Insufficient Irrigation Research Articles

Drought tolerance and recovery capacity of two ornamental shrubs: Combining physiological and biochemical analyses with online leaf water status monitoring for the application in urban settings

When plants are transferred from nursery to urban environments, they often face drought stress due to inadequate maintenance, such as insufficient irrigation. Using drought tolerant species may help mitigate the adverse impact of drought stress in urban settings. Additionally, utilizing novel technologies for water status monitoring may help optimize irrigation schedules to prevent transplanting failures. This study investigated the physiological and biochemical responses of two ornamental shrubs, Photinia x fraseri and Viburnum tinus, subjected to water stress of increasing severity and rewatering. Water relations, gas exchanges, chlorophyll fluorescence and biochemical analyses were conducted alongside real-time monitoring of water status using leaf-water-meter sensors (LWM).The progression of water stress had a notable negative impact on leaf gas exchanges and water relations in both species. Notably, P. fraseri avoided photoinhibition by reducing chlorophyll content and actual efficiency of PSII. Adjustments in leaf phenolic compounds played a significant role in enhancing drought tolerance of both species due to their antioxidant and photoprotective properties.Upon rewatering, both species exhibited complete recovery in their physiological functions, underscoring their remarkable tolerance and resilience to drought stress. Additionally, LWM sensors efficiently tracked the dehydration levels, exhibiting a rising trend during the water stress progression and a subsequent decline after rewatering for both species. These findings confirm the reliability of LWM sensors in monitoring physiological status of plants in outdoor contexts, making them a suitable tool for use in urban settings.

Study of genetic variations of oat varieties under insufficient and insufficient irrigation

A field experiment was carried out in the fields belonging to the Faculty of Agricultural Engineering Sciences /University of Baghdad-Jadriya during the season 2020-2021 in order to study the genetic variations of varieties of oats under lack of irrigation. The experiment was carried out using the design of complete random sectors and the distribution of splintered panels and two factors, the first was the treatment of irrigation at the arrival of humidity ( 50%, 25% and 10%), while the second factor was the varieties (Genzania, Anatolia, plmulao Algoda and healing ) the experiment was carried out three times. The results showed that the third irrigation level exceeded the number of days of planting up to 75% flowering in the second irrigation treatment gave the highest averages for all other qualities studied, and the V4 variety gave the highest average for all qualities except for the weight of 250 grains. . While there was a significant significant difference for the second irrigation level in the values of genetic variation for all accuracy except for the single trait, while we note that accuracy is the number of branches and the total number of branches only and it was highly effective at the first irrigation level. Later, the effect was good at the second irrigation level. The difference is in appearance. It is noted that the values at the second level of road types, except for the obtained characteristic and the nature ratio, gave the second level of irrigation the highest average for most types of resistance. Why is it not different from what was mentioned above, which did not adopt a study of scientific variations in the expected researchers, as you would expect, the second irrigation and the V4 variety, which recorded the highest averages for the characteristics that were studied.

Assessing the Use of Butachlor 5G in High and Mid Altitude Rice Growing Areas in Bhutan: A Case Study

Rice is a vital cereal crop in Bhutan, cultivated widely for domestic consumption. Rice production is gradually decreasing due to diverse reasons including labour shortages and insufficient irrigation water. With the shortage of farm labour, weed management is challenging and Bhutanese farmers have long relied on Butachlor 5G for weed control. However, prolonged use of a single herbicide can lead to herbicide resistance in weeds. This study aimed to determine the extent of use of the weedicide and to assess the development of Butachlor resistance in paddy weeds through farmers’ perceptions. The study, conducted in four western rice-growing areas, surveyed 190 farmers using semi-structured questionnaires. The findings revealed that Butachlor has been extensively used for over three decades, with most farmers applying it more than the recommended dosage. Despite this, 86.85% of respondents reported a decrease in Butachlor's effectiveness over the years. More than half of the respondent (50.53%) believed that weeds had developed resistance to Butachlor, a concern that correlated with the increased dosage used. The findings suggest a diminishing efficacy of Butachlor, potentially attributed to the development of herbicide resistance. Of significance, the study identifies Potamogeton distinctus as the most prevalent weed, followed by Schoenoplectiella juncoides and Pontederia vaginalis in the surveyed areas.

