Abstract To optimize productivity and prevent pasture degradation, management strategies such as the use of thermal sum (TS) to adjust grazing intervals can improve forage efficiency. The aim was to evaluate the effect of different TS as grazing intervals on the bromatological and structural composition of wheat cv. XFront®. The experiment followed a block design with repeated measures over time, with six plots and two treatments: T1) 330 TS and T2) 550 TS, in two years of evaluation. TS were defined by leaf emission speed, based on the phyllochron (110 days). The botanical (wheat) and structural composition was determined by manual separation of components. In general, management by TS did not influence (P > 0.05) the contents of dry matter (DM; 13.9%), organic matter (OM; 10.9%), in vitro dry matter digestibility (IVDMD; 65.7%), percentage of leaves (PL; 54.0%), or percentage of other species (POE; 9.7%). However, there was an effect of TS (P < 0.05) on the percentage of dead material (PDM; 7.7% vs. 10.4%), height (26.7 cm vs. 32.8 cm), dry matter yield (DMY; 9,369 vs. 7,305 kg/ha), and yield per cycle (DMC; 1,787 vs. 2,043 kg/ha) for TS 330 and TS 550, respectively. The variables crude protein (CP; 28.8% vs. 33.0%), hemicellulose (HEM; 23.4% vs. 23.7%), and percentage of stem plus sheath (PS; 24.5% vs. 29.9%) differed between years of evaluation. In conclusion, management with lower TS, i.e., shorter rest intervals, resulted in better nutritional quality of forage biomass, due to greater tissue renewal and reduced senescence.
Abstract The objective was to evaluate effects of age at first joining (7 or 19 months), ewe genotype and age on ewe performance between 2 and 8 years of age, and that of their progeny to slaughter. Three genotypes were represented: Belclare (Bel), F1 Suffolk x Belclare (Suf×Bel), and ≥0.75 Suffolk ancestry (Suf75). The flock (424 ewes initially) was managed in a grass-based system based on rotational grazing at the Athenry Research Centre; ewes were housed from mid-pregnancy to lambing and exited the flock when culled (health/welfare reasons) or they died. There were no significant interactions between first-joining age and ewe genotype. Ewes joined to first lamb at 1 year of age required significantly less lambing assistance and produced heavier lambs at birth, with lower lamb mortality. Bel and Suf×Bel ewes produced larger litters, and reared significantly more lambs per ewe than Suf75. Barrenness was lower for Suf×Bel than Suf75, and their lambs were younger at slaughter. Ewe longevity was unaffected by age at first joining or genotype. Mortality of lambs from Bel ewes was lower than those from Suf75. Ewe and lamb performance traits increased with ewe age to a plateau starting around 5 to 6 years of age. Number of lambs reared per ewe reached a maximum at age 6 and exhibited a major decline (-0.4) at 8 years, reflecting lower prolificacy and increased barrenness. Lamb growth rate increased and age at slaughter declined as ewes aged.
Abstract Cultural weed management through intercropping helps in weed suppression, resulting in improved crop productivity. Cereal–legume intercropping is one of the major eco-friendly approaches to suppress weeds and improve crop performance and soil fertility. Therefore, a two-year field experiment was carried out at the campus of Ramakrishna Mission Vivekananda Educational and Research Institute, Ranchi, Jharkhand during the monsoon season of 2023 and 2024 in a randomized block design with three replications using eight cropping systems. Results revealed that sole black gram ensured highest weed control efficiency (55.9%), followed by intercropping system of finger millet and black gram (1:2) (49.5%). Finger millet + black gram (1:2) and sole black gram recorded higher growth attributes and yields of finger millet and black gram, respectively. However, finger millet + black gram (1:2) also recorded high growth and yield attributes of black gram. System productivity was maximum in sole black gram (4730 kg/ha), followed by intercropping system of finger millet and black gram (1:2) (3900 kg/ha), along with protein content (23.4%) and consequently, the production economics (net return: Rupees 56830/ha; benefit: cost of 1.90). It also resulted in the highest residual soil fertility. Additionally, the combined land equivalent ratio (1.44) was higher in the 1:2 intercropping system of finger millet and black gram, indicating a 44% yield advantage. Thus, in Eastern Plateau and Hill Zone of India, an intercropping system of finger millet and black gram (1:2) is recommended for cultivation in monsoon to achieve high weed suppression, crop productivity, and economic profitability.
