Precision Agriculture Research Articles

Role of Information Technology in Agriculture : A Review

Information Technology (IT) is the application of computers and telecommunications equipment to store, retrieve, transmit and manipulate data, often in the context of a business, education or other enterprise. This paper reviewed the India’s IT Industry and in addition studied the Impact of IT on the Indian Agriculture. To improve the quality of agricultural products and production using information technology that requires efficiency and information in all sectors of agriculture. Information technology support new methods and ideas for precision and healthy agriculture used computers in farm, climate or weather forecasting, use of method and materials and kind of crops. In this paper I tried to find how information technology is useful for making choices to setting goals, improve planning and produce better agriculture products and study the key elements and basic issues of information technology in agriculture.

Correction to: On-farm experimentation of precision agriculture for differential seed and fertilizer management in semi-arid rainfed zones

Correction to: On-farm experimentation of precision agriculture for differential seed and fertilizer management in semi-arid rainfed zones

Smart farming based on IoT to predict conditions using machine learning

<span>Smart farming is a type of technology that utilizes the internet of things (IoT) to provide information on agricultural and environmental conditions as well as perform automation. Some of these ecological conditions can be used and analyzed in machine learning (ML) data management. This study focuses on utilizing ML algorithms to find the best prediction; typically used methods include linear regression, decision tree (DT), random forest (RF), and extreme gradient boosting (XGBoost). In the application of smart farming, research on IoT and artificial intelligence (AI) is still uncommon since most IoT cannot make predictions like AI. Because basically, some IoT can't make predictions as AI does. In this Study, predictions were made by looking at the regression results in the form of root mean square error (RMSE) and absolute error. The results show a strong and weak correlation between features (positive or negative). The best prediction results are obtained by XGBoost when predicting temperature (RMSE 6.656 and absolute error 3.948) and (soil moisture 17.151 and absolute error 11.269). However, using different parameters (RMSE RF and absolute error DT) on RF and DT resulted in good and distinct results. Linear regression, on the other hand, produced unsatisfactory and poor result.</span>

МАТЕРИАЛЬНО-ТЕХНИЧЕСКОЕ ОБЕСПЕЧЕНИЕ СЕЛЬСКОГО ХОЗЯЙСТВА: СОСТОЯНИЕ, ПРОБЛЕМЫ, НАПРАВЛЕНИЯ СОВЕРШЕНСТВОВАНИЯ

One of the determining conditions for competitive domestic agricultural production in foreign markets is the technical and technological modernization of the industry. However, despite the significance of the problem, over the past two decades, a stable trend of reduction in the number of employees in agricultural organizations in Russia has developed for all types of agricultural machinery. The highest rates of reduction in agricultural machinery were observed until 2010, and in subsequent periods the downward trend has significantly decreased. At the same time, it is not entirely correct to assess the current situation unambiguously, since the reduction in the fleet of machinery and equipment in agricultural organizations is due to certain objective circumstances and conditions: the area of cultivated land and cultivation of specific crops has decreased; the number of animals has decreased; the technical means used have become more energy-intensive and productive, which is especially important in the context of a shortage of personnel in rural areas. In 2018-2022 the production of domestic agricultural machinery in value terms increased by almost 2.5 times, while in physical terms the changes are insignificant. At the same time, domestic mechanical engineering practically does not produce machinery and equipment for pig farming, poultry farming, milk processing, potato harvesters, beet harvesting equipment, equipment for gardening, vegetable growing. As a result of the outstripping rate of disposal of agricultural machinery and equipment over the rate of their production and replenishment, the energy capacity of the industry is declining. The sanctions imposed on the Russian economy have led to increased risks of non-receipt of critical components and spare parts; disruption of stable logistics and distribution chains that have functioned for a long time, their rise in price; revision of contract terms, failure to meet delivery deadlines. Sanctions against the use of foreign high technologies used in precision farming, genetics, selection, enterprise management, etc. have a negative impact on the development of the agro-industrial complex.

