Irrigation Application Research Articles

Application of Smart Techniques, Internet of Things and Data Mining for Resource Use Efficient and Sustainable Crop Production

Technological advancements have led to an increased use of the internet of things (IoT) to enhance the resource use efficiency, productivity, and cost-effectiveness of agricultural production systems, particularly under the current scenario of climate change. Increasing world population, climate variations, and propelling demand for the food are the hot discussions these days. Keeping in view the importance of the abovementioned issues, this manuscript summarizes the modern approaches of IoT and smart techniques to aid sustainable crop production. The study also demonstrates the benefits of using modern IoT approaches and smart techniques in the establishment of smart- and resource-use-efficient farming systems. Modern technology not only aids in sustaining productivity under limited resources, but also can help in observing climatic variations, monitoring soil nutrients, water dynamics, supporting data management in farming systems, and assisting in insect, pest, and disease management. Various type of sensors and computer tools can be utilized in data recording and management of cropping systems, which ensure an opportunity for timely decisions. Digital tools and camera-assisted cropping systems can aid producers to monitor their crops remotely. IoT and smart farming techniques can help to simulate and predict the yield production under forecasted climatic conditions, and thus assist in decision making for various crop management practices, including irrigation, fertilizer, insecticide, and weedicide applications. We found that various neural networks and simulation models could aid in yield prediction for better decision support with an average simulation accuracy of up to 92%. Different numerical models and smart irrigation tools help to save energy use by reducing it up to 8%, whereas advanced irrigation helped in reducing the cost by 25.34% as compared to soil-moisture-based irrigation system. Several leaf diseases on various crops can be managed by using image processing techniques using a genetic algorithm with 90% precision accuracy. Establishment of indoor vertical farming systems worldwide, especially in the countries either lacking the supply of sufficient water for the crops or suffering an intense urbanization, is ultimately helping to increase yield as well as enhancing the metabolite profile of the plants. Hence, employing the advanced tools, a modern and smart agricultural farming system could be used to stabilize and enhance crop productivity by improving resource use efficiency of applied resources i.e., irrigation water and fertilizers.

Exploring the Potential of Co-Application of Sewage Sludge, Chinese Medicinal Herbal Residues and Biochar in Minimizing Human Exposure to Antibiotics Contamination in Edible Crops

Agricultural practices such as wastewater irrigation and manure application may contaminate soils with antibiotics and, consequently, lead to human health risk. The co-application of three waste-derived materials, sewage sludge (SL), Chinese medicinal herbal residues (CMHR) and biochar (BC), as a soil amendment was proposed recently for minimizing the antibiotic amount in crop tissues. The fate of six antibiotics—amoxicillin, tetracycline, sulfamethazine, norfloxacin, erythromycin and chloramphenicol—were investigated in a greenhouse soil-plant system with a fruit crop species: tomato. The pots were mixed with 5%, 10% or 20% SL-BC and SL-CMHR-BC and irrigated with wastewater with 3 μg/L or 30 μg/L antibiotics. The pot containing 20% SL-CMHR-BC captured the lowest antibiotic concentration in soils and tomato tissues. Norfloxacin was the most abundant antibiotic in the fruits, followed by tetracycline. The pot containing 20% SL-CMHR-BC significantly lowered the bioconcentration factor of the fruit, while its effects on the translocation factor were more varied. Current and some previous data were used to assess the human health risk of consuming carrot, lettuce and tomato. The estimated daily intake suggested a negligible risk to human health in general compared with the acceptable daily intake, except for CAP. A concentration of 20% SL-CMHR-BC helps minimize the human exposure risk to antibiotics contamination in edible crops.

