Production Management Strategies Research Articles

The Effects of Climate Change on Streamflow, Nitrogen Loads, and Crop Yields in the Gordes Dam Basin, Turkey

The Mediterranean region is highly vulnerable to climate change. Longer and more intense heatwaves and droughts are expected. The Gordes Dam in Turkey provides drinking water for Izmir city and irrigation water for a wide range of crops grown in the basin. Using the Soil and Water Assessment Tool (SWAT), this study examined the effects of projected climate change (RCP 4.5 and RCP 8.5) on the simulated streamflow, nitrogen loads, and crop yields in the basin for the period of 2031–2060. A hierarchical approach to define the hydrological response units (HRUs) of SWAT and the Fast Automatic Calibration Tool (FACT) were used to reduce computational time and improve model performance. The simulations showed that the average annual discharge into the reservoir is projected to increase by between 0.7 m3/s and 4 m3/s under RCP 4.5 and RCP 8.5 climate change scenarios. The steep slopes and changes in precipitation in the study area may lead to higher simulated streamflow. In addition, the rising temperatures predicted in the projections could lead to earlier spring snowmelt. This could also lead to increased streamflow. Projected nitrogen loads increased by between 8.8 and 25.1 t/year. The results for agricultural production were more variable. While the yields of poppy, tobacco, winter barley, and winter wheat will increase to some extent because of climate change, the yields of maize, cucumbers, and potatoes are all predicted to be negatively affected. Non-continuous and limited data on water quality and crop yields lead to uncertainties, so that the accuracy of the model is affected by these limitations and inconsistencies. However, the results of this study provide a basis for developing sustainable water and land management practices at the catchment scale in response to climate change. The changes in water quality and quantity and the ecological balance resulting from changes in land use and management patterns for economic benefit could not be fully demonstrated in this study. To explore the most appropriate management strategies for sustainable crop production, the SWAT model developed in this study should be further used in a multi-criteria land use optimization analysis that considers not only crop yields but also water quantity and quality targets.

Biorational Fungicides to Manage Cucurbit Powdery Mildew on Winter Squash in New York

Cucurbit powdery mildew (CPM) is one of the most common foliar diseases of winter squash grown in New York. Conventional fungicides remain the primary method for managing CPM. However, increasing consumer demand for organic produce and concerns about both environmental safety and fungicide resistance development have driven research to identify alternative management strategies. Biorational fungicides, including biologicals, botanicals, and minerals, are increasingly available for certified organic production but are generally considered less effective at managing CPM than conventional products. Copper-containing pesticides approved for use in organic production are effective, but concerns about nontarget effects are driving exploration of alternative biorational solutions for CPM. Further research is warranted to validate and expand management strategies for organic cucurbit production. In this study, we evaluated 9 and 10 biorational fungicides to reduce CPM on winter squash in field trials in 2021 and 2022, respectively. The treatment that consistently and most effectively reduced disease severity was Kocide 3000-O (copper hydroxide) followed by Theia ( Bacillus subtilis) and Regalia plus Stargus ( Reynoutria sachalinensis plus B. amyloliquefaciens). The developmental product Curezin (copper zinc) and the adjuvant Dyne-Amic (alkylphenol ethoxylate) also significantly reduced disease compared with the untreated control in 2022. No differences in yield were observed in either year. We conclude that copper-based biorational fungicides most effectively managed CPM compared with other biological and botanical products evaluated, followed by Theia and Regalia plus Stargus. Knowledge gained from this study can inform current CPM management practices and the development of future tools for IPM strategies.

The impact of climate change on vegetable crop diseases and their management: the value of phytotron studies for the agricultural industry and associated stakeholders.

Climate change is having a significant impact on global agriculture, and in particular on vegetable crops, which play a critical role in global nutrition. Recently, increasing research has concentrated on the impact of climate change on vegetable crop diseases, with several studies being conducted in phytotrons, which have been used to explore effects of increased temperatures and CO2 concentrations, to simulate future scenarios. This review focuses on the combined effects of temperature and carbon dioxide increases on foliar and soil-borne vegetable diseases, as evaluated under phytotron conditions. The influence of climate change on mycotoxin production and disease management strategies is also explored through case studies. The results offer valuable information that can be used to guide both seed and agrochemical industries, and to develop disease-resistant varieties and innovative control measures, including biocontrol agents, considering the diseases that are likely to become prevalent under future climatic scenarios. Recommendations on how to manage vegetable diseases under ongoing climate change are proposed to facilitate the adaptation and enhanced resilience of plants to the changing conditions. A proactive and comprehensive response to climate-induced challenges in vegetable farming is imperative to ensure food security and sustainability.