Reducing nitrogen (N) application represents a strategy for sustainable rice production. The combined effects of deep fertilization (DF) and urease inhibitor (UI) under reduced N input on ammonia (NH3) volatilization, N-use efficiency (NUE) and yield in double-cropping rice remain uncertain. A two-year field trial in Hunan, China, using early-and late-season rice (ESR and LSR), established seven treatments: conventional fertilization (CF, manually broadcast); DF with 30% N reduction; DF with 0.5, 0.75, 1.0, 1.25 and 1.5% NBPT (DF + UI1-DF + UI5, respectively); and a zero-N control (CK). In ESR and LSR, the total NH3 loss rates under CF were 46.9% and 54.2% (2024), and 51.6% and 52.5% (2025), respectively. DF + UI significantly reduced the cumulative NH3 loss rates to 6.9-16.0% (2024) and 9.4-16.4% (2025) for ESR, and to 10.6-17.4% (2024) and 3.6-9.9% (2025) for LSR. DF + UI effectively mitigated NH3 volatilization by lowering surface water ammonium, inhibiting urease activity and delaying urea hydrolysis; it also increased grain yield and apparent N recovery efficiency by 5.6-21.1% and 13.8-33.4 percentage points, respectively. These benefits were attributed to the dual effect of delaying the NH3 volatilization peak by two days while reducing its intensity, which improved synchronization between N supply and rice demand, enhanced total N uptake, promoted N accumulation and increased panicle number and spikelets per panicle. Overall, reducing N input by 30% under DF with 1.25% UI effectively reduced NH3 volatilization while enhancing NUE and rice yield in double-cropping systems.
Abstract Sea fennel ( Crithmum maritimum L.) is a halophyte species with high potential for supporting sustainable food production and agrobiodiversity. Despite this potential, studies on its domestication and standardized cultivation protocols remain highly limited. In the current study, the agronomic performance and phytochemical diversity of three ecotypes (Atlantic ecotype and native Turkish ecotypes) were evaluated under Mediterranean conditions over two growing seasons. Fresh biomass increased by 76% in the second growing season compared with the first year. This indicates that the plants were successfully established under the experimental conditions and maintained productive growth. Differences among ecotypes were statistically significant; the Atlantic ecotype exhibited superior yield potential compared with the native ecotypes. Bio-fertilizer application significantly increased canopy development and total biomass while also supporting marketability. Phytochemical profiling revealed distinct distributions among plant parts. Flowers were superior in terms of total phenolic and reducing power, whereas leaves stood out as the main reservoir of vitamin C, carotenoids, and radical-scavenging activity. The average essential oil yield was 1.6 ml/100 g dry matter, and compositional analysis showed that the native ecotypes contained high levels of dillapiole, whereas this compound was detected only at trace levels in the Atlantic ecotype. Overall, these findings confirm that sea fennel is a resilient and chemically valuable crop suitable for Mediterranean agriculture and offers a feasible strategy for crop diversification by farmers.
The objective of this study was to develop calibration equations for a rising plate metrer (RPM) to estimate herbage mass in irrigated ryegrass/white clover (RGWC) swards with varying proportions of plantain. A 32-ha area, divided into 0.3-ha paddocks, was randomly allocated to three treatments sown with increasing plantain seeding rates: (i) RGWC with no plantain, (ii) RGWC + 3 kg/ha and (iii) RGWC + 6 kg kg/ha. Over two production years (2021/22 and 2022/23), 1138 quadrat cuts and 228 botanical samples were collected. Data were grouped by season (late-winter, spring, summer and autumn) across treatments and years. A multivariate linear regression model incorporating compressed sward height, plantain % in sward DM and season explained 73.5% of the variation in herbage mass (R-2 = 0.735; P < 0.001). Compressed sward height was positively associated with herbage mass (estimate +/- SE; 145 +/- 6.2 kg DM/ha per RPM unit; P < 0.001), while plantain % was negatively associated (-0.45 +/- 0.12 kg DM/ha per 1% increase; P < 0.001). Season significantly affected the intercept (P < 0.001), being -128 +/- 135.0 (late-winter), 82 +/- 104.0 (spring), 251 +/- 106.0 (summer) and -81 +/- 111.0 (autumn) kg DM/ha. Validation using an independent dataset from the 2023/24 production year showed the model predicted herbage mass with a root mean square error (RMSE) of 350 kg DM/ha. These equations can be integrated into RPM devices to estimate herbage mass in rotationally grazed, irrigated RGWC swards containing plantain, accounting for both plantain content and seasonal variation.