Econometric Modeling of Input-Driven Output Risk through a Versatile CES Production Function

The conventional functional form of the Constant-Elasticity-of-Substitution (CES) production function is a general production function nesting a number of other forms of production functions. Examples of such functions include Leontief, Cobb–Douglas, and linear production functions. Nevertheless, the conventional form of the CES production specification is still restrictive in multiple aspects. One example is the fact that the marginal effect of increasing input use always has to be to increase the variability of output quantity by the conventional construction of this function. This paper proposes a generalized variant of the CES production function that allows for various input effects on the probability distribution of output. Failure to allow for this possible input–output risk structure is indeed one of the limitations of the conventional form of the CES production function. This limitation may result in false inferences about input-driven output risk. In light of this, the present paper proposes a solution to this problem. First, it is shown that the familiar CES formulation suffers from very restrictive structural assumptions regarding risk considerations, and that such restrictions may lead to biased and inefficient estimates of production quantity and production risk. Following the general theme of Just and Pope’s approach, a CES-based production-function specification that overcomes this shortcoming of the original CES production function is introduced, and a three-stage Nonlinear Least-Squares (NLS) estimation procedure for the estimation of the proposed functional form is presented. To illustrate the proposed approaches in this paper, two empirical applications in irrigation and fertilizer response using the famous Hexem–Heady experimental dataset are provided. Finally, implications for modeling input-driven production risks are discussed.

Selection of Optimum Land Leveling Design Method for Surface Irrigation

Land leveling or land grading of surface irrigated fields improve irrigation water distribution and application efficiencies, conserve water and increases crop productivity. Land formation for irrigation face many constraints (ensuring proper slopes, prevention of flood, ensuring canal water command over the field, optimizing earthwork, minimizing truck travel distances, proper equipment utilization). Design engineers traditionally, perform site formation design manually by plane shape, least squire or linear programming methods. Such methods are with different characteristics. The main objective this study is to select and compare performance of these three design methods for proper land leveling design. Consequently, the basic theory of these alternative design methods are reviewed and their performance using data surveyed from five fields in Khartoum North-Sudan, each with different soil surface topographic configurations, is analyzed. The statistical analysis revealed that the linear programming method is the most appropriate design method. Employing the linear programming design method revealed that design slopes in row and cross row directions are within the acceptable range (0.1 to 0.5, the ratio of Cut/fill volumes is within the recommended range (1.1 to 1.3), uniformity of distribution of design elevations of grid points are acceptable and within the target limits (80%), while their deviation is at 80% of grid points around the mean before leveling.

Simulation Effect of Water and Nitrogen Transport under Wide Ridge and Furrow Irrigation in Winter Wheat Using HYDRUS-2D

An experiment was conducted to create a science-based program of irrigation and fertilizer application for two-year winter wheat under wide ridge and furrow irrigation in the Yellow River irrigation area. The study was performed in a test field located in Zhengzhou, Henan Province, China. A numerical model of soil water and nitrogen transport for winter wheat under wide ridge and furrow irrigation was created using HYDRUS-2D. The behavior of soil water and nitrogen was predicted for different irrigation water and nitrogen treatments and analyzed to identify pathways of nitrogen transport and transformation. The nitrogen balance was calculated for the different water and nitrogen treatments. The coefficients of determination for measured and predicted values of soil water content, nitrate nitrogen, and ammonium nitrogen in both horizontal and vertical directions were all >0.68; the mean absolute error was <0.06; and the root mean square error was <0.1. These values indicate the feasibility of using a numerical model of nitrogen transport for wide ridge and furrow irrigation. The correlation coefficient R2 between simulated values of nitrogen uptake and measured values of total crop nitrogen content was 0.88, the RMSE value was 10.58 kg/ha, and the MAE value was 5.9 kg/ha. Nitrogen loss was primarily caused by denitrification, and the quantity of gaseous nitrogen loss was 7.05–38.2% of the nitrogen form. The total quantity of ammonium nitrogen absorbed by winter wheat plant roots in each treatment was 7.6–15.1% of the total amount of nitrate nitrogen absorbed. The maximum nitrogen uptake was 155.53 kg/ha with a yield of 6888.67 kg/ha at a nitrogen application rate of 220 kg/ha and irrigating to 70% field capacity. The UE of the 220 kg/ha and irrigating to 70% field capacity treatment was relatively high, the PFP of the 120 kg/ha and irrigating to 80% field capacity treatment was relatively high, and the nitrogen use efficiency of the 320 kg/ha and irrigating to 60% field capacity treatment was the lowest overall. This study provides a basis for investigating soil water and nitrogen transport mechanisms of winter wheat under wide ridge and furrow irrigation in the Yellow River irrigation area.