Weed and disease management strategies for sustainable sugar cane production

Weed and disease management strategies for sustainable sugar cane production

A method for developing and calibrating optimization techniques for oil production management strategy applications

A method for developing and calibrating optimization techniques for oil production management strategy applications

Factors driving antimony accumulation in soil-pakchoi and wheat agroecosystems: Insights and predictive models

The accumulation of antimony (Sb) in plants and its potential effects on human health are of increasing concern. Nevertheless, only a few countries or regions have established soil Sb thresholds for agricultural purposes, and soil properties have not been taken into account. This study investigated the accumulation of Sb in the edible parts of pakchoi and wheat grain by adding exogenous Sb to 21 soils with varying properties. The results revealed a positive correlation between bioavailable Sb (Sbava, extracted by 0.1 M K2HPO4) in soil and Sb in the edible parts of pakchoi (R2 = 0.77, p < 0.05) and wheat grain (R2 = 0.54, p < 0.05). Both machine learning and traditional multiple regression analysis indicated Sbava was the most critical feature and the main soil properties that contributed to Sb uptake by pakchoi and wheat were CaCO3 and clay, respectively. The advisory food limits for Sb in pakchoi and wheat were estimated based on health risk assessment, and used to derive soil thresholds for safe pakchoi and wheat production based on Sbtot and Sbava, respectively. These findings hold potential for predicting Sb uptake by crops with different soil properties and informing safe production management strategies.

Goliath vs. Goliath, IT product management at Amazon and IBM

Product management (PM) is nearing its centennial. The father of modern PM Neil H. McElroy laid the foundation for this ever-expanding role. Since 1931, this role has undertaken many changes and additions; a lot of literature covers these aspects. However, two of the most interesting aspects of this role are the introduction of PM in technology and the new product development theory (NPD). The goal of this paper is to examine and compare the PM practices of two giant corporations, Amazon and IBM, that seemingly use different techniques and approaches when it comes to their PM implementation and strategy. The research methods applied are two case studies and a comparative analysis. Through examining relevant literature and publicly accessible information, the comparative analysis is performed and the specific practices of strategy, product development, validate customer needs, service innovation, portfolio management, new product development and diffusion or adoption are selected to provide a spherical approach and information for the two selected companies. A plethora of literature papers are reviewed, and more emphasis is of course given to the aforementioned practices that information is more available and for the other topics a brief introduction is accomplished and space for further research is set.

An overview on major diseases, damage pattern, and management of Mango (Mangifera indica L.) fruit and tree

Mango is one of the most important tropical fruits grown throughout the world particularly in Asia with high economic and nutritional value. However, several diseases and pests cause significant damages to different parts of mango trees and mango fruits, resulting in severe economic losses to farmers and the agricultural sector. Some of the major mango diseases are anthracnose, powdery mildew, die back, and mango malformation. These diseases affect various parts of mango tree, including leaves, flowers, fruits, stems, and roots. The causative organisms of mango diseases include fungi, bacteria, and viruses. Of these, the majority is caused by fungi. Some of the common fungal diseases of mango include anthracnose, powdery mildew, stem-end rot, and sooty mould. Therefore, it is a pressing need to accurately identify the causative organisms for determination of the best management strategy for an effective control. To manage mango diseases, farmers and researchers use several approaches, including cultural practices, chemical control, biological control, and genetic resistance. In this article, the major mango diseases, damage patterns, and management strategies for sustainable mango production has been critically reviewed and presented.

A Case Study on Business Continuity following the Establishment of a Soho Fashion Shopping Mall: Longitudinal Research

This study analyzed the current operational status, business continuity, and business continuity strategies of 11 Soho fashion shopping malls through a longitudinal case study (2019/2020 and 2022/2023). The aim was to determine how Soho fashion shopping malls are continuing their business having been successfully established in the fiercely competitive current online fashion market. Regarding changes in shopping mall operation status, all cases displayed changes in items, distribution channels, marketing channels, core values, and profit structures. After establishing the businesses, a crisis arose due to the COVID-19 pandemic, leading to difficulties in creating new customers. Moreover, there was excessive business expansion, resulting in saturation of the online platform store market. This meant companies were experiencing reduced sales (5) or difficulties in maintaining their business (3). However, there were differences in the direction of overcoming the crisis and continuing or converting the business. These revealed that to continue the business after successful establishment of an online fashion shopping mall, it is essential to have the expertise of entrepreneurs, work performance, and marketing ability, as well as differentiation capabilities such as product power and management strategy and core competitiveness that provides a relative advantage over other shopping malls. Customized government support at the level of the start-up ecosystem is also essential for the survival and business continuity of a SOHO online fashion shopping mall with poor human and material resources.

