Amount Of Irrigation Water Research Articles

Determining Irrigation Requirements of Extensive Crops Using the Typical Meteorological Year Adjusted to the Growing Cycle Period

In the Castilla-La Mancha (CLM, Spain) region, most of the irrigated area is managed by two different strategies in which the previously defined irrigation requirements of crops affect both the distribution of crops and the sustainable management of groundwater resources. Thus, in the western Mancha system, the amount of irrigation water per farm is limited, while in the eastern Mancha system the irrigable area per farm is limited. Therefore, the use of average irrigation requirements in these areas may cause yield drops in dry years and the overuse of groundwater. Consequently, the main aim was to achieve a better approach to the irrigation requirements of the main extensive crops in CLM (maize (Zea mays L.), onion (Allium cepa L.), garlic (Allium sativum L.), and barley (Hordeum vulgare L.)) to help farmers and water authorities achieve higher yields and a more sustainable use of water resources. The typical meteorological year (TMY) methodology combined with the MOPECO model were used to: (1) determine the distribution of wet, intermediate, and dry years during the growing cycle of the four selected crops; (2) determine the average (AVE) and typical irrigation requirements of these crops for the complete 70 years series (TMYG) or the duration of the crop cycle (TMYC), and under wet (TMYW), intermediate (TMYI), and dry (TMYD) year conditions; and (3) recommend the irrigation depths to be used for the management of farms and water bodies. The results show that the number of wet, intermediate, and dry years depends on the growing cycle of the crop considered, with wet years being unusual, although they notably increase the average rainfall in the area. The irrigation requirements for the average year were between 20.4 and 9.0% lower than the average irrigation requirements calculated for the four studied crops during the 70 years of the series. For western Mancha farmers the recommended irrigation depth for dry years and most profitable crops (garlic and onion) is the one calculated for the driest year of the series, while for the rest of the years and crops is that estimated by the global dry TMY (TMYGD). For eastern Mancha farmers the recommended irrigation depths are also those estimated by the TMYGD.

Optimasi PID Kontroller Pada Sistem Pengaturan Irigasi Menggunakan Metode Bat Algorithm (BA)

Provision of irrigation water on agricultural land aims to meet crop water needs. In its utilization, irrigation water must be used optimally. An automatic irrigation system is needed that is able to provide water for plants with the expected conditions. PID (Proportional, Integral and Derivative) is widely used for optimization of control systems. In irrigation control system and sensor connection with software program (Matlab 2013b). PID simulation was applied to the irrigation prototype used to increase efficiency and determine the amount of irrigation water to regulate the provision of irrigation water as needed. As a comparison controller, conventional PID (PID-Konv) was used, Matlab auto tuning PID (PID-Auto), and Bat Algorithm tuning PID (PID-BA). The simulation results show that PID-BA is the best method in the simulation with the smallest overshot (0.043) and the fastest settlingtime (84 seconds).

Matching water requirements of Chinese chives planted at different distances apart from the line emitter under negative pressure irrigation subsurface system

To supply water to crop in a proper way by using subsurface negative pressure irrigation (NPI), the distribution of soil moisture around the emitter with different water supply pressure (N1: −2 kPa, N2: −4 kPa, N3: −6 kPa) was investigated with surface irrigation as control (CK), to discuss the match degree of soil moisture to root distribution of Chinese chives planted at different distance apart from the NPI emitter. In the first growth season (FG), it took more than 15 days to form the stable wetting body of NPI due to the very low initial soil moisture, as a result the soil moisture and soil water storage (W) in NPI was lower than CK. In the second growth season (SG), the wetting body of NPI is almost invariable along time, and the soil moisture was much higher in NPI system with N1 significantly larger than CK. The yield showed a significant positive relation with soil moisture and W in both growth period (R was 0.942 and 0.849, respectively). As a result, the yield in NPI was significantly lower than CK in the FG and the yield in N1 was much higher than CK in the SG (p < 0.05). IWUE in NPI was significantly lower than CK in the FG while significantly larger than CK in the SG (p < 0.05). At the same water supply pressure, the soil moisture content was larger near the emitter, resulting better crop growth (p < 0.05). From the perspective of long-term irrigation, NPI could obtain a better yield and IWUE with less irrigation water amount (p < 0.05). The water supply pressure of − 2 kPa was more feasible to supply water for 6 lines of Chinese chives, with the same yield to CK and much higher IWUE (p < 0.05). The results indicated that planting crops in regions with proper soil moisture contents within the unique wetting body of NPI maintained high crop yield and improved crop IWUE, thus it is feasible to supply water for multiple rows of dense planted crops of Chinese chives with one linear emitter of the NPI subsurface system.

