Irrigation Strategies Research Articles

Water Use Efficiency and Winter Wheat Grain Yield of Different Cultivars Under Different Irrigation Strategies in a Semi-arid Region

Water Use Efficiency and Winter Wheat Grain Yield of Different Cultivars Under Different Irrigation Strategies in a Semi-arid Region

Water strategy improves the inflorescence primordia formation of 'Arra 15' grapevine in the Brazilian semiarid region

Failure in irrigation management of grapevines grown in the Brazilian semiarid region can affect bud fertility. Adequate irrigation, considering both the development of bunches in the current cycle and the formation of fertile buds for subsequent cycles, can bring significant advances to viticulture. Therefore, the objective of this research was to investigate the effect of different irrigation levels during flowering on the formation of buds and potential bunches of 'Arra 15' grapevine and its relationship with metabolic processes. A field experiment was carried out in a commercial vineyard in Petrolina, Pernambuco, Brazil, during the 2021 and 2022 seasons. The experiment was designed in randomized blocks with four replications and five irrigation levels (70; 85; 100; 115 and 130% of crop evapotranspiration – ETc) during three production cycles. The variables fertile bud, vegetative bud, dead bud, potential fertility of the basal, median, and apical regions of the branches, number of potential bunches, reducing sugar, total soluble sugar, net photosynthesis, stomatal conductance, transpiration, and relative chlorophyll index were evaluated. The 115% ETc irrigation level improved the number of fertile buds and number of potential bunches. Irrigation level above 115% ETc increased gas exchange and relative chlorophyll index, while 70% ETc increased leaf sugar content. The most appropriate irrigation strategy is the application of 115% ETc during the flowering stage, for the increase of fertile buds and potential bunches of the next cycle, without influencing the vine metabolism. Total soluble sugars are a promising indicator of water deficit during flowering and as an indicator of vegetative bud formation for the next cycle.

Chitosan combined with humic applications during sensitive growth stages to drought improves nutritional status and water relations of sweet potato

The current decline in freshwater resources presents a significant global challenge to crop production, a situation expected to intensify with ongoing climate change. This underscores the need for extensive research to enhance crop yields under drought conditions, a priority for scientists given its vital role in global food security. Our study explores the effects of using humic and chitosan treatments to alleviate drought stress during critical growth phases and their impact on crop yield and water efficiency. We employed four different irrigation strategies: full irrigation, 70% irrigation at the early vine development stage, 70% irrigation during the storage root bulking stage, and 85% irrigation across both stages, complemented by full irrigation in other periods. The plants received either humic treatments through foliar spray or soil application, or chitosan foliar applications, with tap water serving as a control. Our findings highlight that the early vine development stage is particularly vulnerable to drought, with a 42.0% decrease in yield observed under such conditions. In normal growth scenarios, foliar application of humic substances significantly improved growth parameters, resulting in a substantial increase in yield and water efficiency by 66.9% and 68.4%, respectively, compared to the control treatment under full irrigation. For sweet potatoes irrigated with 70% water at the storage root bulking stage, ground application of humic substances outperformed both foliar applications of chitosan and humic in terms of yield results. The highest tuber yield and water efficiency were attained by combining chitosan and humic ground applications, regardless of whether 70% irrigation was used at the storage root bulking stage or 85% irrigation during both the early vine development and storage root bulking stages.

Empowering coffee farming using counterfactual recommendation based RNN driven IoT integrated soil quality command system