Enhancing Soybean and Maize Yields through Improved Nitrogen and Soil Water Use Efficiencies: A 40-Year Study on the Impact of Farmyard Manure Amendment in Northeast China.

The combined application of manure and chemical fertilizers has been recognized as a critical factor driving significant changes in crop yield and nutrient use efficiency, holding the potential to optimize agricultural management to achieve high yields. In this 40-year study, we investigated the effect of manure amendment on soybean and maize yields, water and nitrogen use efficiencies (WUE and NUE), and water and mineral N storage at 0-100 cm soil depths from 2017 to 2018 to explore the optimization of fertilization management strategies for soybean and maize production in Northeast China. To elucidate the impact of chemical fertilizers and manure, twelve treatments-control (CK); single N fertilizer at a low rate (N1) and that at a high rate (N2); N1, phosphorus (P), and potassium (K) fertilizer (N1PK); manure alone at 13.5 and 27 t ha-1 (M1 and M2); and those combined with N, P, or K fertilizer (M1N1, M1N2, and M1N1PK and M2N1, M2N2, and M2N1PK)-were selected and studied. The results showed that long-term amendment with manure significantly increased crop biomass and yield in the soybean-maize-maize rotation system. Combining with manure increased the WUE, the partial factor productivity of N fertilizer (PFPN), and N physiological efficiency (PEN) in both the soybean and maize seasons; conserved soil water (mainly at 40-60 cm); and increased soil N retention (in the upper 60 cm layer), which reduced the risk of N leaching, with a better effect being observed after the application of 13.5 t ha-1 manure. These results provide insight into the potential of using fertilization management strategies that include amendment with 13.5 t ha-1 manure in combination with N, P, and K fertilizer in the maize season and only chemical fertilizer in the soybean season, as these results indicate that such strategies can achieve high yields and be used to implement agricultural sustainable development in brown soil regions in Northeast China.

Analysis of Land Suitability for Maize Production under Climate Change and Its Mitigation Potential through Crop Residue Management

Land Suitability Analysis (LSA), under the impact of climate change, is a fundamental approach to the design of appropriate land management strategies for sustainable crop production and food security. In this study, the FAO framework was used to assess the impact of climate change on land suitability for maize in Flanders, Belgium. The current LSA revealed the marginal suitability for maize cultivation, characterizing most of the agricultural land in Flanders and identifying precipitation as the most limiting factor for maize suitability. The LSA, under two climate change scenarios, was based on climate projections from several CMIP5 Global Circulation Models, transformed into future land suitability projections and assembled into a multi-model ensemble (MME) of projected suitability changes. The results indicate an average reduction in projected suitability of approximately 7% by 2099 under the high-emission scenario. The potential of the Soil-Improving Cropping System (SICS) to mitigate the impacts of climate change on land suitability was statistically significant under both low- and high-emission scenarios. This research provides valuable insights into the MME modeling of climate change impacts on land suitability and its associated uncertainty, with the application of SICS as a potential long-term mitigation measure to promote sustainable agricultural practices.

Mechanistic insights into the early life stage microbiota of silver pompano (Trachinotus blochii).