Foliar application of potassium and restricted irrigation improved the growth and yield of wheat under rainfed condition of Bhal region

Foliar application of potassium increases the drought tolerance in the wheat crop with restricted irrigation, keeping in the view, a field experiment effect of foliar K application for improving wheat yield and water productivity under restricted irrigation condition was conducted at Agricultural Research station, Anand Agricultural University, Dhandhuka, Bhal region of Gujarat under conserved soil moisture condition with restricted irrigation in the Rabi season of 2021-22 with the objective to reduce moisture stress and to enhance the yield potential of wheat by using potash sprays. Inadequate moisture during the sensitive stages will cause substantial reduction in yield. The experiment was laid out in three replication with nine treatments in split plot design. They are (A). Irrigation levels, I1­: One irrigation at CRI stage, I2: Two Irrigation at CRI and flowering stage, I3: Three irrigation at CRI, late jointing and milking stage. (B). Foliar K application, F1: Control (Water spray), F2: 2% K foliar application at tillering (40-45) and jointing (60-65 DAS), and K3: 4% K foliar application at tillering (40-45) and jointing. The result indicated that due to irrigation management plant height at harvest (70.56 cm), length of ear (7.12), biological yield (7751 kg/ha) and grain yield (3367 kg/ha) was found significant with I3 treatment rest of parameters found non- significant with irrigation levels. Further data indicate from K foliar application, the plant height at harvest (71.51 cm), no of ear head sq. m. (295.44), length of ear (7.17), no, of grain per ear (32.68), test weight (44.03), biological yield (7112 kg/ha) and grain yield (3244 kg/ha) were recorded superior with K3 Treatment (4% K foliar application at tillering (40-45) and jointing) whereas, plant height, no of ear head (sq. m) no, of grain per ear, biological yield and grain yield found at par with F2 treatments Overall, it was observed that the foliar potassium fertilization and restricted irrigation increased the growth, yield attributes and grain yield.

IoT, Big Data Analytics and Deep Learning for Sustainable Precision Agriculture

Agriculture is undergoing a digital transformation because of population growth, climate change, and food security concerns. Agriculture is influenced by information technology in terms of cost reduction, efficiency, and sustainability. Precision agriculture employs IoT, deep learning, predictive analytics, and AI-based technologies to aid in the detection of plant diseases, pests, and poor plant nutrition in the field. The study's objectives are as follows: 1) evaluate the role of smart technologies and their impact on precision agriculture sustainability; 2) assess the typical application of IoT data analytic and deep learning in precision agriculture; and 3) investigate the barriers to the adoption of sustainable precision farming. IoT technologies collect data and relay it to data analytics and deep learning for in-depth analysis. According to the findings, data assists farmers in managing crop variety, phenotypes and selection, crop performance, soil quality, pH level, irrigation, and fertilizer application quantity. Technological issues, safety, privacy, cost, and legal issues also influence the adoption of these technologies. Keywords: IoT, Big Data Analytics, Deep Learning, Precision Agriculture, Sustainability DOI: 10.7176/JIEA/13-1-03 Publication date: February 28 th 2023

Root distribution, soil water depletion, and water productivity of sweet corn under deficit irrigation and biochar application

Root modifications can play a vital role in crop adjustments to soil water deficit. It is important to understand root growth and soil water depletion patterns to develop effective cropping systems, especially in semi-arid regions like Texas High Plains (THP). This study evaluated root growth, soil water depletion, and water productivity (WP) of sweet corn under three deficit irrigation treatments [100 %, 70 % and 40 % crop evapotranspiration (ETc)] and biochar application (hardwood and softwood). The experimental units were replicated 4 times in a split-plot design. The results revealed no interaction between irrigation and biochar treatments for almost all measured parameters. The 70 % ETc treatment increased the root length density (RLD) over 100 % ETc during 2019, while no differences were observed among irrigation treatments in 2020. Both deficit irrigations (70 % and 40 % ETc) increased soil water depletion compared to 100 % ETc, the highest being in 40 % ETc. The 70 % ETc maintained a similar yield and increased WP by 21 % compared to 100 % ETc across two years. However, 40 % ETc resulted in significant decline in yield and WP in 2020. The hardwood biochar increased RLD over no biochar treatment without affecting the soil water status and WP. Long-term studies are needed to investigate biochar effects beyond two years of application. In case of limited water availability, 70 % ETc can be recommended as an alternative to 100 % ETc in the THP of the US.

