Total Demand Research Articles

Long Term Forecasting of Peak Demand and Annual Electricity Consumption of the West African Power Pool Interconnected Network by 2032

The uneven distribution of primary sources of electric power generation in Economic Community of West African States (ECOWAS) compelled the heads of states to create the West African Power Pool (WAPP). The vision of this system is to set up a common electrical energy market to satisfy the balance between supply and demand at an affordable price using the interconnected network. Forecasting maximum power demand and energy consumption is essential for planning and the coordination of new power plant and transmission lines building. This work consists of predicting maximum power demand and total energy that must transit through the WAPP interconnected network by the year 2032. We compare the performances of three time series models namely the Long Short-Term Memory (LSTM), Auto-Regressive Integrated Moving Average (ARIMA) and Fb Facebook Prophet. Electric power and energy data used for training the systems comes from the WAPP authorties. The results show that, for monthly peaks, the Facebook (Fb) Prophet model is the best, with a MAPE (mean absolute error percentage) of 3.1% and a low RMSE (root mean square error) of 1.225 GW. For energy prediction, ARIMA performances are the best compared to others with (RMSE 1.20 TWh, MAPE 1.00%). Thus, the forecast for total annual energy consumption and annual peak demand will be, respectively, 96.85TWh and 13.6 GW in 2032.

Uncertainty Measures and Business Cycles: Evidence From the US

Most of the macro-literature on uncertainty has focused on macro-uncertainty caused by real activity as a source of economic fluctuations. Economic uncertainty reduces total demand in the economy via a conventional channel that is associated with real option theory. Given the findings of the existing literature, financial uncertainty other than macroeconomic uncertainty matters more for business cycle fluctuations. This study seeks to answer the following questions: Is uncertainty the primary cause of the business cycle’s fluctuations? Alternatively, does it matter what kind of uncertainty exists? The research utilized the generalized linear model (GLM) and the Bayesian generalized linear model (BGLM) to analyze a dataset covering the time from July 1960 to April 2015 in the United States. Elevated levels of macroeconomic uncertainty, akin to real uncertainty, and economic policy uncertainty, as measured by news sources, demonstrate a counter-cyclical pattern in relation to business cycles. Low levels of uncertainty have a positive impact on business cycles, leading to an increase in industrial production. Conversely, high levels of uncertainty have a negative effect on business cycles, causing a decline in industrial output. We are of the opinion that high levels of macroeconomic uncertainty have a ripple effect on the entire economy, which may stifle investments, reduce consumption, and create unemployment, which is likely to influence labor participation. JEL Classification: D81, E23, E32, E44, G14.

Techno-economic analysis (TEA) of zero liquid discharge (ZLD) systems for treatment and utilization of brine via resource recovery

The issue pertaining to brine disposal has generated considerable interest in advanced methodologies aimed at harnessing their potential for resource recovery (i.e., water and salts). This techno-economic analysis investigates the technical and economic outlooks of zero liquid discharge (ZLD) desalination systems, employing two distinct crystallization approaches: membrane-promoted crystallization (MPC) in case 1, and wind-aided intensified evaporation (WAIV) in case 2. The findings indicate that case 1 exhibits a higher drinking water recovery rate (96 %) compared to case 2 (84 %), as the crystallization technology adopted in case 2 (WAIV) does not facilitate freshwater recovery. In both systems, the water is extracted via the implementation of efficient technologies, leading to the attainment of ZLD conditions along with minimal brine volumes. In terms of energy and cost requirements, case 1 necessitates a greater total energy demand (19 kWh/m3) and cost (US$95/day) in contrast to case 2 (15 kWh/m3 & US$83/day). Both cases demonstrate feasibility, yielding profits varying from US$179.19/day to US$221.32/day, contingent upon the sale of solely water or both water and solid salt. The insights provided by this study are poised to facilitate viable utilization and management of brine originating from the seawater desalination industry as well as from diverse brine-generating sectors.