Evaluation of irrigation experiments with GGE biplot method and economic analysis of drip irrigation system: a case study of peanut production

Besides irrigation water quantity and quality, there is a decrease also in soil quality and fertility. Agricultural production lands are decreasing both in quantity and quality. There is a search for different operational alternatives in sandy soils with low production potentials. Drip irrigation is largely practised to get greater yields per unit area. This study was conducted under sand soil conditions, commonly preferred for peanut farming, in the 2017- 2018 growing seasons. A drip irrigation system was used in production. Two different irrigation intervals (2 and 4 days) and four different irrigation levels (I50, I75, I100 and I125, calculated based on cumulative evaporation from the class-A pan) were applied. Evapotranspiration values varied between 402-832 mm, applied irrigation water quantities between 313-783 mm, yields between 5269-8269 kg ha-1, water use efficiency (WUE) values between 0.63-1.55 kg ha-1 m-3, economic water productivity (EWP) over gross revenues between 1.29-3.81 $ m-3 and benefit and cost ratios (B/C) varied between 4.73-10.95. The GGE biplot statistical method is a useful tool in the evaluation of irrigation research where the number of applications and materials is high.

A data-driven approach using the remotely sensed soil moisture product to identify water-demand in agricultural regions.

Effective agricultural water management requires accurate and timely identification of crop water stress at the farm-scale for irrigation advisories or to allocate the optimal amount of water for irrigation. Various drought indices are being utilized to map the water-stressed locations/farms in agricultural regions. Most of these existing drought indices provide some degree of characterization of water stress but do not adequately provide spatially resolved high-resolution (farm-scale) information for decision-making about irrigation advisories or water allocation. These existing drought indices need modeling and climatology information, hence making them data-intensive and complex to compute. Therefore, a reliable, simple, and computationally easy method without modeling to characterize the water stress at high-resolution is essential for the operational mapping of water-stressed farms in agricultural regions. The proposed new approach facilitates improved and quick decision-making without compromising much of the skills imparted by the established drought indices. This study aims to formulate a water-demand index (WDI) based on a parameter-independent data-driven approach using readily available remote sensing observations and weather data. We hypothesize that the WDI for an agricultural domain can be characterized by soil moisture, vegetative growth (NDVI), and heat unit (growing degree day, GDD). To this end, we used remote sensing-based soil moisture and NDVI and modeled ambient temperature datasets to generate weekly WDI maps at 1 km. The proposed methodology is verified over a few intensively irrigated agricultural-dominated areas with different climatic conditions. Our results suggest that the proposed approach characterizes water-stressed fields through WDI maps with good spatial representativeness. Overall, this study provides a framework to generate weekly WDI maps quickly with readily available measurements. These water-demand maps will help water resource managers to reduce dependence on established drought indices and prioritize the specific regions/fields with high water demand for optimum water allocations to improve crop health and ultimately maximize water-use efficiency.

How accurately can we retrieve irrigation timing and water amounts from (satellite) soil moisture?

