Irrigation Process Research Articles

A review of smart agricultural transition to achieving Sustainable Development Goals (SDGs): smart irrigation system

Smart agriculture is important in achieving the SDGs, especially food and water. The transition to using smart irrigation systems is highly recommended, considering that this transition can optimize agricultural production. A smart irrigation system is a unified irrigation process integrated with automated technology and IoT (Internet of Things) that drives a new direction of smart agricultural technology development. This study highlights the smart irrigation system as the smart agricultural transition concerning SDGs. The main method was a qualitative review based on a literature study with the criteria for exclusion consisting of indexed journals, review papers or research articles, and publications published within the last decade. The review shows the irrigation control and monitoring used in recent years. Other than that, as a brief report on the current status of IoT-related smart irrigation development, several types of effective smart irrigation that have been done before are compared. Discussed the perspective of SDGs, the goal indicators achieved through smart irrigation showed good results; 11 indicators were achieved. Thus, the challenges and prospects of IoT-related development for smart irrigation are discussed. This study will help researchers and farmers understand clever irrigation more effectively and precisely.

Improving Irrigation Performance by Using Adaptive Border Irrigation System

Shortages of water resources and labor make it urgent to improve irrigation efficiency and automation. To respond to this need, this study demonstrates the development of an adaptive border irrigation system. The inflow is adjusted based on the functional relationship between the advance time deviation and the optimal adjustment inflow rate, thereby avoiding the real-time calculation of infiltration parameters required by traditional real-time control irrigation systems. During the irrigation process, the inflow rate is automatically adjusted based only on the advance time deviation of the observation points. The proposed system greatly simplifies the calculation and reduces the requirements for field computing equipment compared with traditional real-time control irrigation systems. Field validation experiments show that the proposed system provides high-quality irrigation by improving the application efficiency, distribution uniformity, and comprehensive irrigation performance by 11.3%, 10.7%, and 11.0%, respectively. A sensitivity analysis indicates that the proposed system maintains a satisfactory irrigation performance for all scenarios of variations in natural parameters, flow rates, and border length. Due to its satisfactory irrigation performance, robustness, facile operation, and economical merit compared with traditional real-time control irrigation systems, the proposed system has the potential to be widely applied.

Adaptive membership enhanced fuzzy classifier with modified LSTM for automated rainfall prediction model

Nowadays, various research works is explored to predict the rainfall in the different areas. The emerging research is assisted to make effective decision capacities that are involved in the field of agriculture broadly related to the irrigation process and cultivation. Here, the atmospheric and climatic factors such as wind speed, temperature, and humidity get varies from one place to another place. Thus, it makes the system more complex, and it attains higher error rate during computation for providing accurate rainfall prediction results. In this paper, the major intention is to design an advanced Artificial Intelligent (AI) model for rainfall prediction for different areas. The rainfall data from diverse areas are collected initially, and data cleaning is performed. Further, data normalization is done for ensuring the proper organization and related data in each record. Once these pre-processing phases are completed, rainfall recognition is the main step, in which Adaptive Membership Enhanced Fuzzy Classifier (AME-FC) is adopted for classifying the data into low, medium, and high rainfall. Then for each degree of low, medium, and high rainfall, the prediction process is performed individually by training the developed Tri-Long Short-Term Memory (TRI-LSTM). Additionally, the output achieved from the trained TRI-LSTM rainfall prediction in cm for each low, medium, and high rainfall. The meta-heuristic technique with Hybrid Moth-Flame Colliding Bodies Optimization (HMFCBO) enhances the recognition and prediction phases. The experimental outcome shows that the different rainfall prediction databases prove the developed model overwhelms the conventional models, and thus it would be helpful to predict more accurate rainfall.

Experimental study on clogging of three different types of emitters with similar properties

AbstractThe drip irrigation process has been designed to reduce water losses, and to combine irrigation, with the supply of fertilizers. However, in drip irrigation systems, the clogging of emitters is a major problem that significantly reduces the performance of drip irrigation systems. The water used in these systems is generally loaded with suspended matter, which might cause clogging of the emitters. This work was carried out in order to evaluate the clogging rate in three different types of emitters with roughly similar flow rates, tested in an experimental drip irrigation system, using water pumped from the Sebou River. Thus, a compensating‐pressure emitter named E1 and two non‐compensating‐pressure emitters named E2 and E3 were tested. Each dripper was subjected to 112 irrigations, which lasted 397 h and were spread over a period of 2 months. To evaluate the hydraulic performance of the emitters, the following three coefficients were used to measure the effect of clogging: (i) the variation of the flow ratio (Dra), which reflects the degree of clogging; (ii) the emission uniformity coefficient (EU); and (iii) the Christiansen uniformity coefficient (CU). No emitters became completely clogged during the experiment. However, as the clogging rate increased, the average flow rates measured in some emitters at the end of the test had decreased by 89% compared to the initial flow rates. During the experiment, flow fluctuations were observed during the evolution of the clogging, which could come from a partial recovery of flow.