Soil health is essential for whirling stale soil into rich coffee-growing land. By keeping healthy soil, coffee producers may improve plant growth, leaf health, buds, cherry and bean quality, and yield. Traditional soil monitoring is tedious, time-consuming, and error-prone. Enhancing the monitoring system using AI-based IoT technologies for quick and precise changes. Integrated soil fertility control system to optimize soil health, maximize efficiency, promote sustainability, and prevent crop threads using real-time data analysis to turn infertile land into fertile land. The RNN-IoT approach uses IoT sensors in the coffee plantation to collect real-time data on soil temperature, moisture, pH, nutrient levels, weather, CO2 levels, EC, TDS, and historical data. Data transmission using a wireless cloud platform. Testing and training using recurrent neural networks (RNNs) and gated recurrent units gathered data for predicting soil conditions and crop hazards. Researchers are carrying out detailed qualitative testing to evaluate the proposed RNN-IoT approach. Utilize counterfactual recommendations for developing alternative strategies for irrigation, fertilization, fertilizer regulation, and crop management, taking into account the existing soil conditions, forecasts, and historical data. The accuracy is evaluated by comparing it to other deep learning algorithms. The utilization of the RNN-IoT methodology for soil health monitoring enhances both efficiency and accuracy in comparison to conventional soil monitoring methods. Minimized the ecological impact by minimizing water and fertilizer utilization. Enhanced farmer decision-making and data accessibility with a mobile application that provides real-time data, AI-generated suggestions, and the ability to detect possible crop hazards for swift action.

Assessing the impact of irrigation and nitrogen management on potato performance under varying climate in the state of Florida, USA

Optimizing irrigation and nitrogen (N) fertilizer management in irrigated potato crops grown on sandy soils in subtropical regions such as in northeastern Florida, USA is essential to sustain a high yield and to minimize leaching. N applications in this region typically occur at approximately 25–30 days prior to planting (Npre), at emergence (Neme), and at tuber initiation (Nti). However, recent studies suggest that applying N near planting (Npl) enhances fertilizer N use efficiency (FNUE). We combined experimentation with modeling to assess irrigation and N management options for potato in northeastern Florida. We first aimed to evaluate the DSSAT/CSM-SUBSTOR-Potato model using two-year irrigated field experiments conducted on sandy soils with variable N rates and application timings. CSM-SUBSTOR-Potato accurately simulated aboveground plus tuber dry weight [Relative root mean squared error (RRMSE) = 26.4%, Willmott’s index (d) = 0.98] and N accumulation (RRMSE = 28.6%, d = 0.97). Soil moisture and mineral N were captured well overall, but they were often underestimated due to a water table influence that is currently not considered in DSSAT. Subsequently, CSM-SUBSTOR-Potato was applied to simulate tuber yield, N leaching, and FNUE under scenarios of irrigation scheduling and N-fertilizer application (rate/timing) strategies, focusing on Npre versus Npl aiming to improve resource use efficiency. The simulations indicated that a target of 60% and 70% of the available soil water can be safely used as an irrigation strategy to achieve a high yield, while reducing irrigation water applied and N leached to the environment. Overall Npl increased crop N uptake by 10%, tuber yield by 7%, reduced N leached by 13%, and consequently increasing FNUE by 9%, compared to Npre across the irrigation treatments. Thus, Npl should be preferred in sandy soils and climate-risky subtropical environments, along with Neme and Nti as key timings to synchronize N supply with potato growth.

Simulation Model Construction of Plant Height and Leaf Area Index Based on the Overground Weight of Greenhouse Tomato: Device Development and Application

Plant height and leaf area index (LAI) are crucial growth indicators that reflect the growth status of tomatoes in greenhouses, enabling accurate determinations to effectively estimate crop transpiration and formulate irrigation strategies for reducing agricultural water waste. There is a need for the increased application of related models to simulate tomato growth indices in the traditional greenhouse production in China. This study proposes a nondestructive, real-time monitoring and simulation device for measuring tomato plant height and leaf area index. The weight of aboveground tomatoes was obtained by suspending tomato plants on dynamometers, while the total weight of stem and leaf organs was determined using a distribution coefficient simulation model. The R2 value between the measurements from the electronic scale and those from the aboveground fresh weight device for tomatoes was 0.937, with an RMSE value of 0.05 kg. The monitoring device did not affect the average tomato growth during operation. The device will not affect the growth of tomatoes during monitoring. A multiple linear regression was used to compare the measured and simulated values of the plant height and leaf area index of various types of greenhouse tomatoes cultivated in different greenhouse types. The average R2 value for simulating plant height was 0.817 with an RMSE of 10.81 cm. The average R2 value for the leaf area index was 0.854, with an RMSE of 0.55 m2·m−2. The simulated values for plant height and leaf area index closely matched the measured values, indicating that the model has high accuracy and applicability in traditional Chinese greenhouses (solar greenhouses and insulated plastic greenhouses). However, further optimization is required for commercially produced, continuous plastic greenhouses equipped with greenhouse environmental control equipment.