Estimation of Roof Top Rain Water Harvesting Potential: A Proposed Solution to Water Scarcity in Shrigonda Town, Maharashtra, India

The burning issue in cities will be water scarcity in the coming years. The world population in cities has increased from 29.6 percent to 56.2 percent and is predicted to reach 68.4 percent by 2050. Therefore, this study has attempted to find a solution to tackle the urban water scarcity issue. Recently, rainwater harvesting has emerged as a sustainable and effective system for water conservation in urban areas. Hence, the ward-wise rooftop area was calculated and the rooftop rainwater harvesting potential was estimated by applying the Gould & Nissen, formula for Shrigonda Town. The result reveals that the total water demand in the water stress period was 41,34,41,010 litres while the total rainwater harvesting potential was 39,07,42,128 litres, which means about 94.51 % of the total demand will be met after the rooftop rainwater harvesting system is installed. The study concludes that rooftop rainwater harvesting is considered a sustainable and best alternative tool to tackle urban water scarcity.

Impact of fertilizer and pesticide reductions on land use in China based on crop-land integrated model

While chemical fertilizers and pesticides have significantly enhanced crop productivity per unit of land in China, the excessive utilization of these chemicals has led to a range of environmental issues that are not conducive to the sustainable development of China’s agriculture. Controlling the use of fertilizers and pesticides in crop cultivation is therefore necessary and has been adopted as an action plan since 2015 in China. However, the effects of fertilizer and pesticide reductions have not been systematically investigated. This paper explores how yields and land use for rice, wheat, corn, and soybean cultivation shift when reducing their fertilizer and pesticide inputs using China’s provincial crop-land integrated partial equilibrium model (the CPMCL model). Simulation results for different scenarios show that, among the studied crops, rice and wheat exhibit greater adaptability than corn and soybeans. Reducing the use of fertilizers and pesticides within the interval from 0% to 3.5% may increase the total demand of land resources for crop production from 0.220% to 4.21%. Limited land resources will be allocated to more profitable crops to maximize output, which means the land use for wheat production may increase over 20% while for rice, corn and soybean may decrease around 4% under the shock of fertilizer and pesticide reductions. Merely reducing fertilizer and pesticide inputs in crop cultivation may exacerbate the conflict between crop production and land resource conservation in China, which means the technology and efficiency of fertilizer and pesticide use needs to be improved. The findings of this paper can help formulate more province-specific and crop-targeted plans to properly reduce fertilizer and pesticide use, thus promoting sustainable land use while ensuring food security and protecting the environment.

LEAP model-based analysis to low-carbon transformation path in the power sector: a case study of Guangdong–Hong Kong–Macao Greater Bay Area

As a major carbon emitter, the power sector plays a crucial role in realizing the goal of carbon peaking and carbon neutrality. This study constructed a low-carbon power system based on the LEAP model (LEAP-GBA) with 2020 as a statistic base aiming of exploring the low-carbon transformation pathway of the power sector in the Guangdong–Hong Kong, and Macao Greater Bay Area (GBA). Five scenarios are set up to simulate the demand, power generation structure, carbon emissions, and power generation costs in the power sector under different scenarios. The results indicate that total electricity demand will peak after 2050, with 80% of it coming from industry, buildings and residential use. To achieve net-zero emissions from the power sector in the GBA, a future power generation mix dominated by nuclear and renewable energy generation and supplemented by fossil energy generation equipped with CCUS technologies. BECCS technology and nuclear power are the key to realize zero carbon emissions from the power sector in the GBA, so it should be the first to promote BECCS technology testing and commercial application, improve the deployment of nuclear power sites, and push forward the construction of nuclear power and technology improvement in the next 40 years.

Bicarbonate Alternatives in the Neutralization Phase of Leather Tanning to Ensure Sustainability

The post-tanning procedure involves neutralizing the iso-electric point, which ensures that there is no imbalance between carboxylic groups and amino groups. This balance allows for the penetration of dyes, fatliquoring agents, and other chemical materials. Bicarbonate is used during the neutralization phase, and to eliminate it, 4 metric tons of water are needed for each metric ton of leather. Additionally, this leads to an elevation in both Biological Oxygen Demand (BOD) and Chemical Oxygen Demand (COD). The objective of the research was to substitute bicarbonate with sodium borate, sodium acetate, and sodium formate, and neutralise syntan to decrease the quantities of pollutants generated from this process, minimize the consumption of water, and improve the quality of the produced leather. Each experimental group's BOD, COD, microscopic micrographs, physical, chemical, and organoleptic parameters were determined. The use of sodium borate, neutralizing syntan, sodium acetate, and sodium formate resulted in a significant decrease in the discharge of BOD, COD, and water consumption. Furthermore, the use of 2.5% sodium borate has proven to be the most effective neutralizing agent in reducing water consumption by 80%, total oxygen demand by 39% and costs of neutralization chemicals by 0.62%. Also, the physical and chemical properties of the leather product were similar to those of the control. Therefore, the leather that has been neutralized with sodium borate is considered to have the best organoleptic characteristics compared to the control.

