment coupled with the NE or RDF could enhance the yields, farm profits, soil properties of the maize–chickpea rotation, thereby, could sustain production in the long run.

Abstract Reduction of excess nutrient application and balanced fertilizer use are the key mitigation options in agriculture. We evaluated Nutrient Expert (NE) tool-based site-specific nutrient management (SSNM) in rice and wheat crops by establishing 1594 side-by-side comparison trials with farmers’ fertilization practices (FFP) across the Indo-Gangetic Plains (IGP) of India. We found that NE-based fertilizer management can lower global warming potential (GWP) by about 2.5% in rice, and between 12 and 20% in wheat over FFP. More than 80% of the participating farmers increased their crop yield and farm income by applying the NE-based fertilizer recommendation. We also observed that increased crop yield and reduced fertilizer consumption and associated greenhouse gas (GHG) emissions by using NE was significantly influenced by the crop type, agro-ecology, soil properties and farmers’ current level of fertilization. Adoption of NE-based fertilizer recommendation practice in all rice and wheat acreage in India would translate into 13.92 million tonnes (Mt) more rice and wheat production with 1.44 Mt less N fertilizer use, and a reduction in GHG of 5.34 Mt CO2e per year over farmers’ current practice. Our study establishes the utility of NE to help implement SSNM in smallholder production systems for increasing crop yields and farmers’ income while reducing GHG emissions.

Abstract Cellular senescence is a stable cell cycle arrest that normal cells undergo after a finite number of divisions, in response to a variety of intrinsic and extrinsic stimuli. Although senescence is largely established and maintained by the p53/p21WAF1/CIP1 and pRB/p16INK4A tumour suppressor pathways, the downstream targets responsible for the stability of the growth arrest are not known. We have employed a stable senescence bypass assay in conditionally immortalised human breast fibroblasts (CL3EcoR) to investigate the role of the DREAM complex and its associated components in senescence. DREAM is a multi-subunit complex comprised of the MuvB core, containing LIN9, LIN37, LIN52, LIN54, and RBBP4, that when bound to p130, an RB1 like protein, and E2F4 inhibits cell cycle-dependent gene expression thereby arresting cell division. Phosphorylation of LIN52 at Serine 28 is required for DREAM assembly. Re-entry into the cell cycle upon phosphorylation of p130 leads to disruption of the DREAM complex and the MuvB core, associating initially to B-MYB and later to FOXM1 to form MMB and MMB-FOXM1 complexes respectively. Here we report that simultaneous expression of MMB-FOXM1 complex components efficiently bypasses senescence with LIN52, B-MYB, and FOXM1 as the crucial components. Moreover, bypass of senescence requires non-phosphorylated LIN52 that disrupts the DREAM complex, thereby indicating a central role for assembly of the DREAM complex in senescence.

Abstract Due to complexity of smallholder farms, many times technologies with great potential fail to achieve the desired impact in leveraging productivity and profitability of the farming community. In the Indo-Gangetic Plains there is an urgent need to understand the diversity of farm households, identifying the main drivers deciding their system thus, classifying them into homogenous groups. In the present study, the diversity of smallholder farms was assessed using crop, livestock and income related characteristics and associated farm mechanization. Using principal component analysis and cluster analysis for 252 farm households, 4 farm types were identified i.e. Type 1. Small Farm households with cereal-based cropping system and subsistence livestock (39%), Type 2. Small Farm households with diversified cropping system dominated by cereal and fodder crops with only cattle herd (9%), Type 3. Marginal Farm household with diversified cropping system dominated by cash crop and herd comprising of only cattle (39%), Type 4. Marginal Farm household with diversified cropping system dominated by cereal crops and herd dominated by small ruminants (12%). Based on the constraints identified for different components of farming systems, low-cost interventions were planned for each farm type. These interventions have resulted in 84.8–103.2 per cent increase in the income of the farm HH under study suggesting usefulness of typology-based intervention planning in increasing income of small farm holders.