Although carrot productivity is influenced by irrigation scheduling and planting techniques, however their interactive effects on soil properties and consequent crop performance in hilly agro-ecosystem remain insufficiently explored. It was hypothesised that optimised irrigation levels, combined with an appropriate sowing method would significantly improve soil nutrient availability, carrot yield and water productivity. A field experiment was carried out for two consecutive years (2021-22 and 2022-23) using a factorial Randomised Block Design with two sowing methods, Flat-bed (S1) and Ridge (S2) and four irrigation regimes based on irrigation water (IW)/cumulative pan evaporation (CPE) ratios of 0.6 (I1), 0.8 (I2), 1.0 (I3) and 1.2 (I4). Ridge sowing (S2) consistently outperformed over flat-bed sowing (S1) with respect to nutrient availability, yield and water productivity. The highest carrot yield (34.2 t/ha) was recorded under the combination of ridge sowing and the highest irrigation level (S2I4). Moderate irrigation level provides the balance between yield and water use, resulting in higher total water productivity, whereas the highest irrigation level (I4) improved crop water productivity and soil nutrient dynamics although it was less efficient in crop production per unit water applied. The findings demonstrate that ridge sowing, in combination with optimised irrigation regimes (I3), offer a practical strategy to enhance soil health and resource use efficiency while sustaining the carrot productivity hilly region. These findings offer a practical guidance for farmer and planners seeking to improve water management and crop performance in comparable agro-ecological environment.
Accurate crop growth models are essential for predicting yield and evaluating adaptation potentials under climate change. As one of Europe's most important forage crops, silage maize (Zea mays L.) requires a model that captures genotype-specific growth traits and environmental variability. The current study presents HUME-Maize (Hannover University Modelling Environment), a new process-based model for silage maize, specifically adapted to conditions in Northern Europe. Model development relied on an extensive dataset from two field trials (2007-2008, 2021-2022) at five sites across Germany, involving two mid-early maize hybrids released 12 years apart. Calibration was based on the older hybrid and evaluated on both, testing the need for hybrid-specific parameter adjustments. Model scalability and predictive accuracy were assessed with a nationwide dataset covering 287 site-year combinations. The baseline model, parameterized using an older hybrid, reproduced biomass formation well (d = 0.98 and 0.95). Application to a newer hybrid without adjustment revealed systematic differences in leaf development and yield formation associated with breeding progress. Hybrid-specific adjustments of physiological traits, e.g. leaf growth rate, specific leaf area and radiation use efficiency, substantially improved model performance, reflecting the enhanced radiation use efficiency of the newer hybrid. On the national scale, the model achieved low prediction errors for final yield (16 % for the older and 21 % for the newer hybrid). Drought and nitrogen stress responses remain areas for refinement. HUME-Maize thus provides a robust framework for simulating hybrid-specific silage maize growth, supporting yield prediction and physiological analysis across hybrids and environments.
Direct-seeding of rice by sowing dry seeds on dry soils often results in poor seedling emergence due to erratic rainfall. Adjusting the sowing depth to a given rainfall pattern may improve rice emergence. To assess risks of crop failure in direct-seeded rice, we developed a platform for modelling and simulation of rice emergence at different sowing depths. We combined the HYDRUS-1D soil simulation model, which simulates the surface soil's moisture dynamics, with two rice emergence models recently developed by our research group. The platform used 48 years of daily weather data (1977-2024) for the study site as inputs for the soil model to simulate soil moisture and temperature at designated depths. We then input the simulated values and sowing depths into the emergence models to simulate final emergence and the emergence date. The simulated soil water tension at a depth of 1 cm showed huge interannual variation, reaching 10 MPa in dry years. The simulation showed that relative to a 1-cm sowing depth, depths of 4 and 6 cm greatly reduce the probability of crop failure under rainfed conditions (from 8 % to between 1 % and 2 %). Our novel platform for risk assessment should therefore facilitate the use of direct-seeded rice in suboptimal environments. The platform also fills a knowledge gap for simulation of crop establishment in direct-seeded rice under future climate scenarios.