An Investigation into Ensemble Learning Techniques for Evaluating Soil Fertility through Analytical Approaches

At the heart of India’s livelihood lies agriculture, a foundational and ever-evolving sector. The realm of agriculture faces modern challenges, encompassing unpredictable climate fluctuations, insufficient irrigation infrastructure, and erratic weather conditions. Amidst these challenges, machine learning has emerged as a valuable tool for evaluating soil fertility and Crop assessment in agriculture. Ensemble machine learning methodologies have garnered attention for their potential to enhance predictive capabilities. These techniques involve constructing meta-classifiers that collectively contribute to improved predictive accuracy. This paper centers on the analysis of soil data acquired from testing laboratories, to predict fertility based on a comprehensive dataset. The study employs prominent ensemble machine learning algorithms, specifically focusing on boosting techniques, to elevate predictive accuracy and ensure heightened consistency.The assessment of soil fertility categories involved the examination of 12 carefully chosen attributes. Diverse soil parameters were measured to facilitate the prediction of soil fertility levels. The outcomes of the experimentation revealed that the application of the boosting technique using the Xgboost algorithm yielded superior accuracy compared to alternative ensemble classifiers, achieving a remarkable 96% accuracy rate.

Performance Evaluation of the Water Advisory for Irrigation Scheduling System (WAISS) Capacitance Soil Moisture Sensor

The agriculture sector accounts for 80% of the total freshwater resource use in the Philippines. With increasing competition for the scarce water supply, it is necessary to utilize water resources efficiently. The application of smart irrigation technology can help achieve higher water use efficiency, increase farm water productivity, and maximize crop yield. To minimize excess or insufficient irrigation water application to crops, and provide more effective and efficient water management, an integrated water monitoring system called Water Advisory for Irrigation Scheduling System (WAISS) was developed. The performance of WAISS was initially evaluated by comparing the soil moisture measurements of its capacitance soil moisture sensor with a commercially developed sensor and the standard gravimetric method. Statistical analysis shows that the low-cost WAISS soil moisture sensors are comparable with the commercially developed sensors with a Percent Error of 5.5% compared to METER ECH2O EC-5's 16.1%. This highlights WAISS' potential as a cost-effective yet reliable alternative for soil moisture monitoring.

Deficient Irrigation and Its Impact on Water Use Efficiency, Maize Yield and some of Its Components

In spring 2021, a clay mixture soil field experiment was conducted in one of Babylon province’s Al-Ataij agricultural fields, 2 km from Hilla’s centre (32°29"24.178″N 43°26"56.459″E) to study the effects of incomplete irrigation on crop sensitivity, water use efficiency, maize yield, and some of its components. Three-replicate RCBDs. Eight treatments were used: the full irrigation treatment (control) after 50% of the available water was drained, and seven incomplete irrigation treatments (25% of the available water was provided after the soil moisture content reached the permanent wilting point) within the root zone. Negative or incomplete irrigation during vegetative development, blossoming, crop output, or both. The number of grains, 1000-grain weight, total yield, crop and field irrigation efficiency, additional water, and real water consumption were calculated. All farming followed rules. Water balance equations calculated effective evapotranspiration (Eta). Full irrigation used 335.26 mm, partial irrigation 341.55 mm, and 147.10 mm. Partial irrigation only lowered real water use by 9.61% in crop formation, 12.90% in vegetative development, and 26.11% in blooming. Insufficient irrigation did not alter yield components, number of grains, 1000-grain weight, or grain yield during yield development. Irrigation decreased characteristics by 1.2, 1.7, and 5.0%. Incomplete vegetative and flowering watering elevated attribute drop rates to 28.2, 9.4, and 54.6. Incomplete watering affects blooming more than vegetative growth and production. Except during growth phases, incomplete irrigation during crop development outperformed all other incomplete and full irrigation treatments. Incomplete crop irrigation was most efficient (1.075 kg/grain 1) and least average (0.75) kg/grain. Water-tolerant crop growth. Water-sensitive plant growth. Correcting poor flower watering boosted crop irrigation efficiency. Partial irrigation only improved crop development ethically.