Farklı İğne Tasarımlarının Diş Kanalı İrrigasyonu Üzerindeki Etkilerinin Hesaplamalı Akışkanlar Dinamiği ile İncelenmesi

This study aims to investigate the effects of irrigation needles geometries on the flow inside the root canal and compare their irrigation performances based on Computational Fluid Dynamics (CFD) analyzes. CFD simulations of three commonly used close-ended irrigation needles were performed for various inlet Reynolds numbers and working lengths. Their irrigation performances were evaluated based on apical pressure and wall shear stress. The flow was assumed to be incompressible, turbulent and steady at all inlet Reynolds numbers. The closed-ended needles showed similar limited irrigant penetration toward the apex. Among all configurations, the Model C outperforms others as it provides the highest wall shear stress around the needle tip and the lowest apical pressures in the apical foramen, which reduces the risk of apical extrusion. The needle tip designs influence important parameters for the effectiveness and safety of the irrigation process.

A Low Cost Smart Irrigation Planning Based on Machine Learning and Internet of Things

In an agriculture system major issues of irrigation systems for plants water supply is a critical factor. A significant amount of freshwater is required for this task but after the utilization of water in the irrigation process it is being polluted. In addition, the excessive use of water during the irrigation process can negatively affect crop production. Therefore, we need to provide a balanced amount of water for effective crop production and conservation of water. In this paper, we proposed low-cost irrigation planning with two key aims: first is to reduce the installation and maintenance costs of data collection in innovative irrigation systems and second is to control the valve for water supply automatically. In this context, we first provide a review of recent irrigation systems based on the Internet of Things (IoT) and Machine Learning (ML). Next, we introduce a working plan to collect crop water requirements using a soil moisture sensor. Then, an algorithm is proposed to decide the water supply for water treatment. Finally, the experiments are conducted on the samples collected from the farmland of wheat crops. Additionally, two different scenarios are considered to collect the water requirement samples. Based on the experimental and theoretical analysis of water requirements the proposed irrigation system can reduce the water demand by up to 25% as compared to traditional ways of irrigation. Moreover, in comparison of popular valve automation system the proposed multiple valve based system reduces the amount of water wastage up-to 22%. Therefore by utilizing the advance computational techniques (IoT and ML), we can reduce the cost of irrigation system and planning.

Sustainable Smart Agriculture Farming for Cotton Crop: A Fuzzy Logic Rule Based Methodology

Sustainable agriculture is a pivotal driver of a nation’s economic growth, especially considering the challenge of providing food for the world’s expanding population. Agriculture remains a cornerstone of many nations’ economies, so the need for intelligent, sustainable farming practices has never been greater. Agricultural industries worldwide require sophisticated systems that empower farmers to manage their crops efficiently, reduce water wastage, and optimize yield quality. Yearly, substantial crop losses occur due to unpredictable environmental changes, with improper irrigation practices being a leading cause. In this paper, we introduce an innovative irrigation time control system for smart farming. This system leverages fuzzy logic to regulate the timing of irrigation in cotton crop fields, effectively curbing water wastage while ensuring that crops receive neither too little nor too much water. Additionally, our system addresses a common agricultural challenge: whitefly infestations. Users can adjust climatic parameters, such as temperature and humidity, through our system, which minimizes both whitefly populations and water consumption. We have developed a portable measurement technology that includes air humidity sensors, temperature sensors, and rain sensors. These sensors interface with an Arduino platform, allowing real-time climate data collection. This collected climate data is then sent to the fuzzy logic control system, which dynamically adjusts irrigation timing in response to changing environmental conditions. Our system incorporates an algorithm that generates highly effective (IF-THEN) fuzzy logic rules, significantly improving irrigation efficiency by reducing overall irrigation duration. By automating the irrigation process and precisely delivering the right amount of water, our system eliminates the need for human intervention, rendering the agricultural system more dependable in achieving successful crop yields. Water supply commences when the environmental conditions reach specific thresholds and halts when the requisite climate conditions are met, maintaining an optimal environment for crop growth.

