Input Costs Research Articles

Modelling and Forecasting Future Retail Price of Capsicum Annum L. Var. Kulai for Food Security and SDG Issues in Perlis, Malaysia

Objective: This study focuses on the modeling and forecasting of the retail price of Capsicum Annum L. Var. Kulai in Perlis, Malaysia, as a measure to support food security initiatives. Theoretical Framework: Food security is a pressing global issue exacerbated by factors such as climate change, conflicts, and the COVID-19 pandemic. Malaysia, ranked 41st in The Global Food Security Index (GFSI) 2022, has seen a concerning rise in food insecurity, driven by increased agricultural input costs and a high dependency on food imports. Method: Using historical monthly time series data from January 2018 to May 2023, various univariate time series models were employed, including Naïve, Seasonal Naïve, Holt’s Method, and ARIMA models. Results and Discussion: The study found that Holt’s Method provided the most accurate forecasts, with a mean absolute percentage error (MAPE) of 0.4607. The model predicts a continued increase in chili prices, which could pose challenges to food security in the region. Research Implications: These findings underscore the importance of accurate price forecasting in formulating effective agricultural policies and supporting local communities in mitigating food insecurity. This research contributes to worldwide initiatives aimed at fulfilling SDGs for goal 2 (Zero Hunger and Sustainable Agriculture), goal 11 (Sustainable Cities and Communities), and goal 13 (Climate Action). Originality/Value: This study offers valuable insights into forecasting the price of Capsicum Annum L. Var. Kulai in Perlis, Malaysia. Food security challenges have increasingly affected this area as various univariate time series models have been applied, and Holt’s method has been identified as the most effective. Providing policymakers with reliable forecasts guide strategic agricultural policies and supports food security efforts.

Economics of Seed Spices in Gujarat: Analyzing Parity of Cost, Price, and Income

This study analyzes the cost, price, and income parity in three major seed spices cultivated in Gujarat by examining indices of average input prices, Farm Harvest Prices, cost of production, and gross income to evaluate the profitability and challenges faced by farmers. The secondary data on input cost, cost of production and gross income were collected for the period of eleven years from 2011-12 to 2021-22 from the reports of “The Scheme for Farm Cost Studies of Important Crops in Gujarat State” and “The Scheme for Creating a Permanent Machinery for studying Cost of Cultivation/ Production of Principal crops grown in Gujarat state, further analysis of parity indices were estimated by taking 2011-12 as base year. The results indicate that for cumin crop, input prices grew significantly, while farm harvest prices exhibited a non-significant increase. Parity indices between Farm Harvest Prices and input prices remained below 100, indicating that farm harvest prices did not cover rising input costs. However, in years like 2016-17, 2018-19, and 2021-22, the farm harvest price and gross income were favorable, indicating profitability for farmers. In fennel, input prices and production costs showed significant growth, while farm harvest prices and gross income had minimal increases. Parity indices suggested that farm harvest prices were insufficient to cover rising costs in most years, though 2012-13 and 2021-22 were favorable for farmers in terms of both price and income. Coriander, with significant growth in input prices, showed a slight increase in farm harvest prices and a decrease in production costs. Parity indices indicated that the farm harvest price consistently exceeded input prices and the cost of production, ensuring favorable profitability and encouraging investment in coriander cultivation. Overall, the findings underscore the need for policy interventions to stabilize farm harvest prices and control input cost inflation, ensuring sustained profitability for farmers growing seed spices.

Influence of Seed Priming, Plant Geometry and Conjunctive Use of Fertilizers, FYM and Vermicompost on Productivity and Economics of Green Gram (Vigna radiata L.)