Bactrocera oleae Control and Smart Farming Technologies for Olive Orchards in the Context of Optimal Olive Oil Quality: A Review

Bactrocera oleae Control and Smart Farming Technologies for Olive Orchards in the Context of Optimal Olive Oil Quality: A Review

Corrigendum: Will the development of smart agriculture improve food safety in international markets? A theoretical approach

Corrigendum: Will the development of smart agriculture improve food safety in international markets? A theoretical approach

A Study on the Allelopathic Effects of Wild Barley (Hordeum spontaneum) Residue Incorporated with Soil on Growth of Some Plant species

This study examines the allelopathic effects of wild barley (Hordeum spontaneum) on the growth and yield of bread wheat (Triticum aestivum), barley (Hordeum vulgare), and wild barley (Hordeum spontaneum). The experiment was conducted in a greenhouse at Shamamar-Hawler/ Kurdistan Region of Iraq using a complete randomized factorial design (CRD) within 3 replications. The roots, shoots, and seeds of wild barley were dried, powdered, and added to the soil at different concentrations (0%, 10%, 20%, 30%, and 40%) in 500 g pots. Each pot was planted with 5 seeds, which were later reduced to 3 seedlings. Growth parameters such as shoot and root lengths, dry weights, number of tillers, weight of spikes, seeds number per plant, and biological yield was measured. The results indicated significant effects of wild barley residues on the studied crops. Wheat showed the highest roots, shoots and total lengths were (29.56 cm, 17.05 cm and 46.58 cm, respectively) and the highest shoots and roots dry weights were (0.24 g and 0.30 g). Barley showed the highest number of stems (1.96) but the lowest shoots and dry weights of roots were (0.11 g and 0.23 g). Wild barley had the highest biological weight and harvest index (HI). Among the plant parts, seed extracts significantly enhanced growth parameters, while roots and shoots extract had the greatest inhibitory effects as wild barley residue concentrations increased. Nevertheless, the HI showed a decline as the concentrations increased, suggesting a detrimental effect on growth efficiency. The study shows the potential of wild barley as a bio-herbicide, emphasizing its allelopathic effects. This suggests that agricultural practices should be carefully considered to maximize the efficiency of crops. Incorporating these results into precision agriculture can greatly improve crop management and increase yield.

In-Depth Development of a Versatile Rumen Bolus Sensor for Dairy Cattle

Precision agriculture and the increasing automation efforts in animal husbandry requires continuous and complex monitoring of the animals. Rumen bolus sensors, which are cutting-edge pieces of technology and a rapidly developing research field, present an exceptional opportunity for monitoring the health status, physiological parameters, and estrus of the animals. The objective of this paper is to provide a comprehensive overview of the development process of a new sensor development. We address the issues of conceptual design, an overview of applicable sensor modalities, mechanical design, power supply design, applicable hardware solutions, applicable communication solutions and finally the sensor detection algorithms proved in field tests. In conclusion, we present a summary of the current opportunities in the field and provide an analysis of the foreseeable trends.

Assessing the impact of financial resources on Sorghum yield in Al-Qadarif State, Sudan

The sorghum agricultural sector in Al-Qadarif State, Sudan, plays a pivotal role in ensuring regional food security. However, its productivity is hindered by significant constraints. Substantial improvements in sorghum yield are impeded by the intricate complexities that characterize this sector's financial resources, and agricultural practices. This study in Al-Qadarif State, Sudan, explores the relationship between financial resources and sorghum agrarian productivity. Data were collected from 200 sorghum farmers using standardized questionnaires during the 2022 season, and regression analysis was employed to investigate the association between financial factors and sorghum productivity. The findings indicate that financial accessibility considerations significantly influence sorghum productivity. This emphasizes the importance of improved financial resources for farmers to adopt innovative farming technologies and practices, leading to higher sorghum productivity levels. The study recommends the integration of digital financial services and precision agriculture technologies as a creative solution to enhance financial accessibility and sorghum productivity. By leveraging mobile money platforms and digital credit services, farmers can conveniently access financial resources, enabling them to invest in modern agricultural inputs and technologies. Additionally, the adoption of precision agriculture techniques, such as soil moisture sensors, drone-based crop monitoring, and variable rate application of inputs, can optimize resource utilization, increase yield, and reduce production costs. The combination of these innovative approaches has the potential to bridge the financial and knowledge gaps, promoting the widespread adoption of sustainable agricultural practices. This synergistic approach could significantly improve sorghum productivity, enhance farmer livelihoods, and contribute to regional food security.