Experimental performance of soil monitoring system using IoT technique for automatic drip irrigation

SummaryThis paper proposes an IoT‐enabled soil monitoring system using wireless sensor network for automatic irrigation in agricultural applications, especially for lemongrass plants, where an automated control system is required for irrigation applications. This can solve the problem of the water crisis, which is faced by the farmers during the cultivation of the crop in the field. This controls the water supply in the irrigation process using an IoT communication system. A system architecture for soil monitoring and controlling irrigation using IoT technique is designed where the different sensors and actuators like humidity, soil moisture, temperature, pump, and so forth are connected with a node microcontrol unit and message queuing telemetry transport (MQTT) protocol for enhancing communication capabilities. This wireless sensor network gives feedback to the system. This provides automation by the on/off pump system during drip irrigation. The sensor data are displayed on a PC or mobile phone through wireless communication and an IoT cloud platform. An experimental testing setup is developed and the experimental performance of a soil monitoring system using IoT technique for automatic drip irrigation has been carried out and soil moisture data are also stored in a cloud server for analytics. The performance shows that the MQTT protocol sends data within 48 s to the IoT cloud so that the data can be acquired in a faster manner. This shows that this kind of soil monitoring system is suitable for automatic drip irrigation, which enhances the farming process and overcomes the water crises in the agricultural system by reducing the wastage of water.

Forecasting actual evapotranspiration without climate data based on stacked integration of DNN and meta-heuristic models across China from 1958 to 2021

As a non-linear phenomenon that varies along with agro-climatic conditions alongside many other factors, Evapotranspiration (ET) process represents a complexity when be assessed especially if there is a data scarcity in the weather data. However, even under such a data scarcity, the accurate estimates of ET values remain necessary for precise irrigation. So, the present study aims to: i) evaluate the performance of six hybrid machine learning (ML) models in estimating the monthly actual ET values under different agro-climatic conditions in China for seven provinces (Shandong, Jiangsu, Zhejiang, Fujian, Jiangxi, Hubei, and Henan), and ii) select the best-developed model based on statistical metrics and reduce errors between predicted and actual ET (AET) values. AET datasets were divided into 78% for model training (from 1958 to 2007) and the remaining was used for testing (from 2008 to 2021). Deep Neural Networks (DNN) was used as a standalone model at first then the stacking method was applied to integrate DNN with data-driven models such as Additive regression (AR), Random Forest (RF), Random Subspace (RSS), M5 Burned Tree (M5P) and Reduced Error Purning Tree (REPTree). Partial Auto-Correlation Function (PACF) was used for selection of the best lags inputs to the developed models. Results have revealed that DNN-based hybrid models held better performance than non-hybrid DNN models, such that the DNN-RF algorithm outperformed others during both training and testing stages, followed by DNN-RSS. This model has acquired the best values of every statistical measure [MAE (10.8, 12.9), RMSE (15.6, 17.4), RAE (31.9%, 41.4%), and RRSE (39.3%, 47.2%)] for training and testing, respectively. In contrast, the DNN model held the worst performance [MAE (14.9, 13.7), RMSE (20.1, 18.2), RAE (43.9%, 43.7%), and RRSE (50.6%, 49.3%)], for training and testing, respectively. Results from the study presented have revealed the capability of DNN-based hybrid models for long-term predictions of the AET values. Moreover, the DNN-RF model has been suggested as the most suitable model to improve future investigation for AET predictions, which could benefit the enhancement of the irrigation process and increase crop yield.

IOT-Based Smart Irrigation System using DTMF and 8051 MCU

Abstract: In almost every facet of agriculture and gardening, irrigation is the cornerstone activity, with the regular watering of plants and crops paramount to their growth and well-being. However, this essential task often proves burdensome for individuals preoccupied with daily commitments. For farmers, the significance of water supply is further emphasized, as rainwater assumes a critical role in sustaining their crops. While relying on the unpredictability of monsoon rains, canals, and groundwater resources, farmers face the challenges of ensuring a consistent and appropriate water supply, as each crop type necessitates distinct watering regimens. Any insufficiency in providing water to crops can lead to devastating consequences, resulting in the potential destruction of crops and plants. Addressing these challenges and aiming to revolutionize irrigation practices, this paper proposes an IOT-based Smart Irrigation System using DTMF (Dual Tone Multi-Frequency) and 8051 MCU (Microcontroller Unit) as an innovative and transformative solution. This cutting-edge system combines the power of DTMF technology with the versatility of the 8051 microcontrollers, enabling remote control and monitoring of the irrigation process. By leveraging the interactive capabilities of mobile or landline phones, the system allows users, including farmers and gardeners, to conveniently manage irrigation operations from a distance, reducing the need for constant physical presence. This intelligent irrigation system exhibits applicability in automating the irrigation processes of various settings, including gardens, nurseries, and greenhouses. By carefully regulating the water supply to plants based on specific predefined conditions, the system ensures the provision of an optimal and essential amount of water. As a result, the system achieves energy conservation while effectively mitigating any potential water scarcity issues.