Influence of Foliar Application of Hydrogen Peroxide on Gas Exchange, Photochemical Efficiency, and Growth of Soursop under Salt Stress.

Hydrogen peroxide at low concentrations has been used as a salt stress attenuator because it induces a positive response in the antioxidant system of plants. This study aimed to assess the gas exchange, quantum yield, and development of soursop plants cv. Morada Nova grown with saline water irrigation and foliar hydrogen peroxide application. The experiment was carried out under greenhouse conditions using a randomized block design in a 4 × 4 factorial scheme corresponding to four levels of electrical conductivity of irrigation water, ECw (0.8, 1.6, 2.4, and 3.2 dS m-1), and four doses of hydrogen peroxide, H2O2 (0, 10, 20, and 30 μM), with three replicates. The use of irrigation water with electrical conductivity above 0.8 dS m-1 inhibited stomatal conductance, internal CO2 concentration, transpiration, maximum fluorescence, crown height, and vegetative vigor index of the Morada Nova cultivar of soursop. Compared to untreated plants, the hydrogen peroxide concentration of 30 μM resulted in greater stomatal conductance. Water salinity of 0.8 dS m-1 with hydrogen peroxide concentrations of 16 and 13 μM resulted in the highest variable fluorescence and quantum efficiency of photosystem II, respectively, of soursop plants cv. Morada Nova at 210 days after transplantation.

Precision Nitrogen Fertilizer and Irrigation Management for Apple Cultivation Based on a Multilevel Comprehensive Evaluation Method of Yield, Quality, and Profit Indices

Precise and efficient fertilizer and irrigation management is critical for apple production in the Loess Plateau, China. In this study, we established three levels of nitrogen application and irrigation in nine treatments in an apple orchard based on a completely randomized block design. Then, we analyzed different apple indicator responses to nitrogen and irrigation and their related interactions. More importantly, we used the multilevel comprehensive fuzzy evaluation value (MFCE) method to combine the weights of all indicators to obtain the comprehensive growth indicators for apples. Finally, we analyzed the effect of nitrogen and irrigation coupling on the comprehensive growth of apples and then determined the optimal interval for nitrogen application and irrigation. The results indicated that an increase in the amount of irrigation was beneficial for apple yield, but excessive nitrogen fertilizer application significantly reduced apple yield. The apple indicators were not sensitive to irrigation and nitrogen application and their related interactions; they were mainly controlled by the apple cultivar. On the other hand, an increase in the amount of nitrogen fertilizer or a reduction in the amount of irrigation could improve apple quality. The results of the comprehensive evaluation showed that the T5 treatment was most beneficial for the comprehensive growth of apples. To obtain the optimal interval for nitrogen application and irrigation more precisely, we used multiple linear regression based on the MFCE values of apples, nitrogen, and irrigation in R language. Nitrogen and irrigation showed a positive effect on the comprehensive growth of apples when the irrigation amount was low. However, nitrogen application and irrigation had a negative effect on the comprehensive growth of apples when the irrigation level was high. After optimization, the optimal nitrogen application and irrigation amounts were 170.5–189.5 kg·hm−2 and 38.4–42.7 mm, respectively. We recommend using this irrigation and fertilizer management scheme for apple orchards in China’s Loess Plateau.

The Effect of Soil Preparation Methods on Rain Water Infiltration as The Basis of Irrigation Application for Dry Land Rice

The purpose of this study was to determine the effect of land preparation methods on the soil infiltration which can be used as a basis for designing irrigation for dryland rice cultivation. The study was arranged in a completely randomized design (CRD) with three land preparation treatments, namely T0 (no tillage), T1 (hoeing), and T2 (hoeing plus loosening). Each treatment was carried out with three replication plots. Artificial rain was given with an average intensity of 4.61 mm/h for 120 min. Observations were made on the infiltration thickness and rainwater volume. Results showed that land preparation methods resulted in very significant differences in the cumulative infiltration depth and infiltration rate, where the T2 treatment caused the highest infiltration. During 120 minutes of rain, 331.83 liters of water volume was poured out and resulted in an average infiltration thickness of 7.3 cm for T0 (no tillage), 18.09 cm for T1 (hoeing), and 21,3 cm for T2 (hoeing plus loosening). The results also showed that cumulative infiltration (y) increased with rain water volume (x) that followd a logarithmic curve with an R2 value of more 94-98% for the three land preparation methods with order T2 > T1 > T0.Keywords: Rain, Tillage, Infiltration, Dry land, Rice