Deficit irrigation limits almond trees’ photosynthetic productivity and compromises yields

Almond yields vary between rainfed and intensively irrigated systems, but how to match irrigation to potential productivity is unclear. Hence, we compared almond physiology under deficit (600 mm) and full (1300 mm) irrigation to identify stress indices and determine the production overheads of mismanaged watering. We hypothesized that trees alter their growth to conserve resources during drought and mitigate their hydraulic stress responses. Thus, we monitored stem water potential and stomatal conductance to characterize the hydraulic responses of trees to deficient and hydrated water conditions. Adapting the seasonal relationship between irrigation coefficients and tree water potential was also tested. Finally, soil water status and trunk development were considered physical stress indices for field conditions. Soil water depletion in deficit irrigation reduced stem water potential below − 2 MPa and checked stomatal conductance at 0.15 mol m-2 s-1 for most of the growing season. An empirical productivity model determined that, under deficit irrigation, almond trees suffer from chronic stress that limits their photosynthetic capacity to ∼14 µmol m-2 s-1. Consequently, nominal assimilation limitations (10%) in early summer manifested to 4 kg C tree-1 metabolic losses by autumn. The inter-annual vegetative limitations in deficit irrigation resulted in significant yield reductions (35%) by the second experimental season. Temporal changes in the correlations between stem water potential, stomatal conductance, and trunk contractions made it difficult to use water stress indices to make irrigation decisions. However, normalizing tree performance by phenology indicated a 960 mm irrigation that supported high yields. Further, integrating the variability in soil water with trunk dendrometry illustrated that trees could maintain constant growth between irrigation days under well-watered conditions. Hence, in commercial operations, variable growth rates and trunk contraction measures signal insufficient irrigation and could guide practical irrigation adaptations.

Towards phase-sensitive optical coherence tomography in smart laser osteotomy: temperature feedback

Thermal effects during bone surgery pose a common challenge, whether using mechanical tools or lasers. An irrigation system is a standard solution to cool the tissue and reduce collateral thermal damage. In bone surgery using Er:YAG laser, insufficient irrigation raises the risk of thermal damage, while excessive water lowers ablation efficiency. This study investigated the potential of optical coherence tomography to provide feedback by relating the temperature rise with the photo-thermal expansion of the tissue. A phase-sensitive optical coherence tomography system (central wavelength of λ=1.288 μm, a bandwidth of 60.9 nm and a sweep rate of 104.17 kHz) was integrated with an Er:YAG laser using a custom-made dichromatic mirror. Phase calibration was performed by monitoring the temperature changes (thermal camera) and corresponding cumulative phase changes using the phase-sensitive optical coherence tomography system during laser ablation. In this experiment, we used an Er:YAG laser with 230 mJ per pulse at 10 Hz for ablation. Calibration coefficients were determined by fitting the temperature values to phase later and used to predict the temperature rise for subsequent laser ablations. Following the phase calibration step, we used the acquired values to predict the temperature rise of three different laser-induced cuts with the same parameters of the ablative laser. The average root-mean-square error for the three experiments was measured to be around 4 °C. In addition to single-point prediction, we evaluated this method’s performance to predict the tissue’s two-dimensional temperature rise during laser osteotomy. The findings suggest that the proposed principle could be used in the future to provide temperature feedback for minimally invasive laser osteotomy.

Preparation of floral calendar of bee flora available in Lamjung district, Nepal

Between March and May 2022, researchers conducted a broad survey in the Lamjung district to ascertain the presence and accessibility of bee-friendly flora to compile a floral calendar. In the PMAMP Bee Zone, 62 respondents were chosen for the interview through a simple random sampling approach, from a pool of 382 registered beekeepers. Primary data collection involved using personal interviews, focus group discussions, and key informant surveys. Secondary data were gathered from publications related to the topic from various institutions. The collected data were then analyzed using IBM SPSS V.26 and Microsoft Excel. Nearly all farmers in the study area kept Apis cerana bees, but due to insufficient irrigation, the crop fields provided limited forage for the bees during certain periods. The lowest number of frames covers by bees was four during the dearth period. Farmers in the Lamjung district did not practice migratory foraging. The majority of the respondents reported an increase in productivity compared to the previous year. However, only 37.1 percent of them cultivated bee flora. The colony carrying capacity of the forage area was not estimated. Additionally, an increase in deforestation was identified as the major problem affecting bee foraging. To address these issues, it was recommended to plant and cultivate perennial trees such as butter trees (Vitellaria paradox), bottle brush (Callistemon speciosus), litchi (Litchi chinensis), sissoo (Dalbergia sissoo), and sunflower (Helianthus annus) with assured irrigation. This approach could ensure year-round forage availability and reduce the need for artificial feeding. The research aimed to explore the current status of honey bee flora and investigate major flora that could be introduced in the study area.