Analysis of Paranet Techniques in Fulfilling National Food Diversification as a Solution to the Highland Water Crisis

<p>The need for food in the industrial world tends to increase every time, this is due to Indonesia's population growth rate continues to increase. This prospect is said to be positive, because it also absorbs the level of sales of local agricultural commodities, so that the level of welfare also increases. UKM XYZ is a social enterprise that was formed together, with the aim of collecting various harvests carried out by farmers, which are then processed into processed food products, so as to increase the cost of added value income. The technique in this activity is carried out manually, with the form of nets used that must cover the plantation area as a whole, without gaps, so that the irrigation process using dew can be carried out perfectly. The results of the water quantity value from the paranet net technique are greater than the quantity value. rain of hope. This makes it an alternative technique that can be adopted by farmers in dealing with climate change or prolonged climate crises such as drought. The results of the production value of the production quantity of the harvest value deposited to SMEs XYZ in the three month period (January – March 2023), show a better increase than the initial data period (October – December 2022). The high water quantity value from the paranet netting technique must be adjusted to the conditions of the slopes or the steepness of agricultural land, so that it does not pose a risk of landslides or excessive abrasion, which is detrimental to farmers</p>

IOT-Based Cultural Movement And Monitoring Systems With Renewable Energy Utilities

The procedure of watering for and keeping track of the temperature and humidity levels in the room has a significant impact on the growth and productivity of oyster mushroom plants. It is often believed to be less effective and efficient because people in the Banyuwangi district perform the irrigation process conventionally with human aid. In order to construct digital businesses, artificial intelligence, cognitive technology, and (IoT) are being developed. People's daily lives are becoming more advanced and connected because to this transformation. This will encourage the creation of fresh innovations. Given this context, the idea to undertake research on the method of automatically and continuously monitoring watering (spraying) mushroom production using the Internet of Things (IoT) developed. In order to improve the effectiveness and productivity of mushroom cultivation, this instrument is designed with a temperature sensor (LM35) to monitor the humidity conditions of oyster mushroom plants. It is also fitted with a solar renewable energy system. In order to improve the effectiveness and productivity of mushroom cultivation, this instrument is designed with a temperature sensor (LM35) to monitor the humidity conditions of oyster mushroom plants. It is also fitted with a solar renewable energy system. The five steps of this study's execution were: a needs analysis; tool design; tool prototype; prototype testing; and conclusion. According to test results, the IoT-based control system for watering mushroom cultivation has an average error of 0.1% when measuring temperature and an average error of 2.66% when measuring humidity. This is almost perfect in terms of sensor readings, indicating that it can be used properly. While the success rate for the spray control system using the IoT system after five trials was 100%, the voltage, current, and power for solar panels were 17.60 V, 4.10 A, and 55.7 Watt at 14.00 during the day.

Effect on Vegetative Growth and Development of Strawberry (Fragaria ananassa) in Potting Mixture System under Shade Net Conditions cv. Winter Dawn

In Prayagraj agro climatic conditions strawberry is produced with high-technology, but there is little research on the productivity of strawberry in Potting media mixture under shade net conditions. The present study was conducted to compare single potting media for the strawberry. The conventional method was used for the comparison study. In this method, uniform runners of the strawberry cultivar Winter Dawn were grown in pots with growing medium consisting of goat manure, vermiculite, and peat moss in various ratios on a volume-to-volume basis. Additionally, Ponic green's 3-part Nute hydroponic nutrient set was applied to the plants via foliar spray at fortnightly intervals. In order to meet the nutritional requirements of each individual plant and ensure that the uppermost layer of the pots remained adequately moist, the irrigation process was carefully monitored. Based on both years2021- 22research trail findings of this study. It was determined to have the greatest growth traits for every growth, flowering and fruit weight criteria.

Irrigants and irrigation activation systems in Endodontics.