Deep investigations of host-associated microbiota can illuminate microbe-based solutions to improve production in an unprecedented manner. The poor larval survival represents the critical bottleneck in sustainable marine aquaculture practices. However, little is known about the microbiota profiles and their governing eco-evolutionary processes of the early life stages of marine teleost, impeding the development of suitable beneficial microbial management strategies. The study provides first-hand mechanistic insights into microbiota and its governing eco-evolutionary processes in early life stages of a tropical marine teleost model, Trachinotus blochii. The microbiota profiles and their dynamics from the first day of hatching till the end of metamorphosis and that of fingerling's gut during the routine hatchery production were studied using 16S rRNA amplicon-based high-throughput sequencing. Further, the relative contributions of various external factors (rearing water, live feed, microalgae, and formulated feed) to the microbiota profiles at different ontogenies was also analyzed. A less diverse but abundant core microbial community (~58% and 54% in the whole microbiota and gut microbiota, respectively) was observed throughout the early life stages, supporting 'core microbiota' hypothesis. Surprisingly, there were two well-differentiated clusters in the whole microbiota profiles, ≤10 DPH (days post-hatching) and > 10 DPH samples. The levels of microbial taxonomic signatures of stress indicated increased stress in the early stages, a possible explanation for increased mortality during early life stages. Further, the results suggested an adaptive mechanism for establishing beneficial strains along the ontogenetic progression. Moreover, the highly transient microbiota in the early life stages became stable along the ontogenetic progression, hypothesizing that the earlier life stages will be the best window to influence the microbiota. The egg microbiota also crucially affected the microbial community. Noteworthily, both water and the feed microbiota significantly contributed to the early microbiota, with the feed microbiota having a more significant contribution to fish microbiota. The results illustrated that rotifer enrichment would be the optimal medium for the early larval microbiota manipulations. The present study highlighted the crucial foundations for the microbial ecology of T. blochii during early life stages with implications to develop suitable beneficial microbial management strategies for sustainable mariculture production.

Model of a system for monitoring and managing the efficiency of a construction object

The effectiveness of the construction organization largely depends on the competent design and implementation of the business model and the functional production model. In the process of organizing construction, it is necessary to make a huge number of operational decisions, analyze information and form tactical tasks, and build a production management strategy. The article examines the model of the working time monitoring system formed by the authors using smart helmets trackers, the interface of the created solution for the engineering and technical personnel of the construction site “Digital Worker”, a dashboard for viewing reports on the work of the “Architect-Web” organization for company leaders.

Response of Transplanted Rice to Seedling Root-dip in Phosphorus and Biofertilizer Slurry in Acid Soils of North East India- A Participatory Assessment in Farmers’ Field

Background: Rice production is mainly constrained by low P-use efficiency (PUE) and P-recovery efficiency (PRE) in acid soils of the North East hill region of India. Efficient P fertilizer management strategies for rice production is very essential to achieve higher yield per unit of P fertilizer applied. Rhizosphere-based P management in wetland rice is considered as an efficient strategy to minimize the quantity of applied P to obtain a profitable yield. Methods: Seedling root dipping in P slurry technique in farmers’ field condition was studied in comparison to the conventional methods of application of recommended dose of fertilizer (RDF) and the integrated nutrient management (INM) practices to identify a suitable cost effective method of application of phosphatic fertilizer for the acid soils of this hill region of North East India. Result: The highest plant height, maximum number of effective tillers and root biomass were recorded in SSP root dip+Phosphate Solubilizing Bacteria (PSB) followed by INM practices. P root dip had greater root biomass (4.36 g plant-1) which was significantly higher than RDF (3.82 g plant-1). Root dip application showed higher yields (5.80 t ha-1), compared with INM (5.53 t ha-1) and RDF (5.46 t ha-1) and control (4.25 t ha-1). The result of the present study demonstrated that P-dipping can achieve high applied P use efficiency (1193.42) in transplanted rice compared to conventional incorporation of P (625.43). Thus, P-dipping is a potential strategy to overcome low applied P use efficiency in high P-fixing soils and hence reduces the need for excess P application.

Carbon Farming: How to Support Farmers in Choosing the Best Management Strategies for Low-Impact Food Production

The European Commission is directing efforts into triggering the storage of carbon in agricultural soils by encouraging the adoption of carbon farming practices under the European Green Deal and in other key EU policies. However, farmers that want to enter this production model urgently need to define the sustainable practices required for increasing soil organic carbon without overturning production systems and also need to adapt it for optimizing yields and improving carbon stocks. However, there is still a lack of tools that are easy to use and interpret for guiding farmers and stakeholders to find ways in which to increase soil organic carbon content. Therefore, this research aims to set up a novel bottom–up approach, in terms of the methodology and analysis process, for identifying tailored sustainable farming management strategies for the purpose of increasing soil carbon. We investigated 115 real food production cases that were carried out under homogeneous pedo-climatic conditions over a period of 20 years in the Apulia region (Southern Italy), which made it possible to create a dataset of 12 variables that were analyzed through a decision tree (created with the C4.5 algorithm). The overall results highlight that the treatment duration was the most crucial factor and affected the carbon stock both positively and negatively. This was followed by the use of cover crops alone and then those in combination with a type of irrigation system; hence, specific agricultural management strategies were successfully identified for obtaining effective carbon storage in the considered real food production cases. From a wider perspective, this research can serve as guidance to help EU private actors and public authorities to start carbon farming initiatives, pilot projects, or certification schemes at the local and/or regional levels.