Optimal allocation model and method for parallel ‘reservoir and pumping station’ irrigation system under insufficient irrigation conditions

The effective regulation and storage of water resources by reservoirs in arid and semi-arid areas is important for alleviating water resource shortages. In this paper, multiple irrigation reservoirs and pumping stations are evaluated, according to their special hydraulic connections and used to establish the water resources optimal allocation model of the parallel ‘reservoir and pumping station’ irrigation system. The mathematical model takes the maximum total income of the whole irrigation area as the objective function, the water supply and spill of the reservoir and the water replenishment of the pumping station as the decision variables, and the system water supply, agricultural water rights, reservoir operation criteria as the constraints. A new multilevel decomposition aggregation dynamic programming (MDADP) algorithm is proposed to solve the complex nonlinear model and is compared with the real-coded genetic algorithm, particle swarm optimization, cat swarm optimization and whale optimization algorithm. From the analysis of optimality and the applicability of the algorithm, MDADP was found to be more suitable than the above heuristic models for solving problems in the field of the optimal allocation of water resources.

REVIEW ON CURRENT STATUS OF AVOCADO PRODUCTION IN ETHIOPIA

The study discusses the global significance of avocado as a nutritious fruit and economically important crop. It focuses on the increasing demand for avocados and the potential for their cultivation in Ethiopias diverse agro-ecological zones. The review article examines a wide range of peer-reviewed studies, reports, and literature up to September 2022, using various sources including electronic databases and academic repositories. Grey literature and agricultural organization reports were also considered. The review findings show that avocado production in Ethiopia has been rapidly growing. In 2021, the country produced 245,336 metric tons of avocados across 30,585.70 hectares, with a yield of 80.2 quintals per hectare. Ethiopia exported 604.5 quintals of avocados in the same year. The favourable agro-ecological diversity of Ethiopia, spanning from lowlands to highlands, supports avocado cultivation. However, the industry is still young and faces challenges such as limited access to quality seeds, insufficient irrigation systems, and transportation issues. The post-harvest phase, processing, and marketing of avocados also present difficulties, leading to lower product quality and constrained market reach. The review covers global and local avocado production trends, avocado production and management practices, constraint of avocado production and future direction have been discussed. KEYWORDS: Avocado Production, Production Constraints, Post-harvest losses

Response of the tomato rhizosphere bacterial community to water–oxygen coupling under micronanobubble oxygenated drip irrigation in mildly saline soil

AbstractThe deterioration of the soil water–air environment due to salinization can reduce soil bacterial activity and cause crop yield reduction. Micronanobubble oxygenated drip irrigation can significantly improve the nonsaline soil water–air environment and enhance bacterial activity, but its effect on salinized soil bacteria is unknown. In this study, we used a tomato cultivation experiment in mildly saline soil to evaluate the responses of the rhizosphere bacterial community to the soil microenvironment created by micronanobubble oxygenated drip irrigation. The results indicated that the soil environmental factors (including soil electrical conductivity, i.e., EC) (r = 0.46) and root length (r = −0.86) had important regulatory effects on bacterial community function, which had significant direct effects on tomato yield (r = 0.46). The moderate dissolved oxygen concentration treatment significantly reduced the EC by 63.22%–73.32% compared with CK (noncultivated soil treatment) and generally increased the root length; however, only the combination of a moderate dissolved oxygen concentration and excess irrigation (A15W1.2) significantly increased tomato yields by 190.90% compared with A0W0.8 (the combination of a low dissolved oxygen concentration and insufficient irrigation) because the irrigation water volume was the limiting condition affecting the benefits of the root length increase. The high dissolved oxygen concentration treatment significantly reduced the EC by 60.36%–92.31% and increased the bacterial community diversity by 4.08%–6.16% compared with CK; these aforementioned changes favored the increase in tomato yield. However, similar to the result of the moderate dissolved oxygen treatments, the tomato yields were significantly higher and among the highest of all treatments only when a high dissolved oxygen concentration was combined with sufficient irrigation or excess irrigation (A30W1 or A30W1.2) due to the limiting effect of the irrigation water volume. Therefore, accounting for the changes in EC, soil bacterial community, and tomato yields, A15W1.2, A30W1, and A30W1.2 are recommended for tomato production in mildly saline soils.