Background: Nutrients requirement of crops can easily be met by the application various fertilizers alone but in long run their continuous use deteriorate soil health and may retard the productivity of crops also. Further cost escalation and timely availability of fertilizers and other inputs lead to uneconomic production. Integrated nutrient management (INM) practices including reduced levels of fertilizers with locally available organic sources of plant nutrients, low cost and no cost inputs may be answer to the problems. Very meagre work has been done in past on different aspects on green gram crop. Present study aimed at evaluating and quantify the performance of summer green gram (Vigna radiata L.) crop as affected by seed hydropriming, plant geometry and nutrient applications through fertilizers, FYM, vermicompost and their combinations for maximizing the productivity and economic viability. Methods: The low cost seed hydropriming, no cost treatments of 2 plant geometries of (i) G1 (30´10 cm) and (ii) G2 (30´20 cm) and 5 treatments of integrated nutrient management (INM) practices (N) viz; (i) N1 (20+40+20 kg NPK/ha (RDF), (ii) N2 (100% RDF equivalent FYM), (iii) N3(100% RDF equivalent vermicompost) (iv) N4(50% RDF from fertilizer+50% RDF equivalent FYM) and (v) N5 (50% RDF from fertilizer+50% RDF equivalent vermicompost) were evaluated in field experiments using split-split plot design having 3 replications. Result: The main conclusion is that practices of seed hydropriming and planting geometry of 30´10 cm proved superior for realizing maximum productivity and profitability. Integrated application of fertilizer equivalent to 50% of recommended dose of fertilizers (RDF) coupled with 50% nutrients through organic sources like farmyard manure and or vermicompost (treatments N4 and N5) proved most effective over organic sources alone (FYM and vermicompost through treatments N2 and N3) and 100% RDF through fertilizers (N1) for summer green gram cultivation on sustainable basis. The results of the present work will be useful for majority of farmers particularly pulse crops growers to bridge the gap between present level of productivity and potentially realizable productivity of moong bean crop on cost effective and sustainable basis.

Understanding farmers’ intentions and challenges in organic farming: Policy recommendations for sustainable transition

This paper investigates farmers' intentions toward adopting organic farming practices and the associated challenges they encounter. Through a combination of surveys, interviews, and field observations, the study reveals a notable interest among farmers in transitioning to organic farming but identifies significant barriers that prevent this shift. Key challenges include limited availability and high costs of organic inputs, inadequate technical support, and financial constraints. The findings highlight the urgent need for policy interventions to address these issues effectively. Recommendations for policymakers include improving access to affordable organic inputs, expanding educational and technical support programs, and implementing financial assistance schemes to alleviate initial investment burdens. By addressing these challenges, policymakers can facilitate a smoother transition to organic farming, supporting farmers in their pursuit of sustainable agricultural practices and contributing to the overall resilience and sustainability of the agricultural sector.

The Costs of a Multisectoral Nutrition Program Implemented Through a Poultry Value Chain Platform in Burkina Faso

ABSTRACTUndernutrition in women and young children in Burkina Faso is a critical problem. Egg consumption is low despite many households raising poultry. The Soutenir l'Exploitation Familiale pour Lancer l'Élevage des Volailles et Valoriser l'Économie Rurale (SELEVER) project, an integrated agriculture‐nutrition intervention, promoted egg consumption and sales to investigate the impact of poultry production on child nutrition. Multisectoral nutrition‐sensitive agriculture programs address nutrition deficits but lack comparable cost information. This study estimates the costs of the SELEVER program, an integrated poultry and nutrition intervention. The study estimates the program's economic costs using a standardized methodology from the Strengthening Economic Evaluation for Multisectoral Strategies for Nutrition (SEEMS‐Nutrition) consortium, which aligns financial and economic costs along program impact pathways, allocating costs by activities and inputs. We conducted qualitative interviews and focus groups on time allocation and beneficiary out‐of‐pocket costs. Incremental economic costs were calculated by combining expenditures and economic costs. The total incremental program cost was USD$18,084,727.68 over 5 years, with annual incremental costs of USD$209.20 per direct beneficiary and $796.26 per household. Major cost drivers included overhead (18%), poultry extension (17%), training (16%), household counseling (7%), technical assistance (7%) and microcredit (6%). Total input costs were dominated by personnel (51%), supplies (13%), agricultural inputs (10%) and overhead (9%). We present the total incremental costs of a multisectoral nutrition intervention to generate revenue with poultry. The costs per beneficiary were higher than similar interventions, underscoring the need for cost‐effectiveness evaluations of multisectoral nutrition programs. A standardized cost methodology facilitates comparisons with multisectoral nutrition interventions and builds the evidence base.