Effect of Irrigation and Nitrogen Management on Potato Growth, Yield, and Water and Nitrogen Use Efficiencies

Irrigation and nitrogen management are crucial for sustainable potato (Solanum tuberosum L.) production. A field experiment was conducted during the 2022 and 2023 growing seasons at Farmington, New Mexico, to evaluate the performance of two chip potato varieties (Lamoka and Waneta) under three irrigation regimes (full irrigation (FI), 20% deficit irrigation (DI) and 40% DI) and seven nitrogen fertilizer rates (0, 60, 115, 170, 220, 280, and 340 kg N/ha). The treatment combinations of irrigation regimes, nitrogen rates, and varieties were arranged in a split–split plot design with three replications as main plot, sub-plot, and sub-sub plot, respectively. The two-year results showed that irrigation regimes had the most significant effect on plant growth, physiology, and tuber yield of the potato varieties. For both Lamoka and Waneta, the plant height and canopy cover were lower under 40% DI than under 20% DI and FI treatments. The SPAD meter values were higher under 40% DI, followed by 20% DI and FI treatments, whereas the stomatal conductance was higher under FI, followed by 20% DI and 40% DI during both growing seasons. Regardless of nitrogen rates and variety, a 20% water-saving irrigation strategy reduced the total tuber yield by 4.5% and 22.1% in the 2022 and 2023 growing seasons, respectively, while the 40% water-saving irrigation strategy reduced total tuber yield by 36.8% and 58.2% in the 2022 and 2023 growing seasons, respectively, as compared to full irrigation. Shifting from full irrigation to 20% DI could save 711.2 to 1036.3 m3/ha of irrigation water. For Lamoka, the highest total tuber yield was obtained with 60 kg N/ha under 20% DI and 220 kg N/ha under FI in 2022 and 2023, respectively. For Waneta, the highest total tuber yield was obtained with 115 kg N/ha under 20% DI and 170 kg N/ha under FI in 2022 and 2023, respectively. Maximum water use efficiency (WUE) was obtained at 60 kg N/ha with 20% DI for both Lamoka and Waneta in 2022, while maximum WUE was obtained at 220 kg N/ha under FI for Lamoka and at 170 kg N/ha for Waneta in the 2023 season. The maximum nitrogen use efficiency (NUE) was achieved with 60 kg N/ha under 20% DI for both varieties during both growing seasons. Thus, for sustainable irrigation and nitrogen management, the application of a 20% deficit irrigation strategy with a lower nitrogen rate (60 to 170 kg N/ha) could be the best option to improve WUE and NUE with minimal tuber yield reduction. Our study suggested that 40% deficit irrigation would not be beneficial as compared to both full irrigation and 20% water-saving irrigation.

Enhancing productivity while reducing water footprint and groundwater depletion: Optimizing irrigation strategies in a wheat-soybean planting system