Monitoring of Cropland Abandonment Based on Long Time Series Remote Sensing Data: A Case Study of Fujian Province, China

Farmland is the basis for human survival and development. The phenomenon of cropland abandonment has seriously affected national agricultural production and food security. In this study, remote sensing monitoring of abandoned cropland is carried out based on multisource time series remote sensing data using the Google Earth Engine (GEE) cloud platform. Landsat and Sentinel-2 time series data from 2010–2021 were used to obtain monthly synthetic cloud-free image sets in combination with cropland plot data. The time series farmland probability dataset was generated using the random forest classification method. The LandTrendr algorithm was used to extract and analyse the time series cropland probability dataset. Finally, this study also explored the drivers of change in abandoned cropland in Fujian Province. The results show that (1) the LandTrendr algorithm can effectively extract abandoned farmland and avoid the impact of pseudovariation resulting from non-farmland categories. A total of 87.02% of the abandoned farmland was extracted in 2018; 87.50% of the abandoned farmland was extracted in 2020. (2) The abandoned area in Fujian Province fluctuated after a significant increase in 2012, with the abandoned area exceeding 30 thousand hectares. Since 2017, the abandoned area has decreased to slightly below 30 thousand hectares. (3) The regression results of the factors affecting abandoned cropland in Fujian Province show that the increase in the number of agricultural workers and the improvement in soil organic matter content will significantly reduce the area of abandoned cropland in Fujian Province, while the increase in the rate of urbanization, poor road accessibility, and insufficient irrigation conditions will increase the area of abandoned cropland. The results of this study are useful for conducting surveys of cropland abandonment and obtaining timely and accurate data on cropland abandonment. The results of this study are of great significance for the development of effective measures to stop the abandonment of cropland, and ensure the implementation of food security strategies.

An enhanced version of the D-Risk decision support webtool for multi-scale management of water abstraction and drought risks in irrigated agriculture

Due to it having the lowest priority for water allocation during drought events and the consequent agronomic and economic impacts of abstraction restrictions, UK irrigated agriculture has been identified as a key business sector ‘at risk’. An enhanced version of the D-Risk webtool has been developed to help agricultural stakeholders and catchment water managers to evaluate the joint multi-scale risks of abstraction restrictions (voluntary and mandatory) and having insufficient irrigation volumes during drought events. The webtool uses annual maximum potential soil moisture deficit as the agroclimate index to calculate monthly and annual volumetric irrigation demand for the selected crop mix, soil available water capacity and location. Simulated river flows are used to identify days not under abstraction restrictions. Annual probability distributions of irrigation deficit and licence utilisation (headroom) are derived from a monthly time-step water balance model that calculates whether the farm irrigation demand in each month can be met, taking account of river flow-based abstraction restrictions, daily and annual volumetric licensed abstraction limits, the licenced abstraction period(s) and any on-farm reservoir storage. The enhanced D-Risk tool provides a more holistic understanding of drought risk on irrigated agriculture from individual farm to catchment scales and supports improved collaborative decision-making regarding future water sharing, water trading and on-farm reservoir investment to reduce business vulnerability to drought and regulatory change.