This study evaluated the dynamics of the bacterial community in mixtures of forage cactus and sorghum silage at different proportions, subjected to aerobic exposure periods, without or with faecal contamination. The experimental design was completely randomized in a 2 & times; 2 & times; 4 factorial arrangement, with two forage cactus proportions (20 and 80 %), absence or presence of faecal contamination and four aerobic exposure times (0, 6, 12 and 24 h). Fermentation profile, chemical composition, microbial populations and bacterial diversity were evaluated. A higher proportion of forage cactus resulted in increased pH and greater proliferation of enterobacteria, with detection of Escherichia coli after aerobic exposure. In contrast, mixtures containing 20 % forage cactus and 80 % sorghum silage showed greater fermentative stability, characterized by higher lactic acid production, reduced growth of potentially pathogenic microorganisms and lower abundance of undesirable bacterial groups after 24 h of exposure. The combination of 20 % forage cactus and 80 % sorghum silage was more effective in preserving the microbiological and fermentative quality of the mixture during aerobic exposure.
Deficit irrigation can enhance crop water productivity (CWP; yield per water applied) but requires careful management to prevent drought-like responses that limit leaf gas exchange (i.e., water-conservative responses) and compromise yield. Grafted and ungrafted melons (Cucumis melo L.) were evaluated under three irrigation treatments: full irrigation (100 % field capacity; FC) and 70 % or 50 % deficit irrigation, based on water applied to the 100 % FC. Although deficit irrigation accentuated drought stress through the season, plants under moderate deficit irrigation (70 % FC) had similar water potential (Psi), and only 34 and 14 % lower stomatal conductance (g s) and photosynthetic rate (P n) than the full irrigation. Under severe deficit irrigation (50 % FC), plants had 28 and 17 % lower predawn and midday Psi than the full irrigation. The lower plant water status of the 50 % FC resulted in water conservative-responses, and a 65 and 47 % lower g s and P n than the 100 % FC. Yield of the 100 and 70 % FC treatments were affected by evapotranspiration demands (i.e., irrigation & times; year interaction), while the 50 % FC had a 40 % lower yield than the full irrigation. Moderate deficit irrigation reduced water applied by 25 % and had either a similar or a 47 % increase in CWP compared to the full irrigation. Overall, grafting improved yield by 14 %, but it was greater under full irrigation and low environmental stress. Overall, melon crop performance was maintained under a constant, moderate deficit irrigation, and this should be considered as an effective water-saving strategy for melons to cope with long-season droughts.
Experimental designs involving factors with a mix of fixed and random levels have been explored by few. These designs are useful when comparing a set of new treatments (fixed levels) to a population of established treatments (random levels). This approach enables partitioning variability and testing of both fixed and random effects, leading to improved estimates and more reliable inference. However, combining analyses of variance from partitioned data poses challenges, including data rearrangement, methodology, and coding complexities. Existing statistical software does not directly support combined analyses for such designs. The current study provides guidelines for conducting combined analysis of variance in linear mixed-effects models where factors have both fixed and random levels. The approach utilizes SAS PROC GLIMMIX and tools from the Comprehensive R Archive Network to compile the combined analysis of variance, followed by multiple comparisons of treatment means. The procedure is demonstrated using treatment structures in a completely randomized design, split-split-plot design, and repeated-measures design. The method can be extended to other experimental designs. This framework addresses a critical gap in existing literature by providing a practical and readily applicable analytical tool that enables integrated analysis across all factor levels within a single linear mixed-model structure, while accounting for pre-history effects associated with prior management practices in complex experimental systems.
Due to the negative impacts of climate change, soil degradation and losses of soil organic carbon (SOC) in arable agricultural ecosystems are gradually increasing worldwide. Therefore, implementing agricultural management practices that increase organic carbon (OC) sequestration in soils with intensive agricultural production is essential for maintaining soil quality (SQ) and enhancing sustainable crop production. Understanding the effects of management practices on SOC stability requires understanding the resulting changes in the SOC fractions (labile or recalcitrant), the OC contents associated with aggregates, and the SOCStocks. In the present study, soil samples were collected from three different depths in the & Ccedil;ar & scedil;amba Alluvial Delta Plain, located in Turkey's semi-humid climate zone, to investigate the long-term effects (>5 years) of six different land use types (LUTs). Our results regarding average values revealed that the labile SOCLC and recalcitrant SOCRC fractions, OC contents associated with aggregates, and SOCStocks changed significantly (p < 0.01) in response to the effects of different LUTs. Compared to pasture land use, the contents of SOCLC and SOCRC were statistically decreased from 5.98 to 3.16 g/kg and from 6.37 to 3.43 g/kg (p < 0.01), respectively, in soils under soybean land use. Also, it was found that both SOC fractions reduced statistically (p < 0.01) with increasing soil depth. This study, which evaluated the long-term effects of different LUTs on SOC, revealed that SOCLC and SOCRC fractions can be successful indicators in assessing the effects of different LUTs and soil depths.