Exploring the Role of Smart Systems in Farm Machinery for Soil Fertility and Crop Productivity

Agriculture is experiencing a period of technological change, driven by the addition of intelligent technologies into agricultural technology. The integration of smart systems into farm machinery has greatly improved soil fertility management and crop productivity. Advanced technologies such as sensors, IoT, AI, and precision agriculture tools enable real-time monitoring of critical soil parameters, leading to targeted interventions for improving soil health. Automated machinery with GPS and AI-driven algorithms ensures efficient seed placement, precise fertilizer application, and weed management, thereby minimizing resource wastage and environmental impact. Such insights based on data allow farmers to take appropriate decisions based on changing conditions and improve farming practices sustainably, but their large-scale adaptation can be impeded due to high implementation costs, issues with privacy over the data, and expertise over technicalities. But even these challenges are seen in light of increasing yield, input costs reduced, and sustainability-promoting benefits, thereby raising productivity and meeting the causes for environmental conservation and food security.

Viability of the open-pit cultivation of bell peppers in Meoqui, Chihuahua

Chili bell pepper (Capsicum annuum L.) has its origin in South and Central America, domesticated in Mexico (Mendoza, 2010), and is part of the small genus of tropical herbs. In Mexico, there is a lack of sufficient economic information about the production costs of the chile bell pepper crop; however, it is considered an economic alternative due to the low input costs it requires. The objective of this study was to determine the economic viability of this crop in a plot established in the municipality of Meoqui Chihuahua, Mexico, where the costs of cultural activities and necessary inputs were collected from land preparation, establishment of the plantation until harvest, and the financial indicators net present value (NPV), internal rate of return (IRR) and the benefit-cost ratio (B/C) were considered. A B/C ratio of 1.26 was obtained, an IRR of 22%, higher than the discount rate (12%), which indicates viability.

Encuesta a las empresas españolas sobre la evolución de su actividad: cuarto trimestre de 2024

Rationale The Banco de España Business Activity Survey (EBAE) provides highly valuable, real-time information on a broad sample of Spanish firms’ turnover, employment, costs and prices. This helps to diagnose current economic developments. Takeaways •Firms perceive an increase in turnover in 2024 Q4, compared with the decreases in the same quarter of 2022 and 2023. Those located in the Valencia region have reported adverse turnover developments as a result of the impact of the flash floods. •Inflationary pressures have ticked up slightly in Q4, in both the cost of inputs and selling prices. •The percentage of firms affected by higher borrowing costs and insufficient demand has fallen, but economic policy uncertainty and labour shortages remain high. •In a module on advanced technologies, 3% of respondent firms reported a high or moderate use of artificial intelligence (AI) systems and 11% are experimenting with them. For firms not yet using AI, the main barriers are a lack of skilled staff, prohibitive costs and significant uncertainty about the legal ramifications.