Root canal infections are typically polymicrobial and involve strong bacterial interactions. The goal of endodontic treatment is to remove infected content from the root canal system to allow the healing of a pre-existing periapical lesion or to prevent infection of the periradicular tissues. Instrumentation alone is not capable of touching all of the root canal walls. Therefore, the irrigation process is an essential step in the endodontic treatment. However, due to the complex anatomy of the root canal system, this cleaning is very challenging. Although syringe and needle irrigation associated with the use of chemical substances is still the most used method, it does not guarantee optimal cleaning of the root canals. As a result, not only alternative irrigating substances but also numerous activation systems - which are technologies that aim to optimize the action of irrigating substances, both chemically and physically - have been developed. This work aimed to review the characteristics of both classic and current alternatives of irrigating substances and irrigation activation systems.

Technologies to reduce water waste during land leaching and cultivation of industrial crops

More than half of Uzbekistan’s irrigated land is saline to some degree. The drying up of the Aral Sea has intensified this process. Chronic salt storms in the northern part of the country have for many years sprayed large quantities of salt onto agricultural land, leading to increased salinisation. These processes cause the water required to flush saline soils year after year. The problem is exacerbated by water shortages worldwide, including in Central Asia. This requires leaching of saline soils and a multiplication of the water used in crop cultivation. Therefore, alternative use of water resources in our country is one of the most important issues for agriculture. Introduction of salt leaching and cultivation in farms on the basis of outdated technologies and low efficiency of new technologies (bio-solvent washing, etc.) in production of new salt leaching and cultivation remain a negative obstacle for economic development of farms and the country as a whole. The analysis shows that in our country billions of cubic meters of water are used for flushing of saline soils and cultivation of agricultural crops, but only 60% of this water reaches the fields where crops are grown, while the rest of it disappears into the irrigation systems and irrigation processes (canals, ditches and branch lines). When providing water resources for soil salinisation and cultivation by means of trapezoidal canals, part of the water flowing through them dissolves and filters the mineral and organic fertilizers in the soil due to air pressure and gravity, as a result up to 30% of water is lost (wasted). In this paper the water resources for soil washing and crop cultivation are replaced by a parabolic excavator with a trapezoidal boom, designed to save up to 30% of water resources.

RA Water Resources Management In The Irrigation Process

Հոդվածում ներկայացված է ՀՀ ջրային ռեսուրսների օպտիմալ կառավարման կարևորությունը ոռոգման իրականացման գործում, որով էլ պայմանավորված է աշխատանքի արդիականությունը։ Առաջնային ուշադրություն է դարձվել Հայաստանի ամբողջ ջրային պաշարների վերլուծմանը, Սևանա լճի ջրային պաշարների խնայողաբար օգտագործմանը, ոռոգման համար ջրային ռեսուրսների արդյունավետ կառավարմանը։ Հոդվածում նպատակ է դրվել մշակել Հայաստանում ոռոգման ջրի օգտագործման, պահպանման բարելավմանն ուղղված առաջարկություններ։ Նպատակին հասնելու համար խնդիր է դրվել վերլուծել ՀՀ ջրային ռեսուրսների օգտագործման վիճակը, ուսումնասիրել Հայաստանում ոռոգման համակարգի առանձնահատկությունները, բացահայտել ոռոգման ջրի օգտագործման և պահպանման բարելավման ուղիները։ В статье представлена важность оптимального управления водными ресурсами РА при осуществлении орошения, чем и обусловлена актуальность статьи. Основное внимание было уделено анализу всех водных ресурсов Армении, экономному использованию водных ресурсов озера Севан, эффективному управлению водными ресурсами для орошения. Целью статьи является разработка рекомендаций по совершенствованию управления водными ресурсами на основе изучения использования и охраны водных ресурсов в Армении, в частности поливной воды. Для достижения цели были поставлены задачи: The article presents the importance of the optimal management of the water resources of the RA in the implementation of irrigation, which determines the relevance of the article. The main attention was paid to the analysis of all the water resources of Armenia, the economical use of the water resources of Lake Sevan, the effective management of water resources for irrigation. The purpose to develop recommendations for improvement of the usage and conservation of irrigation water in Armenia. To achieve this goal, the problems were set to analyze the state of the usage of water resources in RA, to study the features of the irrigation system in Armenia, to determine ways to improve the usage and conservation of irrigation water. Analyzes were carried out on the basis of statistical and analytical methods of water management in Armenia, as a result of which it became clear that there is a sufficient amount of water resources in RA, and the main problem is related to the effective conservation and usage of these resources.