Onion seed productivity, quality, and profitability in Ethiopia are constrained by declining soil fertility and inadequate fertilizer management, particularly due to a historical reliance only on blanket nitrogen-phosphorus-based recommendations for bulb production. Therefore, the study examined the impacts of NPSB fertilizer, vermicompost, and their integrated application on soil fertility, onion seed yield, and quality in Yaya-Gulele, Oromia, Ethiopia. Treatments comprised a factorial combination of four NPSB rates (0, 75, 150, 225 kg/ha) and four vermicompost rates (0, 1.25, 2.5, 3.75 t/ha), arranged in a randomized complete block design with three replications. Seed quality was evaluated under laboratory conditions using a completely randomized design with four replications. The integrated application of NPSB and vermicompost improved key soil chemical properties, prolonged vegetative growth, and enhanced seed yield and quality parameters of onions compared to sole applications and the control. The highest-performing integrated treatment increased seed yield by up to threefold relative to the control. The integration of 150 kg/ha NPSB with 3.75 t/ha vermicompost was identified as the most agronomically and economically optimal treatment, producing the highest seed yield and net returns. This first report from North Shewa shows that the synergistic integration of NPSB and vermicompost significantly increases onion seed productivity and quality by improving soil fertility. This approach offers a practical and sustainable nutrient management strategy for onion seed production systems in Ethiopia.
It is crucial to properly evaluate the traits that directly impact agricultural productivity. Some of these traits, such as soil erosion or crop diseases, are quantified with scoring systems. The resulting data are strictly ordinal and often have an underlying percentage scale. Deciding which model to use for this type of data is not straightforward. Ordinal scores do not meet the assumptions required for analysis of variance. Although multinomial ordinal models, particularly the threshold model, can be applied, they do not account for the underlying percentage scale of the data. To address this limitation, a hurdle model tailored for interval-censored percentage data is proposed. It is a two-part model that models the data according to their nature: In its first part, it models presence or absence of a disease (incidence), and in the second part it models severity or abundance. Individually modelling presence and absence in the first part allows to account for zero inflation. The second part implements theory from the threshold model and the Johnson SB system of distributions that involves a transformation of the percentage scale to a normal distribution. The model result also reflects the two components. They individually describe the degree of disease infestation, and the degree of disease spread. This improves interpretability and enables concrete, insightful conclusions. To illustrate the model, mildew scorings from an on-farm trial in grapevines were used. The model was found highly suitable for this dataset and superior to the threshold model.
Grassland biodiversity and forage nutritive value are influenced by pedoclimatic conditions (e.g., soil nutrients, precipitation), management practices (e.g., mowing, grazing), and animal grazing behaviour shaping the sward botanical composition and structure. Horses, in particular, affect sward structure through selective foraging, short biting, trampling, and toileting, resulting in a patchy vegetation pattern on pastures. However, the relative importance of pedoclimatic and management factors across regions remains unclear. The effects of horse grazing and pasture heterogeneity versus management on grassland biodiversity and forage quality are also uncertain. To analyse these interactions, data were collected from 36 horse farms across two contrasting regions in Germany: an upland and a lowland area, differing in pedoclimatic conditions and farming intensity. On each farm, two of the studied grassland fields were exclusively grazed by horses, while two were either mown or both mown and grazed. A total of 148 grasslands were assessed for vegetation (species composition and proportion) and agronomic (forage nutritive value) target variables. Grazed pastures were generally more variable in terms of higher coefficients of variation of target variables than mown sites. The analysis further revealed a significant patch type & times; region interaction for species composition, with higher evenness in short patches - particularly in the more extensively managed upland region - indicating enhanced structural diversity under grazing. Agronomic traits were driven primarily by patch type and management, with minimal regional effects. In this study, patch type and therefore management strategies play a larger role for grassland biodiversity and forage nutritive value than regional context alone.