Climate-smart agriculture: A review of sustainability, resilience, and food security

This paper investigates Climate Smart Agriculture (CSA), a comprehensive strategy aimed at improving agricultural efficiency and sustainability while addressing the challenges of climate change. It examines the economic advantages of CSA for adopters compared to traditional farming methods and assesses CSA's role in mitigating climate change, adapting to its impacts, and enhancing food security. The study reviews essential CSA practices, including agroforestry, conservation agriculture, water-efficient irrigation technologies, crop diversification, improved livestock management, and soil carbon sequestration, as well as the barriers to adoption, such as limited funding, arable land, land tenure issues, and insufficient expertise. Agroforestry and crop rotation have shown encouraging results, with agroforestry serving as a cost-effective solution for food production and environmental preservation. Dairy companies boosted milk consumption from 529,000 to 3 million liters, while farmer profits grew from $0.2 to $0.3 per liter. Rice yields have increased, from 3-4 tons to 7.5 tons per hectare. In cotton farming, CSA adopters cut input costs compared to traditional methods, resulting in long-term economic gains. Crop rotation increased maize productivity by 5–10%, while new irrigation techniques improved water efficiency by 5–35%. However, regions without CSA methods experienced significant livestock losses, highlighting the importance of widespread adoption to ensure resilience. Despite CSA’s advantages, its widespread adoption is hindered by financial and knowledge barriers. Future research should focus on optimizing multiple cropping systems, crop diversification, and no-till agriculture. CSA, particularly when integrated with technologies like the Internet of Things (IoT), offers a promising path toward more adaptive and resilient agricultural practices. Broader adoption will require investments in research and resources to effectively scale CSA innovations.

Hormonal efficiency and net return of BARI Tomato-4 enhanced under polytunnels during rainy summer season

An experiment was conducted at the department of Horticulture, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, Bangladesh to evaluate the benefit cost ratio of summer tomato variety BARI tomato 4. The experiment was laid out in a split plot design with 18 treatments and three replications by maintaining a spacing of 60 cm x 40 cm. It comprised of two cultivation method as main plot viz. Open cultivation (P0) and Cultivation under poly tunnel (P1) and nine levels of growth regulators as sub-plot viz. T0 (Control), T1 (GA3@30 ppm), T2 (GA3@60 ppm), T3 (NAA @30 ppm), T4 (NAA @60 ppm), T5 (MH @30 ppm), T6 (MH @60 ppm), T7 (Tomatotone @30 ppm) and T8 (Tomatotone @60 ppm). Application of growth regulators was influenced in all studied parameters over control. Majority of the parameters responded better with the increased concentration of growth regulators. Tomatotone @ 60 ppm gave the highest yield per hectare (5.38 and 20.82 t) under open and poly tunnel condition, respectively. In open and poly tunnel condition, tomatotone @ 60 ppm showed the highest profitability and benefit cost ratio 1.16: 3.19, respectively. Despite of poly tunnel was being costly to establish (41% of total input cost), but it gave 3-4 times higher economic return. Higher values in respect of economy were obtained from the plants cultivated under poly tunnel with tomatotone @60 ppm. Therefore, tomatotone @ 60 ppm can be used as potential treatment for summer tomato cultivation under open and poly tunnel conditions to get highest profitability.

A Review on Detection of Nutrients of Soil Using NPK and Moisture Sensors

With an emphasis on the combination of NPK (nitrogen, phosphorus, and potassium) and moisture sensors, this review paper explores the critical role that contemporary sensor technology plays in identifying soil nutrients and moisture levels. Precision agriculture, which seeks to optimize irrigation and fertilization techniques based on real-time data, depends on accurate measurement of these parameters. The study looks at different kinds of moisture and NPK sensors, describing how they operate and how they are used in agricultural settings. There are various advantages to incorporating these sensors into farming operations. One of the biggest benefits is increased agricultural yields since optimal plant growth is ensured by accurate fertilizer and moisture management. Another important advantage is cost effectiveness; farmers can save input costs and boost profitability by eliminating excessive fertilization and irrigation. Additionally, efficient resource usage promotes sustainable farming methods, which improve soil health and lessen environmental deterioration. The content of vital nutrients in the soil can be determined using NPK sensors. These sensors allow farmers to customize their fertilization plans to match the unique requirements of their crops by giving them real-time information on the levels of nitrogen, phosphorus, and potassium. This accuracy guarantees that plants get the appropriate quantity of nutrients at the right time, leading to improved crop yields and reduced environmental impact. This paper identifies the need for developing superior systems for soil monitoring to strengthen precision agriculture, crop production, and sustainable farming.