Raising Adaptive Capacity to Climate Change in the Energy and Food Sectors of Egypt

Climate change will likely impact food security globally, regionally, and locally. Climate change can disrupt food availability, reduce access to food, and affect food quality. Accordingly, the impacts of climate change on the agricultural sector reflect food security and pose a serious threat to sustainable development. Furthermore, the total energy demand of Egypt is marked by an exponential growth of electricity demand, at a pace much faster than that of GDP, primary energy consumption, and population mainly due to a doubling up of the consumption of Egypt. The expected development of the industrial sector, the accelerated access to electricity, and the improvement of standards of living (directly connected with the consumption of the residential sector) are the reasons for these consumption upsurges. The different components of climatic change such as projected increases in temperatures, changes in precipitation patterns, changes in extreme weather events, and reductions in water availability may all result in reduced agricultural productivity and may cause energy consumption upsurges. The main problem with climatic change and climatic variability in all parts of the Mediterranean Basin is that systematic climate observation programs are, at present, inadequate to permit reliable assessment, quantification, and prediction of climatic conditions and their impacts. More accurate assessments of regional climate variability and change and their related environmental and socio-economic impacts are highly needed.

Forecasting regional water demand using multi-fidelity data and harris hawks optimization of generalized regression neural network models – A case study of Heilongjiang Province, China

Accurate forecasting of water demand plays a crucial role in decision makers to effectively allocate regional water resources and promotes the rational development and utilization of water resources. To address the challenges posed by limited raw data availability and the difficulty in selecting parameters for water demand forecasting models, this study proposes a coupled model called MF-HHO-GRNN (Multi-Fidelity Data, Hybrid Harris Hawks Optimization, and Generalized Regression Neural Network). Initially, multi-fidelity data was constructed employing water demand factor data for Heilongjiang Province, China (1999–2020) as high-fidelity data, alongside data from Liaoning and Jilin Provinces of China as low-fidelity data. Adaptive boosting algorithms, data concatenation, and data dimensionality reduction techniques were employed to construct multi-fidelity data, thereby improving the availability of the original data. Subsequently, Harris hawk optimization algorithms were implemented to optimize the smoothing factor of the GRNN to resolve the challenge of selecting suitable parameters for water demand forecasting models. Finally, the MF-HHO-GRNN model was compared with other prediction models to analyze the prediction accuracy. The optimized MF-HHO-GRNN model meeting accuracy requirements was utilized to forecast agricultural irrigation, industrial, domestic, ecological water demand, and total water demand in Heilongjiang Province for the next 5 years. Results demonstrated that the proposed MF-HHO-GRNN model attained predictive accuracy of 98 %, 98 %, and 97 % for total water demand under three distinct time horizons (1 year, 3 years, and 5 years), proving excellent predictive capabilities. Furthermore, a comprehensive comparison was made between the predicted total water demand and user-specific water demands for the next 5 years in Heilongjiang Province and the regional development plans. The results showed that the predictions of the coupled model aligned with the future development trends of Heilongjiang Province, validating the practicality of the MF-HHO-GRNN model. This study provides decision-makers with an effective method for forecasting water demand, contributing to the future realization of more intelligent and accurate water resource management and decision-making.

Renewable energy input strategy considering different electricity price regulation policies

This paper examines the impact of the electricity price cap regulation and different policies on renewable energy inputs, electricity prices, demands, and the profits of power firm. Specifically, we compare the impact of the peak-trough electricity price policy (PP policy) and the uniform electricity price policy (UP policy) based on electricity price cap regulation. The findings are as follows: (1) Regardless of the cap, the UP policy consistently results in no lower renewable energy input level and total electricity demand compared to the PP policy. However, power firm earns higher profit in the PP policy. (2) During peak period, the electricity price in the PP policy is not lower than in the UP policy, but the electricity demand is lower. Conversely, during the trough period, the electricity price in the PP policy is lower, and the electricity demand is higher than in the UP policy. (3) When the firm is subject to the electricity price cap regulation, increasing the cap leads to higher electricity prices, renewable energy input levels, total demands, and firm profits. In the absence of the cap regulation, factors of cross-price competition and renewable energy preference increase all equilibrium solutions, while the renewable energy input cost factor has the opposite effect. In the field of renewable energy input, there is no literature considering the impact of the electricity price cap regulation, while our study considers the input behavior of power firm to renewable energy through electricity price cap regulation and different pricing policies. The findings provide substantial theoretical and practical insights for power firm and government in decision-making processes.