A Review of UAV Path-Planning Algorithms and Obstacle Avoidance Methods for Remote Sensing Applications

The rapid development of uncrewed aerial vehicles (UAVs) has significantly increased their usefulness in various fields, particularly in remote sensing. This paper provides a comprehensive review of UAV path planning, obstacle detection, and avoidance methods, with a focus on its utilisation in both single and multiple UAV platforms. The paper classifies the algorithms into two main categories: (1) global and local path-planning approaches in single UAVs; and (2) multi-UAV path-planning methods. It further analyses obstacle detection and avoidance methods, as well as their capacity to adapt, optimise, and compute efficiently in different operational environments. The outcomes highlight the advantages and limitations of each method, offering valuable information regarding their suitability for remote sensing applications, such as precision agriculture, urban mapping, and ecological surveillance. Additionally, this review also identifies limitations in the existing research, specifically in multi-UAV frameworks, and provides recommendations for future developments to improve the adaptability and effectiveness of UAV operations in dynamic and complex situations.

Innovations in Biodegradable Batteries: A Sustainable Future

The increasing demand for batteries in several industries such as medical and electric car (EV) Industry has led to significant environmental challenges due to the production and disposal of traditional batteries, which are nonbiodegradable and pose risks to ecosystems. This report investigates the potential of biodegradable batteries as a sustainable alternative to traditional batteries, aiming to minimize environmental impact. This study analyzing and comparing the fiber batteries, zinc-molybdenum batteries, plant-based batteries (Flower battery), crab shell battery as well as algal biopolymers battery. It also highlights the key materials, methods for manufacture, and performance characteristics (biodegradability, energy capacity, degradation time) of each type of biodegradable batteries. The findings suggest that biodegradable batteries offer promising solutions for specific applications, such as in biomedical devices, wearable electronics, and precision agriculture, where their biocompatibility and environmental safety are crucial. Future development should focus on enhancing energy density, optimizing degradation timelines, and reducing costs to make these batteries more competitive with traditional options.

Context-specific regulatory variants in precision medicine and agriculture.

Context-specific regulatory variants in precision medicine and agriculture.

Maize biomass yield variations due to diverse nitrogen applications using Aquacrop

AbstractIn the quest to increase crop yields and production intensity to meet the demands of a growing global population, the responsible use of nitrogen (N) applications is paramount. Excessive application of these fertilizers results in economic losses, environmental pollution and reduced N‐use efficiency. To address this challenge, precision agriculture techniques offer promising solutions. This study explored the relationships among applied N, maize crop parameters and the nitrogen nutrition index (NNI) to optimize N application usage and crop performance. The AquaCrop model was used to simulate water productivity and plant parameters accurately. The research establishes equations between the NNI and maize parameters, enabling the use of AquaCrop to simulate crop responses to varying N levels. The results demonstrate that AquaCrop effectively simulates more than 95% of the biomass changes. The findings suggest that applying N based on presented equations optimized the use of N applications, thereby mitigating economic losses and environmental impacts.

Unlocking Innovation in Crop Resilience and Productivity: Breakthroughs in Biotechnology and Sustainable Farming

Recent advancements in agricultural biotechnology and sustainable practices are revolutionizing crop production and resilience, addressing global food security challenges. This review highlights cutting-edge innovations in plant sciences, including genetic engineering, genome editing technologies, and biotechnological interventions that enhance crop resistance to biotic and abiotic stresses. It discusses the integration of precision agriculture and digital farming tools that optimize resource use and boost productivity, providing data-driven insights for better crop management. Additionally, sustainable agricultural practices such as agroecology, organic farming, and integrated pest management are examined for their potential to reduce environmental impact while maintaining high yield. The review investigates the key practices like conservation tillage, crop rotation, and biological pest control, emphasizing their roles in enhancing soil health, biodiversity, and agricultural resilience. Significant contributions of biotechnological interventions, including genetic engineering and genome editing, are explored for developing stress-resistant and high-yield crop varieties. Moreover, the integration of precision agriculture and digital farming technologies is discussed for their potential to optimize resource utilization and improve crop management through advanced data analytics.

Development and Evaluation of a Variable-Rate Fertilizer Distribution System for Coffee Plants

Currently, Brazilian coffee farming seeks the rational use of resources through sustainable practices. As a result, the development of machinery with more efficient input application systems and the adoption of precision agriculture techniques have been yielding excellent results. This study was divided into two stages, with the first involving the adaptation of a solid fertilizer application machine with fixed doses, allowing dose variation using an electronic controller. The second stage consisted of conducting trials and their applications under operational conditions. The results confirmed that the developed system remained stable in terms of variable-rate fertilizer distribution for coffee cultivation. The machine’s lateral fertilizer distribution range met the demands of coffee farming satisfactorily. In field conditions, the developed system exhibited an average error of −2.9%, compared to the programmed doses, validating the accuracy of the machine and its suitability for use in coffee plantations.