Simulation of Carbon Tax Impact on the Competitiveness of the Manufacturing Industry in Indonesia Using a System Dynamics Approach

This study investigates the impact of carbon tax on the competitiveness of Indonesia’s manufacturing sector using a System Dynamics (SD) approach. The analysis explores how different carbon tax levels—0, 30, and 200 IDR/kg CO2e—affect production inputs, outputs, and added value. The results show that manufacturing inputs remain low and stable at 0 IDR/kg CO2e due to the lack of financial pressure to reduce fossil fuel consumption. However, input costs increased slightly at 30 IDR/kg CO2e, prompting industries to adopt energy-efficient technologies to manage costs. The highest tax level, 200 IDR/kg CO2e, significantly raises input costs, compelling manufacturers to invest in low-carbon technologies to mitigate the cost burden. The study also assesses the impact of carbon taxes on output and value-added in the manufacturing sector. While carbon taxes initially reduce value added due to increased input costs, investments in green technologies can help companies recover and improve productivity over time. Higher tax rates, such as 200 IDR/kg CO2e, push industries towards significant technological shifts, potentially enhancing long-term competitiveness. The research highlights the importance of supportive policies, including subsidies for renewable energy and efficiency incentives, to facilitate the transition to greener production methods. Overall, the study concludes that well-designed carbon tax policies can drive industrial sustainability while maintaining economic growth in Indonesia.

Economic cost of hemodialysis and peritoneal dialysis under public–private partnership in a public tertiary care centre of Puducherry, India

ABSTRACT Background India faces over 220 000 lakh new kidney failure cases annually, requiring approximately 34 million dialysis sessions, creating a significant economic burden on the healthcare system. This study estimates the costs of providing hemodialysis (HD) and Continuous Ambulatory Peritoneal Dialysis (CAPD) under a Public–Private Partnership (PPP) in a tertiary hospital. Methods Economic health system costs (October 2021–2022) were estimated using a bottom-up approach. Resources consumed were identified, measured, and valued. Capital costs were annualized and discounted at 3%. Sensitivity analysis assessed the impact of variations in input costs. Results The total annual economic cost for HD (n = 103) under PPP was INR 32 611 618 (USD 393 432), and for CAPD (n = 12) was INR 4 103 781 (USD 49 509). The annual cost per beneficiary for HD and CAPD was INR 316 618 (USD 3820) and INR 341 979 (USD 4126), respectively. Unit cost per HD session was INR 1856 (USD 22) and per CAPD exchange was INR 323 (USD 4). Conclusion This study provides detailed costs of HD and CAPD services under PPP, offering insights for expanding dialysis services under the Pradhan Mantri National Dialysis Programme and supporting cost-effectiveness analysis for resource allocation.

Cost-effectiveness of first-line systemic therapies for unresectable hepatocellular carcinoma.

To examine the cost-effectiveness of first-line systemic therapies recommended by the National Comprehensive Cancer Network guidelines for Unresectable Hepatocellular Carcinoma (uHCC) from the US social and payer's perspective. A cost-effectiveness analysis was conducted using a three-state partitioned survival model to assess the cost-effectiveness of atezolizumab plus bevacizumab, tremelimumab plus durvalumab, durvalumab, lenvatinib and sorafenib as first-line treatments for uHCC. Clinical efficacy was derived from a published network meta-analysis. Cost and utility inputs were collected from literature. Main outcomes measured were quality-adjusted life year (QALY), and incremental cost-effectiveness ratio (ICER). Univariate and probabilistic sensitivity analyses, as well as scenario analyses were performed. Over a 10-year time horizon, atezolizumab plus bevacizumab yielded the highest QALYs. Compared to sorafenib, atezolizumab plus bevacizumab, tremelimumab plus durvalumab and lenvatinib had ICERs of $196 704/QALY, $800 755/QALY and $2 032 756/QALY, respectively. Sorafenib was dominated by durvalumab due to lower QALYs and higher costs. At a willingness-to-pay threshold of $150 000/QALY, probabilistic sensitivity analysis revealed that durvalumab had a 99.96% probability of providing the highest net monetary benefit. At a willingness-to-pay threshold of $150 000/QALY, durvalumab is likely the most cost-effective first-line systemic therapy for uHCC compared to sorafenib. Although atezolizumab plus bevacizumab yielded the highest QALYs, their ICERs exceeded the commonly accepted cost-effectiveness threshold ($150 000$ per QALY gained). These findings can inform clinical decision-making, resource allocation and future research priorities in managing uHCC.