Studies on morphogenesis and tillering are crucial for pasture productivity and sustainability, as forage production depends on tiller performance and population density. This two-year study assessed the impact of four grazing frequencies on tillering dynamics and morphogenesis traits of Megathyrsus maximus cv. BRS Zuri under intermittent stocking. A randomized block design was employed, with four pre-grazing light interception (LI) levels (80%, 85%, 90%, and 95%) and four replications per treatment. Evaluated variables included leaf appearance (LAR), elongation (LER) and senescence rates (LSR), leaf lifespan (LLS), phyllochron (PHYL), final leaf length (FLL), live leaf number (LLN), stem elongation rate (SER), tiller appearance (TAR), mortality (TMR) and survival rates, tiller stability index (TSI), and forage accumulation rate (FAR). There was an effect of LI on PHYL, LER, SER, LLS, and LSR, where data fit increasing linear regressions, with increments of 0.29 days, 2.86 cm, 0.013 cm, 1.52 days, and 0.058 cm, respectively, as LI increased. Tiller appearance was similar across treatments, whereas mortality and survival rates showed LI & times; year interaction. The highest mortality rate was observed in pastures managed with 80% LI, while the lowest mortality and highest survival rates occurred in those managed with 95% LI. TSI increased with LI and was higher in the first year, with reductions under 80% and 85% LI. Pastures managed at 90% and 95% LI showed more stable tiller populations and greater leaf elongation and FLL. Management with 90% LI allows for growth interruption before the greatest pseudostem accumulation and leaf senescence.
Efficient sowing techniques ensure proper crop establishment and enable optimal utilization of resources, thereby enhancing crop productivity, reducing production costs and improving overall farm profitability. Although quinoa is a low water-requirement crop, it responds significantly to well-planned irrigation regimes. To develop suitable irrigation schedules for quinoa under different land management in rice fallows, a field experiment was conducted for two consecutive years (2022-2023 and 2023-2024) at the ICAR - Indian Institute of Water Management, Bhubaneswar Research Farm. The experiment included two sowing techniques in the main plots (L1: Broad Bed and Furrow; L2: Flat Beds) and three irrigation schedules in the subplots (I1: Irrigation at branching, primordial initiation, flowering and grain filling; I2: Irrigation at branching, primordial initiation and grain filling; I3: Irrigation at branching and flowering). Sowing quinoa on broad bed and furrow (BBF) resulted in significant increases in grain yield (12.6 %), biological yield (11.9 %), land productivity (13.4 %) and energy use efficiency (12.5 %) compared to flat beds. The BBF method also achieved a higher net return (US $531/ha), benefit-cost ratio (1.82), physical water productivity (0.79 kg/m3) and economic water productivity (US $0.67/m3). Irrigation scheduling at all four critical growth stages (I1) led to an increase in grain yield (1.57 t/ha), higher net return (US $686/ha), Benefit/Cost 'B:C' ratio (2.05) and improved water productivity (0.66 kg/m3 and US $0.57/m3 economic water productivity). Therefore, appropriate land management combined with optimal irrigation scheduling is essential for realizing the full yield potential of quinoa in the rice ecosystems of Eastern India.
Evaluation of genotypes is essential for assessing yield stability in organic farming, helping identify suitable cultivars for Punjab's growers. This is particularly important given the harmful effects of intensive chemical use on soil and water quality, which drives the shift toward organic practices. Unlike conventional methods, organic farming relies on sustainable approaches such as crop rotation, green manure and bio-pesticides to promote agroecosystem health. The experiment was conducted during the Kharif seasons of 2020 and 2021 in a randomised complete block design at the Research Farm of the Punjab Agricultural University, Ludhiana, Punjab. Ten Basmati varieties, including Punjab Basmati 5, Punjab Basmati 4, Punjab Basmati 3, Punjab Basmati 2, Basmati 386, Basmati 370, CSR 30, Pusa Basmati 1121, Pusa Basmati 1509 and Pusa Basmati 1718, were assessed for the various yield-attributing parameters, such as effective tillers, number of grains per panicle, 1000-grain weight, grain yield, straw yield and total biomass. Pusa Basmati 1509 produced the highest grain yield (3.6 tonnes/ha), biomass yield (6.7 tonnes/ha) and harvest index (35.2 %) among all varieties followed by Punjab Basmati 4 and Pusa Basmati 1718. Net returns (INR 122,000 per ha) and benefit-cost ratio (B:C) (2.09) were the highest in Pusa Basmati 1121 because this cultivar fetches higher price in the market due to its superior aroma and cooking quality. The future research could delve into the organic cultivation practices specifically developed for these cultivars, contributing to the development of sustainable and resilient agriculture system in the region.