Assessment of Beauveria bassiana for the biological control of corn borer, Ostrinia furnacalis, in sweet maize by irrigation application

Kernels of sweet maize are directly consumed by humans. This high value crop is grown in arid and semi-arid regions of western Jilin Province, China where trickle irrigation is widely used and larvae of the corn borer, Ostrinia furnacalis Guenée (Lepidoptera: Crambidae), can cause significant kernel damage. Low humidity in arid regions is less conducive to the efficacy of the biological control agent, Beauveria bassiana (Balsamo) Vuillemin (Hypocreales: Cordycipitaceae). Simulated semi-arid conditions in greenhouse experiments were conducted comparing B. bassiana application on a granule carrier or in aqueous suspension to sweet maize. Applications of B. bassiana adhered to granules and in suspension reduced O. furnacalis leaf feeding damage, number of boreholes and tunneling length. Treatments with a granular carrier showed the most significant reductions in maize damage when applied once at whorl stage and in combination with a second application at the ear. The greatest reductions in boring and tunneling attributed to these treatments occurred at internodes around the ear. Although reduced damage was greatest following granular compared to aqueous applications, the latter also provided significant reductions in feeding damage compared to controls. This study demonstrates the utility of B. bassiana as a biological control agent for the reduction in damage caused by second-generation corn borer to sweet maize and existing irrigation equipment could be adapted for efficacious aqueous treatments by growers.

CART model to classify the drought status of diverse tomato genotypes by VPD, air temperature, and leaf–air temperature difference

Regular water management is crucial for the cultivation of tomato (Solanum lycopersicum L.). Inadequate irrigation leads to water stress and a reduction in tomato yield and quality. Therefore, it is important to develop an efficient classification method of the drought status of tomato for the timely application of irrigation. In this study, a simple classification and regression tree (CART) model that includes air temperature, vapor pressure deficit, and leaf–air temperature difference was established to classify the drought status of three tomato genotypes (i.e., cherry type ‘Tainan ASVEG No. 19’, large fruits breeding line ‘108290’, and wild accession ‘LA2093’). The results indicate that the proposed CART model exhibited a higher predictive sensitivity, specificity, geometric mean, and accuracy performance compared to the logistic model. In addition, the CART model was applicable not only to three tomato genotypes but across vegetative and reproductive stages. Furthermore, while the drought status was divided into low, medium, and high, the CART model provided a higher predictive performance than that of the logistic model. The results suggest that the drought status of tomato can be accurately classified by the proposed CART model. These results will provide a useful tool of the regular water management for tomato cultivation.

Yield, quality and physiological variation of strawberry in response to irrigation regimes and exogenous proline with a cost benefit analysis

Strawberry (Fragaria × ananassa Duch.) production is a major aspect of the agricultural economy in Turkey's Mediterranean region, offering high rates of employment and farm revenue. The effects of treatment of the exogenous amino acid on yield, quality, and physiological diversity for strawberry production was analyzed considering the economic aspects. To achieve this, 4 different irrigation regimes (IR (irrigation) 125, IR100, IR75, IR50) with proline treatment was tested. The total berry yield, photosynthesis and leaf water potential (LWP) significantly decreased as irrigation application rates declined. The IR125 treatment with proline (PIR125) produced the highest overall berry production. The use of proline significantly increased berry production by 23%. Exogenous proline generated 3.5 kg/1 m3 greater yields than control in terms of irrigation water use efficiency (IWUE). Under the IR50 conditions, the treatment of proline yielded a 32% higher than the control. Moreover, proline significantly increased fruit soluble solids content (SSC) by 6.4%. The production system achieves the highest cost-benefit ratio (CBR) under PIR125 whereas the lowest cost-benefit ratio under IR50. When each scenario was considered at individually, it was evident that the more water used the more efficient high tunnel strawberry production. The fact that proline generated an increase in CBR in all four irrigation regimes proves this amino acid's economic effectiveness. As a result, PIR125 is recommended for the highest efficiency and CBR in Mediterranean environment. However, it has been discovered that using proline to alleviate this problem in areas where water is limited could be quite helpful.