Alkaline Salt Tolerance of the Biomass Plant Arundo donax

Soil alkalinization and salinization have increased worldwide due to extreme and/or prolonged drought periods as well as insufficient irrigation. Since crops generally react to soil salinity and high pH with decreased yield, the cultivation of tolerant biomass plants represents a reasonable alternative. Thus, we aimed to characterize the tolerance of the biomass plant Arundo donax to alkaline salt stress, induced by irrigation water containing NaHCO3 and Na2CO3 mixture (1:1) at 80 mM and 200 mM of final concentration and pH 10. In terms of physiological parameters such as transpiration, chlorophyll content, photosystem II quantum efficiency, relative water content, and water saturation, the plants were resistant to the stress treatment. The negative impact on the water regime was only measured at 200 mM salt. The K/Na ratio decreased in parallel with Na accumulation. Plants also accumulated Zn, whereas a decrease in the concentration of most other elements (Ca, Cu, K, Mg, Ni, S, Si, and Sr) was detected. Antioxidative defence directed by multiple symplastic enzymes contributed to the high physiological tolerance to the applied stress. In conclusion, the cultivation of Arundo donax as a biomass crop appears to be a feasible alternative in areas affected by salinity or alkaline salt accumulation.

Increase in root density induced by coronatine improves maize drought resistance in North China

Drought stress caused by insufficient irrigation or precipitation impairs agricultural production worldwide. In this study, a two-year field experiment was conducted to investigate the effect of coronatine (COR), a functional analog of jasmonic acid (JA), on maize drought resistance. The experiment included two water treatments (rainfed and irrigation), four COR concentrations (mock, 0 μmol L−1; A1, 0.1 μmol L−1; A2, 1 μmol L−1; A3, 10 μmol L−1) and two maize genotypes (Fumin 985 (FM985), a drought-resistant cultivar and Xianyu 335 (XY335), a drought-sensitive cultivar). Spraying 1 μmol L−1 COR at seedling stage increased surface root density and size, including root dry matter by 12.6%, projected root area by 19.0%, average root density by 51.9%, and thus root bleeding sap by 28.2% under drought conditions. COR application also increased leaf area and SPAD values, a result attributed to improvement of the root system and increases in abscisic acid (ABA), JA, and salicylic acid (SA) contents. The improvement of leaves and roots laid the foundation for increasing plant height and dry matter accumulation. COR application reduced anthesis and silking interval, increasing kernel number per ear. COR treatment at 1 μmol L−1 increased the yield of XY335 and FM985 by 7.9% and 11.0%, respectively. Correlation and path analysis showed that grain yields were correlated with root dry weight and projected root area, increasing maize drought resistance mainly via leaf area index and dry matter accumulation. Overall, COR increased maize drought resistance mainly by increasing root dry weight and root area, with 1 μmol L−1 COR as an optimal concentration.

Effect of Organic Matter And Soil Suspension on Clogging Drip Emitters under Application Two Different Water Qualities

       One of the most critical variables affecting the performance of drip irrigation systems is emitter clogging, which occurs quickly as a result of irrigation systems operating under insufficient pressure or due to poor water quality, not only affecting water distribution uniformity but also results in insufficient irrigation. To investigate the clogging potential of the drippers, two types of water quality were tested. Using local materials organic matter and soil suspension account for more than 47 percent of the clay content was applied with water. The tests identified the clogging severity of emitters with organic matter application for both water qualities Sumael (LSI) and Bazalan (LSII) respectively. In general, clogging ratios developed with time for both water qualities, the most distinct was organic matter application that reduced the discharge rate to 15.561% for Sumael water (LSI) corresponding to Bazalan water (LSII) was 38.002%. The flow rate of the drippers was also affected by the soil suspension particles. The percentages found in the Bazalan water was 5.62%, which was close to 5.575% in the Sumael water.

Synchronous management of public green spaces: The case of Imam Abdulrahman bin Faisal University’s eastern campus – Dammam, Saudi Arabia

The scarcity of water available for landscape irrigation is a great challenge facing urban greenery and landscaping initiatives in arid and semi-arid regions. The Imam Abdulrahman bin Faisal University (IAU) has established a new campus on 3,2000,000 M2 of land extended to the eastern coast of the Arabian Gulf. Since moving to the Eastern Campus in 2014, the IAU has been working hard to increase the green spaces to minimize the environmental impact of harsh climate, hard surfaces, and building masses. In its endeavor to achieve this goal, the management of landscape plant materials and irrigation systems has not kept pace with the development of the campus. Almost 800 M3/day of irrigation water has been pumped into the system however it fails to maintain good quality landscape plants. As a result, green spaces suffer great degradation especially during hot months due to insufficient irrigation management and other factors. This study is an attempt to explore the relationship between the expansion of green spaces on the IAU’s Eastern Campus and their irrigation requirements. It applied the investigative analytical method to study and analyze the green spaces elements and their daily water budget, which led to the proposal of a synchronous management approach balancing the amount of water available for irrigation purposes and the qualities and expansion of landscape plant materials. The study found that applying the required water budget to plants since their establishment on their permanent locations is a waste of available resources, but it must be gradually increased based on the plant's size, its growth rate, and seasonal changes. However, a synchronous management approach is required to ensure that good quality landscapes are maintained while using limited available resources.