The long-term effect of COVID-19 policy stringency on consumer food demand quantities in Switzerland

This is the first study investigating the effect of COVID-19 policy stringency on consumer food demand for the years 2020 and 2021. In particular, we compared food demand in periods with strict COVID-19 policies to food demand in periods with less strict COVID-19 policies. For this purpose, we used Switzerland, which imposed two COVID-19 lockdowns, as a case study. To test this link, we applied fixed effects dummy variable regressions (as baseline estimates) and dose–response functions. To capture the stringency of Swiss COVID-19 policies, we relied on daily data from the Oxford COVID-19 Government Response Tracker. Food demand data at the product level came from the combined retail and consumer panel of the market research company Nielsen and covered meat, milk products, vegetables, and fruits. Empirical findings revealed that consumer demand for all food products was on average 2.5 times higher during the two lockdowns compared to periods without lockdowns. While we found no statistically significant differences in consumer food demand between the two lockdowns for milk products, vegetables, and fruits, the total food demand and the demand for meat was higher during the first lockdown. Increases in Swiss food demand were likely caused by the closing of restaurants (both lockdowns) and the closing of borders to neighboring countries (only the first lockdown), preventing shopping tourism. Against the background of potential future pandemics, our research provides important information for policymakers on the quantification of food demand changes in times of crisis.

Evaluating Rainwater Harvesting Systems for Water Scarcity Mitigation in Small Greek Islands under Climate Change

Rainfall variability, exacerbated by climate change, poses significant challenges to water resource management, particularly in regions prone to intense droughts and floods. The Greek islands, characterized by poor water potential, face interannual water supply issues dating back to their earliest habitation. Rainwater harvesting (RWH) systems emerge as a promising solution to address water scarcity in these regions. This study simulates RWH systems for two small Greek islands, Fourni and Nisyros, representing similar rainfall regimes. Multiple scenarios are explored, and system reliability is assessed in light of simulated daily rainfall time series incorporating climate change projections. Utilizing eight low/medium (RCP 4.5) and eight high (RCP 8.5) emission scenarios over a future 35-year period, the study evaluates system reliability based on model parameters (collection area: 40 to 140 m2, rainwater tank volume: 5 to 30 m3, number of household members: 2, 3), with 30% coverage of total daily water demand (180 L/d). Negligible evapotranspiration effects are assumed due to closed-type tanks. Results indicate that the RWH system demonstrates high efficiency in general. The investigation for the future period revealed that the system’s performance varies, with instances where daily demand targets are not met, even with a 30 m3 tank. This research underscores the potential of RWH systems as a cost-effective “green” solution, particularly in regions with deficient rainfall regimes. It highlights the importance of localized water management strategies, reducing reliance on mainland water transportation, and assisting desalination unit operations. In conclusion, this study contributes to the assessment of RWH systems, demonstrating their viability as a sustainable water management solution in regions facing water scarcity, contingent on local rainfall conditions and system design parameters.

A Forward–Backward Simheuristic for the Stochastic Capacitated Dispersion Problem

In an effort to balance the distribution of services across a given territory, dispersion and diversity models typically aim to maximize the minimum distance between any pair of facilities. Specifically, in the capacitated dispersion problem (CDP), each facility has an associated capacity or level of service, and the objective is to select a set of facilities so that the minimum distance between any pair of them (dispersion) is maximized, while ensuring a user-defined level of service. This problem can be formulated as a linear integer model, where the sum of the capacities of the selected facilities must match or exceed the total demand in the network. Real-life applications often necessitate considering the levels of uncertainty affecting the capacity of the nodes. Failure to account for this uncertainty could lead to low-quality or infeasible solutions in practical scenarios. However, research addressing the stochastic version of the CDP is scarce. This paper introduces two models for the CDP with stochastic capacities, incorporating soft constraints and penalty costs for violating the total capacity constraint. The first model includes a probabilistic constraint to ensure the required level of service with a certain probability, while the second model introduces a soft constraint with penalty costs for violations. To solve both variants of the model, a forward–backward simheuristic algorithm is proposed. Our approach combines a metaheuristic algorithm with Monte Carlo simulation, enabling the efficient handling of the random behavior of node capacities and obtaining reliable solutions regardless of their probability distribution.