ContextTraditional agricultural practices in the Huang-Huai-Hai Plain have led to a decrease in groundwater level, coupled with frequent extreme rainfall in recent years, has seriously threatened grain production and sustainability. ObjectiveThe objective of this study is to evaluate water footprint, groundwater table, and system productivity through a three-year field experiment that focuses on transitioning from the conventional winter wheat-maize (WM) to winter wheat-soybean (WS) system, while integrating suitable irrigation strategies. MethodsMicro-sprinkling irrigation strategies were applied during the winter wheat season, when the soil water content (SWC) of the 40 cm soil layer dropped to 40% of its field capacity (FC). Specifically, W4 treatment irrigated until SWC reached 60% FC at a depth of 40 cm, while the W6 treatment irrigated to SWC reaching 80% FC at a 60 cm depth. In contrast, a rain-fed (W0) treatment served as the control. Field water consumption was simulated using the Water Heat Carbon Nitrogen Simulator (WHCNS) model. Results and conclusionsThe results revealed that the WS system exhibited less variability in evapotranspiration (ETc) compared to WM system, with reductions ranging from 23.6% to 29.1%. Furthermore, the WS system contributed substantially to elevating the groundwater table by 58.4–146.4% while maintaining a higher and more stable annual wheat equivalent yield (WEY) compared to the WM system. The W4 treatment saved 97.9–98.2 mm of irrigation water compared to the W6 treatment, improved water productivity by 10.7–32.1%, and reduced the water footprint by 14.3–25.1%. SignificanceTransitioning from the traditional WM cropping system to the WS system, and adapting an appropriate irrigation regime (W4) can counterbalance extreme weather impacts on crop yields. This study provides valuable insights into sustainable farming practices, and it may provide a practical framework for striking a balance between groundwater conservation and food security.

Impact of soil compaction and irrigation practices on salt dynamics in the presence of a saline shallow groundwater: An experimental and modelling study

AbstractSoil salt accumulation is a widespread problem leading to diminished crop yield and threatening food security in many regions of the world. The soil salinization problem is particularly acute in areas that lack adequate soil water drainage and where a saline shallow water table (WT) is present. In this study, we present laboratory‐scale column experiments, extending over a period of more than 400 days that focus on the processes contributing to soil salinization. We specifically examine the combined impact of soil compaction, surface water application model and water quality on salt dynamics in the presence of a saline shallow WT. The soil columns (60 cm height and 16 cm diameter) were packed with an agricultural soil with bulk densities of 1.15 and 1.34 g/cm−3 for uncompacted and compacted layers, respectively, and automatically monitored for water content, salinity and pressure. Two surface water compositions are considered: fresh (deionized, DI) and saline water (~3.4 mS/cm). To assess the sensitivity of compaction on salt dynamics, the experiments were numerically modelled with the HYDRUS‐1D computer program. The results show that the saline WT led to rapid salinization of the soil column due to capillarity, with the salinity reaching levels much higher than that at the WT. However, compaction layer provided a barrier that limited the downwards moisture percolation and solute transport. Furthermore, the numerical simulations showed that the application of freshwater can temporarily reverse the accumulation of salts in agricultural soils. This irrigation strategy can help, in the short‐term, alleviate soil salinization problem. The soil hydraulic properties, WT depth, water quality, evaporation demand and the availability of freshwater all play a role in the practicability of such short‐term solutions. The presence of a saline shallow WT would, however, rapidly reverse these temporary measures, leading to the recurrence of topsoil salinization.

Mitigation of N2O emissions in water-saving paddy fields: Evaluating organic fertilizer substitution and microbial mechanisms