Multi-property digital soil mapping at 30-m spatial resolution down to 1 m using extreme gradient boosting tree model and environmental covariates

Information on the variability of soil properties including clay, calcium carbonate equivalent (CCE) and acidity (pH) in space and depth play major role in sustainable agricultural development but scarce in many regions in the world, specifically in developing countries. Digital soil mapping technique has shown strong success in the prediction of soil properties both in space and depth from their relationship with environmental covariates. The aim of the study was to digitally map soil properties including clay, CCE and pH at multiple depths and identify the dominant factors controlling their variability using Minadoab region of Iran as a case study area due to its significance for agricultural production and economic development in the country. A total of 104 soil profiles were randomly selected and described in field during 15–30 July 2017, and 386 samples were collected from each genetic horizon with variable depths. A continuous spline function was fitted to the horizon data and properties were estimated at five standardized depths following GlobalSoilMap project. The soil layers were then grouped into three classes: i) H1: top (0–5 cm); ii) H2–H4: middle (5–15, 15–30 and 30–60 cm); and iii) H5: bottom (60–100 cm) for easy interpretation. A total of 17 static environmental covariates were derived from terrain-related attributes. Additionally, matching with the soil sampling date, a total of eight band ratios in addition to six individual bands were derived from Landsat-8 OLI (Product ID: LC08_L1TP_168034_20170721_20170728_01_T1) for the study area. Finally, all covariates were categorized in nine groups representing various factors controlling soil variations. The digital maps associated with uncertainties were prepared using extreme gradient boosting (XGBoost) Tree model and bootstrapping method, respectively. Overall, the highest accuracy using XGBoost Tree model was found for CCE (R2 = 0.73, on average), followed by pH (R2 = 0.72, on average) and clay (R2 = 0.70, on average). The highest amount of clay was observed for the bottom layer, followed by middle and top layers across the study area. H1 to H3 layers were subjected to tillage operations over the time and may have contributed to the redistribution of clays. A similar trend was also observed for CCE and pH as the location of the study area is underlain by massive limestone. The uncertainties helped quantify over- and under-estimation of the predictions and the factors with the highest variable importance was identified as the dominant factor. The information generated for the study area provides soil variability information that is critical for developing management strategies for sustainable production in the area.

Can the Blended Application of Controlled-Release and Common Urea Effectively Replace the Common Urea in a Wheat-Maize Rotation System? A Case Study Based on a Long-Term Experiment.

The one-time application of blended urea (BU), combining controlled-release urea (CRU) and uncoated urea, has proven to be a promising nitrogen (N) management strategy. However, the long-term sustainability of blending urea remains largely unexplored. To assess whether a single application of blended urea could effectively replace split uncoated urea applications, a long-term field experiment was conducted in the North China Plain (NCP). The results indicated that, when compared to common urea (CU) at the optimal N rate (180 kg N ha-1), BU achieved comparable grain yields, N uptake and NUE (61% vs. 62). BU exhibited a 12% higher 0-20 cm soil organic nitrogen stock and a 9% higher soil organic carbon (C) stock. Additionally, BU reduced life-cycle reactive N (Nr) losses and the N footprint by 10%, and lowered greenhouse gas (GHG) emissions and the C footprint by 7%. From an economic analysis perspective, BU demonstrated comparable private profitability and a 3% greater ecosystem economic benefit. Therefore, BU under the optimal N rate has the potential to substitute split applications of common urea in the long-term and can be regarded as a sustainable N management strategy for wheat and maize production in the NCP.

Modelling adaptation measures to improve maize production and reduce soil N2O emissions under climate change in Northeast China