Construction of carbon sequestration ecological network in Linyi City based on supply and demand of ecosystem service.

The increasing carbon emissions is one of the important reasons for global warming. As a key area of carbon emissions, carbon sequestration capacity of cities is urgently needed to be improved. Carbon sequestration ser-vices can be transferred between supply and demand areas due to the circulation of atmosphere. With Linyi City as an example, we used the minimum cumulative resistance model to extract the matching path of supply and demand, and constructed a carbon sequestration ecological network. The results showed that the regions with high supply of carbon sequestration services were located in the north and south of the study area, and that current total supply could solve about 60% of the total demand. Although the spatial distribution of supply and demand was uneven, 54% of the areas that could meet the surrounding carbon sequestration demand were still idle. The optimized supply-demand matching paths could maintain good transmission efficiency of material and energy, with lower costs. Paths with strong potential carbon sequestration capacity were located in the central and northwest part of the research area. In the construction of carbon sequestration ecological network, it is necessary to strengthen the protection and restoration of the supply side of carbon sequestration services, realize carbon reduction and strengthen carbon sequestration on the demand side, and optimize the matching path of supply and demand. This method provided services to the demand areas through the oversupply of ecosystem services, optimized the overall resource allocation, which could advance regional carbon sequestration capacity.

Identification of optimal number and location of isolation valves in an urban water distribution network

Abstract Urban water distribution networks (UWDNs) are critical infrastructures that provide essential services in an urban setting. Such infrastructures are subject to frequent breakdowns, disrupting services to downstream users. Installation of isolation valves (IVs) at strategic locations can reduce such adverse impacts by isolating small segments of the network and expediting repairs, which in turn contribute to water conservation and leak control. However, determining the optimal number of IVs and their placement is a disturbing question for the researchers. This study proposes a methodology to assess the optimal number of IVs in a UWDN and identify their placement in the best of the worst possible scenarios. Based on the network topology and the associated IV costs, it identifies the optimal numbers and their places to minimize the maximum undeliverable demand. The methodology is illustrated with the help of a small water distribution network. Thereafter, the proposed methodology is applied to a real-type UWDN. The results indicate that the optimal number of IVs for the case study is 10, which should be placed at strategic locations to reduce the maximum undeliverable demand to 18% of the total demand.

Optimization path of China’s energy industry structure under low carbon economy situation

The study discusses the main aspects of optimizing the structure of China’s energy industry in a situation with a low-carbon economy. To build a model for forecasting electricity demand, the method of partial least squares regression is used. The basic scenario and the scenario with restrictions are set taking into account the peculiarities of the development of a new normal economy. Based on the baseline scenario and the restricted scenario, the total energy demand, energy consumption structure and CO2 emissions in China are projected. Taking into account energy, economic and environmental factors, a multi-purpose optimization model of the energy consumption structure was built and the structure of China’s energy consumption and the corresponding CO2 emissions under optimization scenarios were obtained. This research describes revise the energy consumption structure in China, should reducing energy consumption and carbon dioxide emissions is very helpful.

Using Surrogate Parameters to Enhance Monitoring of Community Wastewater Management System Performance for Sustainable Operations.

Community wastewater management systems (CWMS) are small-scale wastewater treatment systems typically in regional and rural areas with less sophisticated treatment processes and often managed by local governments or communities. Research and industrial applications have demonstrated that online UV-Vis sensors have great potential for improving wastewater monitoring and treatment processes. Existing studies on the development of surrogate parameters with models from spectral data for wastewater were largely limited to lab-based. In contrast, industrial applications of these sensors have primarily targeted large wastewater treatment plants (WWTPs), leaving a gap in research for small-scale WWTPs. This paper demonstrates the suitability of using a field-based online UV-Vis sensor combined with advanced data analytics for CWMSs as an early warning for process upset to support sustainable operations. An industry case study is provided to demonstrate the development of surrogate monitoring parameters for total suspended solids (TSSs) and chemical oxygen demand (COD) using the UV-Vis spectral data from an online UV-Vis sensor. Absorbances at a wavelength of 625 nm (UV625) and absorbances at a wavelength of 265 nm (UV265) were identified as surrogate parameters to measure TSSs and COD, respectively. This study contributes to the improvement of WWTP performance with a continuous monitoring system by developing a process monitoring framework and optimization strategy.