Water-saving irrigation strategies can successfully alleviate methane emissions from rice fields, but significantly stimulate nitrous oxide (N2O) emissions because of variations in soil oxygen level and redox potential. However, the relationship linking soil N2O emissions to nitrogen functional genes during various fertilization treatments in water-saving paddy fields has rarely been investigated. Furthermore, the mitigation potential of organic fertilizer substitution on N2O emissions and the microbial mechanism in rice fields must be further elucidated. Our study examined how soil N2O emissions were affected by related functional microorganisms (ammonia-oxidizing archaea (AOA), ammonia-oxidizing bacteria (AOB), nirS, nirK and nosZ) to various fertilization treatments in a rice field in southeast China over two years. In this study, three fertilization regimes were applied to rice cultivation: a no nitrogen (N) (Control), an inorganic N (Ni), and an inorganic N with partial N substitution with organic manure (Ni+No). Over two rice-growing seasons, cumulative N2O emissions averaged 0.47, 4.62 and 4.08 kg ha−1 for the Control, Ni and Ni+No treatments, respectively. In comparison to the Ni treatment, the Ni+No fertilization regime considerably reduced soil N2O emissions by 11.6% while maintaining rice yield, with a lower N2O emission factor (EF) from fertilizer N of 0.95%. Nitrogen fertilization considerably raised the AOB, nirS, nirK and nosZ gene abundances, in comparison to the Control treatment. Moreover, the substitution of organic manure for inorganic N fertilizer significantly decreased AOB and nirS gene abundances and increased nosZ gene abundance. The AOB responded to N fertilization more sensitively than the AOA. Total N2O emissions significantly correlated positively with AOB and nirS gene abundances while having a negative correlation with nosZ gene abundance and the nosZ/nirS ratio across N-fertilized plots. In summary, we conclude that organic manure substitution for inorganic N fertilizer decreased soil N2O emissions primarily by changing the soil NO3−-N, pH and DOC levels, thus inhibiting the activities of ammonia oxidation in nitrification and nitrite reduction in denitrification, and strengthening N2O reduction in denitrification from water-saving rice paddies.

The effects of high temperature and low humidity on crop water stress index of seed pumpkin plants (Cucurbita pepo L.) in semi-arid climate conditions

This study aimed to evaluate the effects of high temperature and low humidity on the crop water stress index (CWSI) of seed pumpkin plants grown under semi-arid climate conditions to determine the optimum irrigation time. This research unveils the critical impact of high temperature and low humidity on seed pumpkin growth, emphasizing the vital role of the CWSI in optimizing irrigation strategies and seed yield. Moreover, the relationship between CWSI, physiological parameters, and seed yield of the pumpkin was investigated. The mean CWSI values in the I70 (0.40) and I35 (0.56) treatments were 42% and 100% higher, respectively than those in the full irrigation (I100) treatment (0.28). While the I70 treatment showed manageable water stress with minimal impact, the I35 treatment experienced severe stress, significantly reducing crop growth and yield. The mean seed yield (SY) in the I70 treatment increased to 1245.2 kg ha–1 compared to I35 (903.3 kg ha–1) but remained lower than I100 (1339.3 kg ha–1). The CWSI had negative correlations (p ≤ 0.01) with seed yield, chlorophyll content, and leaf area index, while it had positive correlations with water use efficiency and irrigation water use efficiency (p ≤ 0.01). This study showed that pumpkins could be grown successfully at 30% water deficit conditions, and a water deficit higher than 30% may cause a significant seed yield loss in semi-arid climate conditions. In addition, the results highlight the importance of optimal irrigation and CWSI monitoring for informed irrigation decisions and sustainable agricultural practices. Therefore, moderate water deficit (I70) can be adopted in pumpkin cultivation as an alternative to full irrigation.

Impact of Deficit Irrigation Strategies Using Saline Water on Soil and Peach Tree Yield in an Arid Region of Tunisia

Sustainable fruit orchard development in arid areas is severely affected by the scarcity of fresh water. To mitigate the lack of fresh water, the use of low-quality water for irrigation is becoming a common practice in several margin areas. However, salinity is considered one of the most important environmental constraints limiting the successful crop production. Therefore, the effects of deficit irrigation strategies using saline water (3.1 dS m−1) on soil water content, soil salinity, and yield of commercial peach orchard were investigated. Three irrigation treatments were considered: a Control, full irrigated (FI); and partial root-zone drying (PRD50); and deficit irrigation (DI) strategies irrigated at 50% ETc. These levels of water supply allowed for contrasting watering conditions with clear distinction between irrigation treatments. The differential pattern in soil moisture was accompanied by that of soil salinity with an increase in all FI treatments (16–25%). The results indicated that soil salinity increased with increasing water supply and evaporative demand during the growing season from January (3.2 dS m−1) to August (6.6 dS m−1). Deficit irrigation strategies (DI, PRD50) induced more soil salinity along the row emitter compared to the Control due to insufficient leaching fractions. By the end of the growing season, the soil salinity under long-term saline drip irrigation remained stable (5.3–5.7 dS m−1). An efficient leaching action seemed to be guaranteed by rainfall and facilitated by sandy soil texture, as well as the high evaporative demand and the important salt quantity supplied, which maintain the deficit irrigation strategies as valuable tools for water saving and improving water productivity. The significant water saving of 50% of water requirements induced a fruit yield loss of 20%. For this reason, DI and PRD50 could be reasonable irrigation management tools for saving water and controlling soil salinity in arid areas and on deep sandy soil.