Effects of applications of synthetic polymer and humic acid on resistance to dispersion and mechanical forces

In this study, the effects of the addition of polyvinyl alcohol (PVA), polyacrylamide (PAM), and humic acid (HA) to soils in sandy loam, loam, and clay texture classes on their resistance to dispersion and mechanical forces were examined. The study was performed under greenhouse conditions using surface soil samples and 1.5 kg pots. Furthermore, the study was planned as an incubation experiment and the application of PVA, PAM, and HA at 500, 100, and 500 ppm doses for each soil texture class, respectively. During the incubation times (1 (0), 2 (15), 3 (30) 30, and 4 (45) days), the irrigation process was repeated as half of the available moisture in the soil was depleted. Ultimately, the applications of PVA, PAM, and HA on soils in sandy loam, loam, and clay textures increased the liquid limit/ pF'2 moisture ratio (LL/pF'2) values in them by 6.30%, 5.99%, and 7.30%, respectively, (reducing the tendency to dispersion) compared to the control. Furthermore, the applications increased the plastic limit/pF’2 moisture ratio (PL/pF’2) values (resistance to mechanical forces) by 22.31%, 16.50%, and 9.27%, respectively. Incubation time 1 was more effective in reducing dispersion and increasing resistance to mechanical forces, and the effects decreased over time. PVA was the most effective conditioner for all three soil groups.

IoT-Enabled Smart Drip Irrigation System Using ESP32

Agriculture, or farming, is the science of cultivating the soil, growing crops, and raising livestock. Ever since the days of the first plow from sticks over ten thousand years ago, agriculture has always depended on technology. As technology and science improved, so did the scale at which farming was possible. With the popularity and growth of the Internet of Things (IoT) in recent years, there are even more avenues for technology to make agriculture more efficient and help farmers in every nation. In this paper, we designed a smart IoT-enabled drip irrigation system using ESP32 to automate the irrigation process, and we tested it. The ESP32 communicates with the Blynk app, which is used to collect irrigation data, manually water the plants, switch off the automatic watering function, and plot graphs based on the readings of the sensors. We connected the ESP32 to a soil moisture sensor, temperature sensor, air humidity sensor, and water flow sensor. The ESP32 regularly checks if the soil is dry. If the soil is dry and the soil temperature is appropriate for watering, the ESP32 opens a solenoid valve and waters the plants. The amount of time to run the drip irrigation system is determined based on the flow rate measured by the water flow sensor. The ESP32 reads the humidity sensor values and notifies the user when the humidity is too high or too low. The user can switch off the automatic watering system according to the humidity value. In both primary and field tests, we found that the system ran well and was able to grow green onions.

Sistem Pengawasan Automatik Tanaman Hiasan

In the current era of technological advancement, Internet of Things (IoT) has become a technology that is frequently adopted in all industries. The IoT concept that allows multiple devices to interact with each other over an increasingly popular internet connection is used in everyday applications automatically as well as for monitoring and security purposes. Ornamental plants, vegetables and herbs that can be grown in or around the house that are often left for working residents can apply this IoT system. Residents not only get the view of green and fresh air, but they can also produce fast and fresh food from their own pots with the help of automatic monitoring and planting systems. An efficient irrigation process can be achieved with an IoT approach as it ensures that the plant or plants get the right amount of water to grow well. Therefore, an automated planting system based on the Internet of Things is proposed to solve problems related to the need to irrigate plants when necessary and monitor plant conditions remotely.

Influence of Irrigation, Variety and Collection Time on Mineral Contents of Olive Leaves

The objective of this study was to evaluate the effect of factors such as irrigation, variety and collection time on mineral contents of olive leaves. The highest Ca (31115.73 mg/kg), K (8398.34 mg/kg) and S (1679.05 mg/kg) contents were determined in leaves of Gemlik variety collected in irrigated orchard. Olive leaves of Ayvalık variety grown in irrigated orchard contained the maximum levels of Mg (3394.94 mg/kg) and P (949.13 mg/kg). The P, K and Mg amounts of olive leaves, in general, showed an increase with irrigation treatment. Generally, a regular increase or decrease did not observe in levels of macro elements of olive leaves based on collection time. Concerning the micro element contents of leaves, the highest Na contents were found in Ayvalık (241.11 mg/kg) and Yağlık (237.65 mg/kg) varieties. An increase was obtained in Fe contents of Yağlık olive leaves with irrigation during collection period. The concentrations of both macro and micro elements showed differences depending on the collection time, irrigation process and variety of olive leaves.