Abstract Conservation agriculture (CA) practices are getting space world-wide to answer many emerging challenges like; declining factor productivity, deteriorating soil health, water scarcity, climate change, and farm profitability and sustainability. Oilseed brassica (Indian mustard, Brassica juncea L.), a winter oilseed grown under rainfed agro-ecosystem is vulnerable to low yields, high production cost, degrading soil and water quality, and climatic vagaries. The present study was undertaken on CA-based sustainable intensification of Indian mustard for enhancing inputs efficiencies, farm profitability and sustainability. Permanent beds with residue retention (PB + R) improved mustard equivalent yield (11.4%) and system grain yield (10.6%) compared with conventional tillage without residue (CT − R). Maize–mustard rotation (Mz–M) increased system grain yield (142.9%) as well as mustard equivalent yield (60.7%) compared with fallow-mustard (F-M). Mz–M system under PB + R increased sustainable yield index (376.5%), production efficiency (177.2%), economic efficiency (94%) and irrigation water productivity (66%) compared with F-M under CT − R. PB + R increased soil organic carbon (SOC) stock at 0–15 cm (17.7%) and 15–30 cm (29.5%) soil depth compared with CT − R. Addition of green gram in rotation with mustard improved SOC at 0–15 cm (27.4%) and 15–30 cm (20.5%) compared with F-M system. CA-based cluster bean-mustard/GG-M system increased N productivity, whereas, P and K productivity improved with Mz–M system compared with F-M under CT − R. Thus, CA-based Mz–M system should be out-scaled in the traditional rainfed fallow-mustard system to improve the farm production and income on holistic basis to make the country self-sufficient in edible oils.

Abstract The superconducting systems emerging from topological insulators upon metal ion intercalation or application of high pressure are ideal for investigation of possible topological superconductivity. In this context, Sr-intercalated Bi $$_2$$ 2 Se $$_3$$ 3 is specially interesting because it displays pressure induced re-entrant superconductivity where the high pressure phase shows almost two times higher $$T_c$$ T c than the ambient superconducting phase ( $$T_C\sim 2.9$$ T C ∼ 2.9 K). Interestingly, unlike the ambient phase, the pressure-induced superconducting phase shows strong indication of unconventional superconductivity. However, since the pressure-induced phase remains inaccessible to spectroscopic techniques, the detailed study of the phase remained an unattained goal. Here we show that the high-pressure phase can be realized under a mesoscopic point contact, where transport spectroscopy can be used to probe the spectroscopic properties of the pressure-induced phase. We find that the point contact junctions on the high-pressure phase show unusual response to magnetic field supporting the possibility of unconventional superconductivity.

Glomerular endothelial cells (GEnC) are a specialized microvascular subset of endothelial cells that, when injured, result in many types of diseases within the kidney. Thus, techniques to study GEnC in a cell culture system are important to investigate mechanisms of GEnC injury. Studies of endothelial cell function in culture have predominately relied on using macrovascular endothelial cells from vascular areas other than the glomerulus. Over the last 15 years, glomerular endothelial cells lines have been created but were isolated by targeting cells expressing CD31. Some studies identified endothelial cells isolated from the microvasculature do not express CD31 and some suggest that CD31+ cells are phenotypically different than endothelial cells found in capillaries. Here we detail our method of isolation, purification, and conditional immortalization of mouse glomerular endothelial cells targeting endothelial cells that do not express CD31. • This method allows for isolation, purification, and conditional immortalization of glomerular endothelial cells for continued passage of GEnCs beyond that of primary cell culture. • This method can be used in genetically modified mice to investigate how a modification of a specific gene or protein affects the glomerular endothelium at the cellular level.

Yield gaps of maize (Zea mays L.) in the smallholder farms of eastern India are outcomes of a complex interplay of climatic variations, soil fertility gradients, socio-economic factors, and differential management intensities. Several machine learning approaches were used in this study to investigate the relative influences of multiple biophysical, socio-economic, and crop management features in determining maize yield variability using several machine learning approaches. Soil fertility status was assessed in 180 farms and paired with the surveyed data on maize yield, socio-economic conditions, and agronomic management. The C&RT relative variable importance plot identified farm size, total labor, soil factors, seed rate, fertilizer, and organic manure as influential factors. Among the three approaches compared for classifying maize yield, the artificial neural network (ANN) yielded the least (25%) misclassification on validation samples. The random forest partial dependence plots revealed a positive association between farm size and maize productivity. Nonlinear support vector machine boundary analysis for the eight top important variables revealed complex interactions underpinning maize yield response. Notably, farm size and total labor synergistically increased maize yield. Future research integrating these algorithms with empirical crop growth models and crop simulation models for ex-ante yield estimations could result in further improvement.

Zero tillage is an important pathway to sustainable intensification and low-emission agriculture. However, quantifying the extent of zero tillage adoption at the field scale has been challenging, especially in smallholder systems where field sizes are small and there is limited ground data on zero tillage adoption. Remote sensing offers the ability to map tillage practices at large spatio-temporal scales, yet to date no studies have used satellite data to map zero tillage adoption in smallholder agricultural systems. In this study, we use Sentinel-2 satellite data, random forest classifiers, and Google Earth Engine to map tillage practices across India’s main grain producing region, the Indo-Gangetic Plains. We find that tillage practices can be classified with moderate accuracy (an overall accuracy of 75%), particularly in regions with relatively large field sizes and homogenous crop management practices. We find that models that use satellite data from only the first half of the growing season perform as well as models that use data throughout the growing season, allowing for the creation of within-season tillage maps. Finally, we find that our model can generalize well through time in the western IGP, with reductions in accuracy of only 5–10%. Our results highlight the ability of Sentinel-2 satellite data to map tillage practices at scale, even in smallholder systems where field sizes are small and cropping practices are heterogeneous.