Evaluating the Effect of Deficit Irrigation on Yield and Water Use Efficiency of Drip Irrigation Cotton under Film in Xinjiang Based on Meta-Analysis.

Water scarcity constrains the sustainable development of Chinese agriculture, and deficit irrigation as a new irrigation technology can effectively alleviate the problems of water scarcity and water use inefficiency in agriculture. In this study, the drip irrigation cotton field under film in Xinjiang was taken as the research object. Meta-analysis and machine learning were used to quantitatively analyze the effects of different farm management practices, climate, and soil conditions on cotton yield and water use efficiency under deficit irrigation, to investigate the importance of the effects of different factors on cotton yield and water use efficiency, and to formulate appropriate optimization strategies. The results showed that deficit irrigation significantly increased cotton water use efficiency (7.39%) but decreased cotton yield (-15.00%) compared with full irrigation. All three deficit irrigation levels (80~100% FI, 60~80% FI, and 40~60% FI; FI: full irrigation) showed a significant decrease in cotton yield and a significant increase in water use efficiency. Under deficit irrigation, cotton yield reduction was the smallest and cotton water use efficiency increased the most when planted with one film, two tubes, a six-row cropping pattern, an irrigation frequency ≥10 times, a nitrogen application of 300~400 kg·ha-1, and a crop density ≥240,000 per hectare, and planted with the Xinluzhong series of cotton varieties; deficit irrigation in areas with average annual temperature >10 °C, annual evapotranspiration >2000 mm, annual precipitation <60 mm, and with loam, sandy soil had the least inhibition of cotton yield and the greatest increase in cotton water use efficiency. The results of the random forest showed that the irrigation amount and nitrogen application had the greatest influence on cotton yield and water use efficiency. Rational irrigation based on optimal management practices under conditions of irrigation not less than 90% FI is expected to achieve a win-win situation for both cotton yield and water use efficiency. The above results can provide the best strategy for deficit irrigation and efficient water use in drip irrigation cotton under film in arid areas.

Deficit irrigation strategy to sustain available water resources using guar

The gradual depletion of irrigation water is a major threat to the agricultural economy in the arid and semi-arid regions of the world. Drought–tolerant crops and improved irrigation management practices may help the sustainability of agriculture in the region. A three–year field experiment (2018–2020) was conducted to assess the effects of pre–and in–season irrigations on the physiology, biomass production, yield, and yield components of two diverse guar (Cyamopsis tetragonoloba) cultivars. A split-split plot design was used, where the main plot was pre–irrigation, subplots consisted of in–season irrigation treatments, and sub-sub plots were cultivars. Each treatment was replicated four times each year. Pre–irrigation improved the averaged final seed yield by 32% compared to plots with no pre–irrigation. Seed yield was significantly affected by in–season growth stage based irrigation treatments. Averaged over the years, full irrigation achieved the highest seed yield, although not significantly different from no irrigation during the vegetative growth stage in any study year. Cultivar Kinman performed better than Monument in biomass production and seed yield. Overall, pre–irrigation improves guar growth and development, leading to greater seed yield and biomass production. The most sustainable strategy to utilize the available water resources will be to grow guar with restricted irrigation during the vegetative growth stage, save 22% of water, and maintain a similar seed yield to plots that received irrigation throughout the crop season.