Effects of film mulching on the physiological and morphological parameters and yield of cucumber under insufficient drip irrigation

AbstractA comprehensive study was conducted to analyse the influence of film mulching on the soil water content (SWC), plant physiological and morphological parameters, yield and irrigation water use efficiency (IWUE) of cucumber grown in a greenhouse. The experiment was designed to set the film mulching (M1) and non‐film mulching (M0) applications under two irrigation levels (T1: sufficient irrigation; T2: insufficient irrigation). Thus, four treatments, i.e. T1M1, T1M0, T2M1 and T2M0 were set. The response of plant growth, physiology characteristics, yield and SWC under the designed treatments was analysed based on the data from two planting years (2019 and 2020). Applying film mulching effectively improved the SWC by approximately 10%. The cucumber plant height, stem diameter and leaf area index (LAI) under the T2M1 treatment increased by 38.0–63.1, 16.5–24.9 and 84.0–89.4%, respectively, compared to the T2M0 treatment. The maximum yield was found in the T1M1 treatment, which increased by 24.2–27.5% compared to T1M0. Film mulching increased cucumber yield by 18.0–24.7% compared to non‐film mulching. It was also observed that film mulching under insufficient drip irrigation had a positive influence on plant morphological parameters (photosynthetic rate and stomatal conductance). Among the four treatments, the maximum photosynthetic rate (= 20.69 μmol m−2 s−1) and stomatal conductance (= 0.47 μmol m−2 s−1) were found in the T2M1 treatment. The sap flow rate under the T2M1 treatment was close to that under the T1M0 treatment, while the largest variation in the sap flow rate occurred under the T1M1 treatment, and the smallest variation occurred under the T2M0 treatment. It can be concluded that the effect of the film mulching technique on cucumber yield and IWUE was significant under insufficient drip irrigation.

Simulation of Soil Water and Heat Flow under Plastic Mulching and Different Ridge Patterns

The ridge–furrow mulching system with plastic film (RFMS) has been widely used in semi-arid areas in order to improve soil water and heat conditions, crop yields and water use efficiency. It is of practical significance to study the effect of mulching and ridge types on soil water and heat in order to optimize mulching measures and improve the effectiveness of the ridge and furrow system. To clarify the combined effect of soil water and heat beneath the system and the influence of ridge morphology on it, field experiments were conducted with three treatments, including conventional planting in bare land (CK), a ridge–furrow (wide ridge with 70 cm width and 10 cm height, narrow ridge with 40 cm width and 15 cm height) mulching system with complete plastic film (RFWN) and a ridge–furrow (equal ridge with 55 cm width and 15 cm height) mulching system with complete plastic film (RFE). An insufficient irrigation system was adopted and the two-dimensional numerical software HYDRUS-2D was used to simulate the soil water and heat flow under the experimental conditions. The model was calibrated and verified according to test data for the period of 2018 to 2019, which showed good agreement between the simulated and measured values. The simulation results revealed that the ground temperatures of RFWN and RFE were much higher than that of CK, and the average value of 0–25 cm during the growth period could increase by 2.29–4.61%. Compared with CK, RFWN and RFE reduced soil evaporation (84.71–93.73%) and field evapotranspiration (12.02–21.75%), while they increased root water uptake (25.87–40.98%) and T/ET (48.85–80.15%). Plastic film mulching and ridge morphologies affected the infiltration range and the direction of soil water movement, increased soil moisture when there was no rainfall or irrigation and reduced soil water and heat fluctuations, which was more conducive to crop growth, especially under the RFWN system. The simulation method proposed in this paper is an effective technique for calculating the soil water and heat dynamics under different ridge and furrow sections under the condition of film mulching, and it can be used for the optimal management of soil water and heat in this area.