Mathematical Model for Optimum Temperature and Humidity Determination of Mashed Mushroom in Greenhouses by using Smart Farm Technology and Innovation

Background: At the present time, various technologies have been used in the development of modern agriculture. The technology used to help in the development of agricultural farms is called a smart farm. Mashed Mushroom is a food due to their usefulness and high nutritional and good income, as this result, the researcher was interested in the use of technology and innovation of smart farms in the mashed mushroom cultivation house and find a mathematical model of the optimum temperature and humidity for growing mashed mushrooms. Furthermore, find a mathematical model of the yield amount of mashed mushrooms against temperature and humidity. Methods: There are 5 methods in this research, to be composed of studying the problem, planning the operation process, using technology and innovation in smart farms, collecting data and finally finding a mathematical model of the optimum temperature and humidity for growing mashed mushrooms. In addition, a mathematical model of the yield of mashed mushrooms was obtained. Result: The results showed that the mathematical model of the optimum temperature for mashed mushroom was T= 0.3267t3-2.83t2+7.1433t+20, the most appropriate temperature was 24.95±5.557°C at the average andthe mathematical model of the optimum humidity for mashed mushroom was H= -0.8417t3+4.82-0t2.1883t+59.65, the most appropriate humidity was 74.58±15.451% at the average. In addition, the mathematical model of product yield of mashed mushrooms was = -1.479+0.055T+0.028H when temperature T and humidity H were determined.

Internet of Things : A Way of Transforming Conventional Agriculture

The Internet of Things (IoT) is the network of various devices seamlessly exchanging data. IoT has initiated the 4th agricultural revolution known as Agriculture 4.0/Digital Agriculture (DA)/Precision Agriculture (PA)/Smart Agriculture (SA). All farming activities can be monitored and managed remotely. With IoT, agriculture is becoming more energy-efficient, precise and effective. IoT is emerging as a potential solution to current world problems. In this review paper, the application of IoT in various agricultural activities is discussed. The paper highlights how IoT is transforming the execution of various agricultural activities.

Revolutionizing Precision Agriculture: Advanced Seed Prescription Generation and Cloud Infrastructure

This article explores the revolutionary impact of advanced seed prescription generation engines and cloud infrastructure on precision agriculture. It delves into the technical intricacies of enhancing seed prescription systems through cutting-edge data pipelines and scalable cloud platforms. The article discusses how these sophisticated systems analyze various factors such as soil composition, topography, historical yield data, and climate patterns to determine optimal seeding rates and patterns with unprecedented accuracy. It highlights the challenges faced in implementing these systems, including scalability, data processing, reliability, and monitoring, and presents innovative cloud-based solutions to address these issues. The benefits of these advancements, including improved efficiency, enhanced accuracy, scalability, reliability, and cost-effectiveness, are examined, along with their potential to reshape the global food production landscape and promote sustainable farming practices.

Color Dominance-Based Polynomial Optimization Segmentation for Identifying Tomato Leaves and Fruits

Optimization processes or methods play an essential role in the continuous improvement of various human activities, particularly in agriculture, given its vital role in food production. In precision agriculture, which utilizes technology to optimize food production, a primary goal is to minimize the consumption of resources like water, fertilizers, and the detection of pests and diseases. In the fertilization process, it is essential to identify any deficiencies or excesses of chemical elements. Nutrient deficiencies, which are essential for plant development, are typically detected in the leaves of crops. This paper proposes a methodology for optimizing the color threshold dominance factors employed in the segmentation process for tomato crop leaves and fruits. The optimization is performed using an interpolation method to find the values that maximize the segmentation of leaves and fruits used by the color dominance segmentation method. A comparison of the interpolation method results with those obtained using a greedy algorithm, which iteratively finds the optimal segmentation values, shows nearly identical outcomes. Similarly, a UNetmodel is used for semantic segmentation, the results of which are inferior to those obtained by the proposed interpolation optimization method. The most significant contribution of the interpolation method is that it requires only a single iteration to generate the initial data, in contrast to the iterative search required by the greedy algorithm and the lengthy training process and video card dependency of the UNet model. This results in an 80% reduction in computation time.

Factors predicting innovation-decisions: The effects of performance expectancy, social influence, and facilitating conditions on U.S. Extension’s promotion of precision agriculture technologies

Factors predicting innovation-decisions: The effects of performance expectancy, social influence, and facilitating conditions on U.S. Extension’s promotion of precision agriculture technologies