Optimizing management practices is essential to guarantee crop yield and reduce greenhouse gas emissions for the sustainable agricultural production under climate change. The objectives of this study were to i) calibrate and evaluate the Denitrification-Decomposition (DNDC) model using the measurements of maize yield, nitrogen (N) uptake, soil temperature, soil moisture, soil inorganic N and nitrous oxide (N2O) emissions from a 5-year maize field experiment in Northeast China (NEC) and ii) simulate the impacts of climate change on maize yield and N2O emissions and explore adaptation strategies based on DNDC modelling. For N-fertilized treatments (farmers’ practice, FP-N; current optimized management, OPT-N), the DNDC model overall showed “good” performance in simulating maize yield, aboveground biomass, N uptake and soil inorganic N based on the average statistical values. The model also performed well in simulating soil moisture, soil temperature and N2O emissions. For N-unfertilized treatments, however, the DNDC model overestimated crop yield and N uptake mainly due to the overestimation of crop growth under low-temperature stress conditions, and the underestimation of soil inorganic N resulted from the underestimated N mineralization and N availability from the dissolved inorganic N pools under continuous N deficiency. The DNDC model showed that compared to the baseline scenario, future climate change would improve the maize yield (1.4–8.8%) while increasing the N2O emissions (37.6–83.4%) without adaptation measures in NEC. Compared to OPT-N management, solely adjusting N fertilization rate (200–220 kg N ha−1) would concurrently increase maize yield (5.0–8.7%) and N2O emissions (0.9–18.6%), while the adoption of optimized planting dates (April 27th to May 18th), new cultivars (with thermal degree days ranging from 2550 to 2700 °C), and the implementation of no-tillage and maize-soybean rotation would increase the maize yield by 1.8–8.9% and reduce the N2O emissions by 0.7–26.5% under future climate change scenarios. This study provided insights into the adaptive management strategies for the sustainable maize production under climate change in NEC.

Napier grass (Pennisetum purpureum Schum) management strategies for dairy and meat production in the tropics and subtropics: yield and nutritive value.

Napier grass (Pennisetum purpureum Schumach) comprises up to 80% of the cattle diet in many tropical and subtropical regions and is used primarily by smallholder farmers. Despite the grass's high yield, resulting animal productivity from this grass is low. One of the key reasons for the low animal productivity of Napier grass is its low nutritive value under current management. Taken together, previous work has shown the current yield, crude protein (CP), and metabolisable energy (ME) of Napier grass to be 26t dry matter (DM)/ha/year, 96 g/kg DM, and 8.7 MJ/kg DM, respectively, ranging from 2 to 86t DM/ha/year, 9 to 257g CP/kg DM, and 5.9 to 10.8 MJ ME/kg DM, respectively, suggesting an opportunity for significant improvement on both yield and nutritive value of this grass. The DM yield and nutritive value of this grass are inversely related, indicating a trade-off between yield and quality; however, this trade-off could be minimised by increasing sowing density and harvesting frequency. Available literature shows that this simple management strategy of increasing sowing density (50cm × 40cm) and harvesting frequency (11-12 harvests/year) provides 71t DM/ha with 135 g/kg DM CP and 10.8 MJ ME/kg DM. This quality of Napier grass has the potential to increase both milk and meat production substantially in the tropics and subtropics, and the farmers will likely find this simple management acceptable due to the high yield obtained through this management. However, there is a paucity of work in this field. Therefore, management strategies to improve the nutritive value of Napier grass are required to increase milk and meat production in the tropics and subtropics and in doing so improve the food security of more than half of the global population living in these regions.

Field-level rice yield estimations under different farm practices using the crop simulation model for better yield

Crop yield estimation is essential for decision-making systems and insurance policy makers. Numerous methodologies for yield estimation have been developed, encompassing crop models, remote sensing techniques, and empirical equations. Each approach holds unique limitations and advantages. The primary aim of this study was to assess the accuracy of the DSSAT (Decision Support System for Agro Technology Transfer) model in predicting rice yields and LAI (Leaf Area Index) across various management methods. Additionally, the study sought to identify the optimal management practice for attaining higher yields. Crop models facilitate the expeditious evaluation of management strategies aimed at improving crop yield and analyzing the balance between production, resource efficiency, and environmental impacts. The study region selected for analysis is Karimnagar district of Telangana state. DSSAT has been chosen as the preferred tool due to its high efficiency in evaluating crop yield. The model's simulated yield was compared to the observed yield obtained from crop-cutting experiments. The results indicate a correlation of 0.81 and 0.85 between observed and simulated yields, as well as between model LAI and yield. An observation was made regarding a discrepancy between predicted and actual yields, which can be attributed to biotic stress. However, it should be noted that the current model does not account for this factor. The observed average yield was 5200 kg ha-1, whereas the projected yield was 5400 kg ha-1. The findings indicate that the model's performance is influenced by both the timing of sowing and the amount of nitrogen applied. The findings indicate that the DSSAT model has demonstrated a high level of accuracy in predicting both yields and leaf area index (LAI) across various management strategies. This study showcases the potential use of crop simulation models as a technology-driven tool to identify the most effective management strategies for rice production.