Green Manuring and Irrigation Strategies Positively Influence the Soil Characteristics and Yield of Coriander (Coriandrum sativum L.) Crop under Salinity Stress

This study shows the influence of soil salinity and irrigation dose on biomass production and its impact on some edaphic indicators and functions. For this purpose, an experiment was carried out in two representative soils from Murcia (SE Spain), one slightly saline (LS) and the other saline (S), where an oat–vetch green manure was intercalated between a spinach cycle and a coriander cycle; the latter being subjected to three different irrigation doses (deficient, optimum and surplus). Rapid response indicators (ECext, cations and anions in the soil solution, etc.) were monitored, as well as the material balances, in particular C and salts. Green manure and crop residues increased soil OC by 12.5% and reduced Na+ and NO3− concentrations. Total biomass production was also affected by salinity, both in oat–vetch, 35.9 and 31. 9 tm ha−1 in LS and S, respectively, and in the coriander crop, where the irrigation dose was decisive, obtaining around 29 tm ha−1 with the optimum and surplus doses and significantly lower amounts with the deficit dose: 20.4 tm ha−1 in LSD and 14. 0 in SD. Therefore, it is necessary to adjust the irrigation doses, since deficit irrigation significantly reduces production and the surplus does not lead to an increase with respect to the optimum, while also causing ions to leach to depth horizons, as is the case for NO3−, Cl− and Na+, with the consequent risk of contaminating the water table.

Implementation of an in-field IoT system for precision irrigation management

Due to the impact of climate change on agriculture and the emergence of water security issues, proper irrigation management has become increasingly important to overcome the challenges. The Internet of Things (IoT) technology is being utilized in agriculture for collecting field information and sharing it through websites in real time. This study discusses the efforts taken to develop an IoT-based sensor station, a user-friendly website, and a smartphone app for irrigation management. In addition, the demonstration of the IoT-based sensor station and its effectiveness are discussed. Before deploying the sensor station, soil moisture sensor calibration was conducted using a laboratory experiment. Overall, the calibrated soil moisture sensors met the statistical criteria for both sand [root mean squared error (RMSE) = 0.01 cm3/cm3, index of agreement (IA) = 0.97, and mean bias error (MBE) = 0.01] and loamy sand (RMSE = 0.023 cm3/cm3, IA = 0.98, and MBE = −0.02). This article focuses on case studies from corn, blueberry, and tomato fields in Michigan, USA. In the corn and blueberry fields, the evaluation of irrigation practices of farmer's using an IoT-based sensor technology was considered. In the tomato field, a demonstration of automation irrigation was conducted. Overirrigation was observed using the IoT-based sensor station in some fields that have sandy soil and use a drip irrigation system. In the blueberry demonstration field, the total yield per plant (p = 0.025) and 50-berry weights (p = 0.013) were found to be higher with the recommended irrigation management than the farmer's existing field. In the tomato demonstration field, there were no statistical differences in the number of marketable tomatoes (p = 0.382) and their weights (p = 0.756) between the farmer's existing method and the recommended irrigation strategy. However, 30% less water was applied to the recommended irrigation strategy plot. Thus, the result showed that the IoT-based sensor irrigation strategy can save up to 30% on irrigation while maintaining the same yields and quality of the product.

Adjustment of the AquaCrop model in maize with different levels of irrigation in southern Uruguay temperate climate conditions

The AquaCrop model allows evaluating and designing irrigation strategies that improve the use of irrigation water. The objective of this research was to calibrate and validate the AquaCrop model for maize to the climatic conditions of southern Uruguay, with different irrigation water management. This model was calibrated and validated for corn using experimental data from irrigation trials with different deficit levels in three seasons, 2015-16 and 2016-17 (calibration) and 2014-15 (validation). Three maximum irrigation depths were evaluated: 3, 6 and 9 mm day-1, and rainfed (rainfall only). The crop was parameterized for local conditions and water stress coefficients were adjusted. The calibration simulated the yield, biomass and soil moisture in the irrigated treatments with good performance. All the statistic indexes used to evaluate the adjustment between the observed and simulated data model indicated a good model performance, with the exception of the efficiency coefficient of the Nash-Sutcliffe (EF) model. The model underestimated the yield in the rainfed treatment (EF of -0.52) when root depth was limited to 0.7 m. However, the test soil allowed for greater radical exploration than the initially used. At 0.90 m root depth, the model was good at simulating the yields in the rainfed treatment, mainly in dry years (EF of 0.79). The model predicts the yield with good adjustment in different irrigation and rainfall situations if the stress coefficients are adjusted and the crop is properly parameterized, mainly the root depth.