Proteinuria is strongly associated with kidney disease progression but the mechanisms underlying podocyte handling of serum proteins such as albumin and IgG remain to be elucidated. We have previously shown that albumin and IgG are transcytosed by podocytes in vitro. In other epithelial cells, the neonatal Fc receptor (FcRn) is required to salvage albumin and IgG from the degradative pathway thereby allowing these proteins to be transcytosed or recycled. Here we directly examine the role of FcRn in albumin and IgG trafficking in podocytes by studying handling of these proteins in FcRn knockout (KO) podocytes in vitro and in a podocyte-specific FcRn knockout mice in vivo. In vitro, we find that knockout of FcRn leads to IgG accumulation in podocytes but does not alter albumin trafficking. Similarly, in vivo, podocyte-specific knockout of FcRn does not result in albumin accumulation in podocytes in vivo as measured by mean albumin fluorescence intensity whereas these mice demonstrate significant intraglomerular accumulation of IgG over time. In addition we find that podocyte-specific FcRn KO mice demonstrate mesangial expansion as they age and activation of mesangial cells as demonstrated by increased expression of α-smooth muscle actin. Taken together, these results suggest that trafficking pathways for albumin and IgG differ in podocytes and that sustained disruption of trafficking of plasma proteins alters glomerular structure.

We describe a stromal predominant Wilms tumor with focal anaplasia and a complex, tumor specific chromosome 11 aberration: a homozygous deletion of the entire WT1 gene within a heterozygous 11p13 deletion and an additional region of uniparental disomy (UPD) limited to 11p15.5-p15.2 including the IGF2 gene. The tumor carried a heterozygous p.T41A mutation in CTNNB1. Cells established from the tumor carried the same chromosome 11 aberration, but a different, homozygous p.S45Δ CTNNB1 mutation. Uniparental disomy (UPD) 3p21.3pter lead to the homozygous CTNNB1 mutation. The tumor cell line was immortalized using the catalytic subunit of human telomerase (hTERT) in conjunction with a novel thermolabile mutant (U19dl89-97tsA58) of SV40 large T antigen (LT). This cell line is cytogenetically stable and can be grown indefinitely representing a valuable tool to study the effect of a complete lack of WT1 in tumor cells. The origin/fate of Wilms tumors with WT1 mutations is currently poorly defined. Here we studied the expression of several genes expressed in early kidney development, e.g. FOXD1, PAX3, SIX1, OSR1, OSR2 and MEIS1 and show that these are expressed at similar levels in the parental and the immortalized Wilms10 cells. In addition the limited potential for muscle/ osteogenic/ adipogenic differentiation similar to all other WT1 mutant cell lines is also observed in the Wilms10 tumor cell line and this is retained in the immortalized cells. In summary these Wilms10 cells are a valuable model system for functional studies of WT1 mutant cells.

Parkinson's disease (PD) is a common age-related neurodegenerative disease and it is critical to develop models which recapitulate the pathogenic process including the effect of the ageing process. Although the pathogenesis of sporadic PD is unknown, the identification of the mendelian genetic factor PINK1 has provided new mechanistic insights. In order to investigate the role of PINK1 in Parkinson's disease, we studied PINK1 loss of function in human and primary mouse neurons. Using RNAi, we created stable PINK1 knockdown in human dopaminergic neurons differentiated from foetal ventral mesencephalon stem cells, as well as in an immortalised human neuroblastoma cell line. We sought to validate our findings in primary neurons derived from a transgenic PINK1 knockout mouse. For the first time we demonstrate an age dependent neurodegenerative phenotype in human and mouse neurons. PINK1 deficiency leads to reduced long-term viability in human neurons, which die via the mitochondrial apoptosis pathway. Human neurons lacking PINK1 demonstrate features of marked oxidative stress with widespread mitochondrial dysfunction and abnormal mitochondrial morphology. We report that PINK1 plays a neuroprotective role in the mitochondria of mammalian neurons, especially against stress such as staurosporine. In addition we provide evidence that cellular compensatory mechanisms such as mitochondrial biogenesis and upregulation of lysosomal degradation pathways occur in PINK1 deficiency. The phenotypic effects of PINK1 loss-of-function described here in mammalian neurons provides mechanistic insight into the age-related degeneration of nigral dopaminergic neurons seen in PD.