Strategies to cope with warming and reduced rainfall in green gram for northern transition zone of Karnataka, India

South West monsoon has become more erratic and unpredictable in the northern Transition Zone of Karnataka and in the coming decades this will continue further with warming. To cope with change in climate, agronomic adaptation strategies (optimum sowing window and application of irrigation at critical stages) are required to maintain higher yields of greengram. As a result, the DSSAT model was used to investigate the influence of climate change on greengram. The study included a combination of two temperature (+1 and +2 °C) and two reduced rainfall (˗10 and ˗20 %) scenarios in comparison with the baseline scenario (i.e., current climate). These scenarios were built for 32 years using historical weather data from 1985-2016. With regard to adaptation strategies, six dates of sowing; starting from June 1st week to July 2nd week at a weekly interval and four irrigation treatments each of 60 mm; one at pre-flowering stage, one at pod formation stage, one each at pre-flowering and pod formation stages, and no irrigation (rainfed) were included. Between sowing dates, the model's simulation of average grain yield across 32 years revealed that, 3rd (513 kg ha-1) and 4th (508 kg ha-1) week of June were found to be optimum under future climate. Irrigation at any of the critical stages increased the yield, but largest positive yield response was replicated with two irrigations: one at pre-flowering and the other during the pod formation stage (556 kg/ha). This study clearly showed that under future climates of 1 to 2 ℃ warming with reduced rainfall scenarios (-10 % & -20 %), sowing on 3rd and 4th week of June is best one, providing two irrigations (60 mm each) one at pre-flowering and the other at pod formation stage would more than compensate the loss in yield projected under changing climates in coming decades.

Comprehensive evaluation of the optimal rates of irrigation and potassium application for strawberry

Accurate and effective management of irrigation and fertilization is essential for efficient greenhouse strawberry production. Here, the effects of the combined application of water and potassium on strawberry growth were evaluated by experimenting with 12 treatments, including four transpiration (ETC)-based irrigation levels (W1: 100% ETC, W2: 85% ETC, W3: 70% ETC, and W4: 55% ETC) and three potassium levels according to the target yield (K1: 369.5 kg/hm2, K2: 307.9 kg/hm2, and K3: 246.3 kg/hm2). Various indexes of strawberry yield, fruit quality, water and fertilizer utilization efficiency, and soil nutrient residues were measured. Irrigation and potassium application had significant effects on strawberry production. Higher irrigation levels increased yield (Y), and moderate water and potassium application increased single fruit weight (SFW), water utilization efficiency (WUE), total soluble sugar (TSSC), and the sugar-acid ratio (SAR). While low-application of potassium increased the soluble protein content (SP), partial factor productivity of potassium (PFPK), and reduce nutrient residues in soil effectively. A comprehensive system for evaluating strawberry growth and its benefits to the soil environment was developed. The FAHP and CRITIC methods were used to calculate the subjective weight and objective weight of each index, respectively. The largest subjective weight was observed for Y (0.200), and the largest objective weight was observed for soil-available potassium (0.101). The final weight was determined using Game theory; Y had the highest weight (0.185), and free amino acids (FAA) had the lowest weight (0.047). Grey relational analysis (GRA) was used to evaluate the optimal irrigation and potassium scheme for accomplishing multiple objectives. The response of the comprehensive score of strawberries to irrigation and potassium exhibited a negative parabolic relationship, and the effect of irrigation was greater than the effect of potassium application. There was a significant interaction between irrigation and potassium application, and an irrigation amount of 2053-2525 m3/hm2 with a potassium application rate of 288.1-334.2 kg/hm2 was optimal for promoting strawberry yield, fruit quality, and efficiency and reducing soil nutrient residues. The results of this study provide new insights that could aid the development of sustainable approaches for enhancing agricultural production. Keywords: strawberry, irrigation, potassium, FAHP, CRITIC, nutrient residues DOI: 10.25165/j.ijabe.20231602.7591 Citation: Yang X Q, Du R C, Zhang M C, Feng H W, Wang Z Q, Zhang Z. Comprehensive evaluation of the optimal rates of irrigation and potassium application for strawberry. Int J Agric & Biol Eng, 2023; 16(2): 65-72.