Molecular and Physiological Responses to Exogenously Applied Melatonin in Spinach Under Deficit Irrigation Conditions

Melatonin, an important phytochemical, encourages plants to redirect growth in response to environmental stresses. The study aims to investigate the changes in the morphological, physiological, biochemical, and molecular properties of spinach subjected to the exogenous application of melatonin (MEL) at different doses under different water stress. The following four irrigation levels were applied: I100 (complete irrigation), I80 (20% water deficit), I60 (40% water deficit), and I40 (60% water deficit). MEL was applied through a spray on the leaves in three doses—0, 50, and 100 µM. In the present study, the application of MEL50 exhibited no significant decrease in water use efficiency (WUE) at the I80 irrigation level compared to the I100 irrigation level, while a significant decrease in the WUE was observed beyond this point. The application of MEL contributed to influencing the morphological parameters while also positively affecting the photosynthesis activity and, contribution to the antioxidant defense system. It was observed that the genes involved in the carbon metabolism of photosynthesis), the antioxidant mechanism, and the continuity of photosynthesis, all of which affect the expression of melatonin, facilitated water stress reduction in spinach. Therefore, it was inferred that the application of MEL50I80 could serve as an important irrigation strategy in semi-arid regions with limited water resources.

Water retention properties of wood fiber based growing media and their impact on irrigation strategy

Water retention properties of wood fiber based growing media and their impact on irrigation strategy

AI in precision agriculture: A review of technologies for sustainable farming practices

Precision agriculture, facilitated by advancements in Artificial Intelligence (AI), has emerged as a transformative paradigm in modern farming. This review comprehensively examines the integration of AI technologies in precision agriculture to enhance sustainability and optimize farming practices. The paper synthesizes recent research and developments in AI applications, covering key areas such as crop monitoring, resource management, decision support systems, and automation. The adoption of AI-driven techniques, including machine learning, computer vision, and sensor technologies, is reshaping traditional farming methods by providing farmers with real-time data and actionable insights. Crop monitoring applications utilize satellite imagery, drones, and ground-based sensors to assess plant health, detect diseases, and optimize irrigation strategies. AI-driven decision support systems empower farmers to make informed choices based on data-driven predictions, weather forecasts, and historical patterns, contributing to resource-efficient practices and minimizing environmental impact. Resource management is a critical aspect of sustainable farming, and AI plays a pivotal role in optimizing the use of water, fertilizers, and pesticides. Smart irrigation systems, enabled by AI algorithms, ensure precise and efficient water distribution, reducing water wastage and promoting water conservation. AI-driven analysis of soil conditions helps farmers tailor fertilization practices, enhancing nutrient utilization and minimizing environmental runoff. The review also explores the role of AI in automating farming operations through robotics and autonomous vehicles. These technologies not only alleviate labor shortages but also improve efficiency in planting, harvesting, and crop maintenance. Additionally, the integration of AI fosters connectivity in agriculture, enabling seamless communication between devices, sensors, and farming equipment. As precision agriculture continues to evolve, the review highlights challenges and future prospects. Ethical considerations, data security, and the digital divide in rural areas are among the challenges that need attention. Moreover, the paper discusses potential avenues for further research, emphasizing the need for interdisciplinary collaboration to address the complex issues associated with the sustainable implementation of AI in precision agriculture. This review provides a comprehensive overview of the transformative impact of AI in precision agriculture, offering insights into current technologies, challenges, and future directions. The integration of AI not only enhances productivity and efficiency but also contributes to the long-term sustainability of farming practices, ensuring food security in the face of a growing global population.