Study on Cost and Returns of Cash Crops in Sirmour District, Himachal Pradesh, India

The present study examines the cost and returns of major cash crops raised by different category of farmers in district Sirmour, Himachal Pradesh. The study also identified the different production problems faced by farmers using weighted rank method. Two stage stratified random sampling technique was followed to select a sample of villages and the ultimate farmers. A random sample of 60 farmers was chosen for the study. The major findings revealed that production of vegetables varied from 6.42 qtl for peas to as high as 25.93 qtl of tomato per farm. Garlic being a spice crop recorded the production of 14.37 quintal per farm. In the study, per hectare cost of cultivation was found to be highest for tomato, i.e., Rs. 34200, followed by garlic (Rs. 26134) and beans (Rs. 15427) and lowest for peas (Rs. 11247), The per hectare net return was found to be higher for garlic crop (Rs.115066) when compared to tomato crop (Rs. 55785), beans and peas (Rs. 17108 to Rs. 6703). Therefore, garlic crop was found to be the most profitable crop with the net return of Rs. 115066 which was more and double of profit earned from tomato (Rs. 55785), peas (Rs. 6703) and beans (Rs. 17108). Similarly, the cost of cultivation was found to be highest for the large farmers and the per hectare net return also seemed to be the highest for the large farmers. Likewise, gross returns were also found highest for large farmers than that of small farmers. Further, the study revealed that major production problems faced by the farmers were availability of quality seed, high cost of inputs which were rated at top, followed by monkey & stray animals, quality of seed not available, high cost of inputs and high incidence of pest and pesticides etc. In order to increasing farm production and to minimise operational costs, the availability of high yielding variety seeds, reasonable prices of inputs like seed, fertilizers, pesticides etc., may enhance the farmers’ net return and income.

Exploring Feed Efficiency in Beef Cattle: From Data Collection to Genetic and Nutritional Modeling.

Increasing feed efficiency in beef cattle is critical for meeting the growing global demand for beef while managing rising feed costs and environmental impacts. Challenges in recording feed intake and combining genomic and nutritional models hinder improvements in feed efficiency for sustainable beef production. This review examines the progression from traditional data collection methods to modern genetic and nutritional approaches that enhance feed efficiency. We first discuss the technological advancements that allow precise measurement of individual feed intake and efficiency, providing valuable insights for research and industry. The role of genomic selection in identifying and breeding feed-efficient animals is then explored, emphasizing the benefits of combining data from multiple populations to enhance genomic prediction accuracy. Additionally, the paper highlights the importance of nutritional models that could be used synergistically with genomic selection. Together, these tools allow for optimized feed management in diverse production systems. Combining these approaches also provides a roadmap for reducing input costs and promoting a more sustainable beef industry.