Application of under-film drip irrigation for high yield yields in saline soils and global warming

The use of water- and resource-saving technologies for the cultivation of cotton on saline soils in the context of global warming is considered. In the studies, drip irrigation was used under the film, without a film through a row and furrow irrigation. In the control, 3000 m3/ha of water was used for leaching, 4200 m3/ha for vegetation, productivity - 40 c/ha, for vegetation for 1c crop - 105.0 m3/ha of water. With drip irrigation without a film and under a film, it was watered 21 times, the water consumption was respectively: 3770-3465-m3/ha, and with salt washing - 2400-2200m3/ha, the yield was 53-64 centners/ha. To obtain 1 centner of yield during the growing season, 71.13-54.40 m3/ha of water was consumed, compared to the control, less by 33.86-50.86 m3/ha. For growing 1s. harvest, spending 71.13-54.14 m3/ha of water, 13-24 centners/ha of yield increase was obtained, water savings for cotton is 1.48-1.94 times lower than the control. Scientifically substantiated, saving water, resources, eliminating excessive consumption of nutrients due to the accumulation of CO2 under the film, pH neutralization and soil desalination, successful completion of biochemical processes, improved absorption of phosphorus by the plant and the absence of fusarium, verticillium wilt.

АҚМОЛА ОБЛЫСЫНДА КӨГАЛДАНДЫРУҒА ЕНГІЗУ ҮШІН ПЕРСПЕКТИВАЛЫБҰТАЛЫ ӨСІМДІКТЕРДІҢ ҚҰРҒАҚШЫЛЫҚҚА ТӨЗІМДІЛІГІН ЗЕРТТЕУ

The research purpose was to study and recommend the most decorative types of shrubs with a number of drought resistance-related agronomic characters for introduction into gardening in Akmola region. The experiments were conducted under both open-field (nursery) and closed-field (greenhouse) conditions. We explored the application of drip irrigation, different propagation methods (field seeding or seedling planting), use of hydrogels and various fillers such as perlite, vermiculite, and gravel for soil structuring and moisture retention. The selection of the optimal approach was based on morphological indicators of seedlings, including height, annual growth rate, leaf flooding indicators, size, area measurements, and the timeframe for obtaining standard planting material. The leaf water retention capacity was assessed from May to September. We studied and compared the growth and development of selected shrub plants using conventional annual irrigation and horticultural fleece (agrotextile), as well as automated drip irrigation with the application of moisture-absorbing agents to the sowing and planting wells. To evaluate critical growth periods and irrigation needs, we analyzed leaf moisture and water retention capacity monthly under various watering conditions. High water retention capacity indicates the plants resistance to water deficiency, and the data studied varied in scores. The research identified critical irrigation periods in the arid conditions of the Akmola region. Morphological indicators of Tamarix ramosissima and Salix purpurea seedlings notably enhanced with drip irrigation and in nursery setting.

The importance of metrology and measurements in the application of drip irrigation in horticulture

The paper describes advantages of drip irrigation in horticulture. The importance of metrology and measurements in the drip irrigation system was explained. The effect of "gross errors" in the measurement results on the system was explained, and the method of further increasing the accuracy by processing the results obtained from measuring instruments and not taking into account "gross errors" was justified by concrete examples and diagrams. The disadvantage of using the conventional method has been pointed out. Using the proposed method, the maintenance of soil moisture in a stable state during the processing of the results obtained from the sensors was considered. This method allows saving a certain amount of water and more accurately measure soil moisture.

Design of Automatic Irrigation Robot Based on Tracking and Visual Recognition

The purpose of this project is to design an automatic watering robot with tracing module and visual module, which is equipped with watering, spraying and supporting facilities. This product aims to solve the problems of difficult management of potted plants in flower lovers ' families or greenhouses, and high mortality caused by neglect of management of flowers due to human factors. The project takes STM32 single-chip microcomputer as the core, with tracing module and visual recognition module. The execution module adopts belt transmission, combined with Internet of things, path automatic planning, magnetic coupling resonance wireless charging and other technologies to realize the application of robot automatic irrigation and spraying by autonomous planning of road trajectory. The project has good promotion value in the flower market and smart home.