A cooperative vehicle routing problem with delivery options for simultaneous pickup and delivery services in rural areas

The booming e-commerce is challenging express companies by requiring higher logistics service efficiency in rural China. This study investigates a cooperative vehicle routing problem for simultaneous pickup and delivery requests, in which the delivery orders can be fulfilled either by home delivery or customer pickup. The delivery option for each order is complex due to the optional cooperative relationships among express companies, the inter-dependence between self-pickup site selection and the overall online vehicle routing scheme, and the distance-dependent compensation to self-pickup customers. The problem is formulated as a mixed integer linear programming model and solved by a tailored adaptive large neighborhood search algorithm. A cost-saving allocation mechanism based on the core guaranteed Shapley value is applied to carrier collaboration. The numerical results show that the newly introduced cooperative distribution system can significantly reduce operational costs. Such improvements are robust even if the total demand changes or under different rural logistics network topologies.

Study on the mechanism of action of methane production by co-fermentation of sludge and lignite.

To improve the methanogenic efficiency of lignite anaerobic fermentation and explore innovative approaches to sludge utilization, a co-fermentation technique involving lignite and sludge was employed for converting biomass into biomethane. Volatile suspended solids were introduced as a native enrichment of the sludge and mixed with lignite for fermentation. The synergistic fermentation mechanism between sludge and lignite for biomethane production was analyzed through biochemical methane potential experiments, measurement of various parameters pre- and post-fermentation, observation of bacterial population changes during the peak of reaction, carbon migration assessment, and evaluation of rheological characteristics. The results showed that the addition of sludge in the anaerobic fermentation process improved the microorganisms' ability to degrade lignite and bolstered biomethane production. Notably, the maximum methane production recorded was 215.52mL/g-volatile suspended solids, achieved at a sludge to coal ratio of 3:1, with a synergistic growth rate of 25.37%. Furthermore, the removal rates of total suspended solids, and total chemical oxygen demand exhibited an upward trend with an increasing percentage of sludge in the mixture. The relative abundance and activity of the methanogens population were found to increase with an appropriate ratio of sludge to lignite. This observation confirmed the migration of carbon between the solid-liquid-gas phases, promoting enhanced system affinity. Additionally, the changes in solid-liquid phase parameters before and after the reaction indicated that the addition of sludge improved the system's degradation capacity. The results of the study hold significant implications in realizing the resource utilization of sludge and lignite while contributing to environmental protection endeavors.

Bioactive carbohydrate from potato peels: A sweet inducer that mediate resistance against powdery mildew disease of cucumber through phytohormonal alterations

Large volumes of nutritive wastes are generated by food industries, which can be used in the production of bioactive compounds of commercial values. The waste generated by potato chips industries contains high quantities of insoluble starch, high concentrations of total suspended solids and chemical oxygen demand, or environmental issues. In this study, the starch extracted from the potato peels was subjected to bioconversion of isomaltose-oligosaccharide by enzymatic method and further eluted isomatlose by liquid chromatography-mass spectrometry. The structural elucidation of isomaltose was confirmed by 1H NMR and 13C NMR spectroscopy. The purified isomaltose displayed excellent in vitro antifungal action against Erysiphe cichoracearum and Fusarium oxysporum at concentrations 1.0 and 2.5 mg/ml, respectively. Notably, cucumber-seeds primed with isomaltose (2.5 and 5.0 mg/mL) concentrations recorded a significant improvement of germination (91.5 and 89 %) and vigor (2210.93 and 2015.7) over the untreated control. Subsequently, the isomaltose-primed cucumber plants challenged with powdery mildew pathogen showed enhanced protection of 63% in comparison with pathogen alone-induced plants. This enhanced growth parameters and induced resistance in cucumber may be fairly contributed by the upregulation of phytohormone levels in primed plants observed in this study. Taken together, this study is unique in the use of bioactive isomaltose from potato peels, which could enable us to minimize the agro-industrial wastes and most importantly could help to develop new formulations for sustainable crop protection strategies.