Economics and Marketing of Hub and Spoke based Model: A Descriptive View of Mint Business in Northern India

India has total mint production of 39,000 t covering an area around 3,36,000 ha. Last 15 years’ studies were taken into consideration to find the three items viz; Producer’s Net Price, Price Spread and Producer’s share in Consumer Rupee with their highest and lowest values. It was found that highest Producer’s net price was received through Channel II (U.S. Nagar, Uttarakhand), highest price spread in channel II (Sitapur) and highest Producer’s share in Consumer Rupee was received though channel1 (Moradabad), while lowest Producer’s net price was received through Channel II (Rampur), lowest price spread in channelI (Moradabad) and lowest Producer’s share in Consumer Rupee was received though channel II (Sitapur). Numbers of lacunas were observed in existing supply chain viz. high input cost, inadequate market informationand improper price mechanism. Present study proposes “A Hub and Spoke Based Mint Business Model” which directly approaches buyer without any intermediaries. This business model would increase per kg return and decrease amount of costs.

Hatay’ın Su ürünleri ihracatını canlandırma yolunda zorluklar: Karşılaştırmalı bir analiz (2008-2023)

A comparative analysis of seafood exports in the Hatay region between 2008 and 2023, in relation to overall trends in Türkiye and different regions, was conducted. Seafood export data was obtained from the Turkish Statistical Institute. The export amount has been in a long-term decline fishing and seafood production potential of Hatay, contrary to the general trend in Türkiye. Specifically, the export amount decreased by 62% since 2018, while it decreased by 22.65% in 2023 compared to the previous year. This ongoing downward trend can be attributed to the COVID-19, Syrian civil war, and the recent devastating earthquake in the region. Despite the high potential for seafood production in the region, investments have been limited due to the lack of allocation in organized industrial zones. Additionally, the absence of a wholesale fish market is a major issue preventing the emergence of a regional market. All these factors have caused disruptions in the supply chain and production, increased input costs, and market uncertainties both domestically and internationally. This indicates that infrastructure investments in the region must be prioritized by all stakeholders, the central authority, decisionmakers and policymakers for sustainable seafood exports contributing to regional development. In conclusion, despite the strong industrial and logistics infrastructure in Iskenderun Bay, the seafood sector in Hatay has failed to reach its full potential, unlike the national trend in Türkiye. This shortfall is directly reflected in export values. Therefore, necessary measures must be taken to effectively utilize the region's seafood potential.

Joint Communication and Channel Discrimination.

We consider a basic joint communication and sensing setup comprising a transmitter, a receiver and a sensor. The transmitter sends a codeword to the receiver through a discrete memoryless channel, and the receiver is interested in decoding the transmitted codeword. At the same time, the sensor picks up a noisy version of the transmitted codeword through one of two possible discrete memoryless channels. The sensor knows the codeword and wishes to discriminate between the two possible channels, i.e., to identify the channel that has generated the output given the input. We study the trade-off between communication and sensing in the asymptotic regime, captured in terms of the channel coding rate against the two types of discrimination error exponents. We characterize the optimal trade-off between the rate and the exponents for general discrete memoryless channels with an input cost constraint.

Dynamic ensemble-based machine learning models for predicting pest populations

Early prediction of pest occurrences can enhance crop production, reduce input costs, and minimize environmental damage. Advances in machine learning algorithms facilitate the development of efficient pest alert systems. Furthermore, ensemble algorithms help in the utilization of several models rather than being dependent on a single model. This study introduces a dynamic ensemble model with absolute log error (ALE) and logistic error functions using four machine learning models—artificial neural networks (ANNs), support vector regression (SVR), k-nearest neighbors (kNN), and random forests (RF). Various abiotic factors such as minimum and maximum temperature, rainfall, and morning and evening relative humidity were incorporated into the model as exogenous variables. The proposed algorithms were compared with fixed-weighted and unweighted ensemble methods, and candidate machine learning models, using the pest population data for yellow stem borer (YSB) from two regions of India. Error metrics include the root mean square log error (RMSLE), root relative square error (RRSE), and median absolute error (MDAE), along with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) algorithm. This study concluded that the proposed dynamic ensemble algorithm demonstrated better predictive accuracy in forecasting YSB infestation in rice crops.