While ensuring food security worldwide, irrigation is altering the water cycle and generating numerous environmental side effects. As detailed knowledge about the timing and the amounts of water used for irrigation over large areas is still lacking, remotely sensed soil moisture has proved potential to fill this gap. However, the spatial resolution and revisit time of current satellite products represent a major limitation to accurately estimating irrigation. This work aims to systematically quantify their impact on the retrieved irrigation information, hence assessing the value of satellite soil moisture for estimating irrigation timing and water amounts.

Use Radial Basin Function &amp;Empirical Bayesian kriging To derive and improve the digital height model from the topographic map (Case study on Lake Talker)

The study of lakes and how they are represented spatially is important and has a key role in the construction and development of any country and this depends on the main location of the lake and the possibility of investing its water in agriculture, tourism, electricity generation and others after water scarcity and low level of placements, which led us to study Lake Talker through the use of the model of digital height and topographic maps to reach the possibility of improving this model to reach an academic study that can be used in other scientific fields Lake Al-Tharthar is located 120 km northwest of Baghdad between the Tigris and Euphrates rivers, with an area of 2,710 km2. The highest storage level is 65 meters above sea level and the volume of water storage at this level is 85.89 billion m3. The lake is one of the largest natural depressions in Iraq, where it was established in 1956 to store excess water from the Tigris River, so that adequate amounts of irrigation water can be returned to the two rivers whenever needed.1 Lakes and dams have been established and developed mainly to avoid floods that feed Iraq's rivers from time to time. Two methods of completion were thus used: the Radail Basin Function method and the Empirical Bayesian Kriging and we were able to note that the Payson Road is the best in spatial fulfilment to reach the representation of the 3D shape of the lake. Based on the above, the research has reached a number of results, namely, the possibility of developing improved digital altitude models for different regions of Iraq with local specifications that form the basis of similar studies and research.

Optimal sowing times and irrigation schedule of the chickpea (Cicer Arietinum L.) in semi-arid regions

The purpose of this study was to determine the effects of different sowing times and irrigation schedules on seed yield and water use of chickpea in Central Anatolia's semi-arid conditions. For two years, field trials were conducted using a split-block trial design with three replications. The study addressed two sowing times as well as five irrigation treatments. While the effect of sowing time on grain yield varied by year, the effect of irrigation on grain yield was significant for both sowing times. At both sowing times, the three irrigation treatments (flowering, pod set, and pod filling) produced the highest grain yield. The efficiency of water use was higher in late sowing than in early sowing. While plant water consumption increased during the early sowing period, the amount of irrigation water decreased. The seasonal yield response factor early sowing, on the other hand, was lower than in late sowing.

Determination of irrigation water quantity and its impact on crop yield and groundwater

The objective of reservoir water allocation based on considering the ecological water demand of the downstream river has an important impact on the water allocation of each water user and the downstream ecology. Agricultural irrigation with large water consumption will directly affect crop yield. Irrigation water, as the recharge of groundwater in irrigation districts, also plays an important role in the restoration of groundwater. This research used the range of variability approach (RVA), a method of flow management considering the water demand of river ecosystems, to provide the recommended outflow range (RVA target) of the Huangbizhuang Reservoir upstream of the Shijin irrigation district. First, we used the RVA target to determine the water allocation of each water user, set 27 irrigation schemes with the water allocation of agriculture as a constraint, and used the validated AquaCrop model (seven years of field experiment data were used to calibrate AquaCrop model parameters) to evaluate the most appropriate irrigation schemes and their impact on groundwater restoration in the irrigation district. The results showed that the amount of water available for agricultural irrigation in the flood season under the RVA target was 84 mm, which was 36 mm less than the current irrigation quota (120 mm). Three irrigation schemes better than the current scheme (scheme 0) were selected, i.e., scheme 1 (irrigate 42 mm at the seedling and jointing stages), scheme 16 (irrigate 42 mm at the seedling stage), and scheme 22 (irrigate 84 mm at the seedling stage). Scheme 22 increased the yield of corn and WP (water productivity), which were 17 kg/ha and 1 kg/ha/mm higher than scheme 0, respectively, which provided the greatest increase in yield. Scheme 22 can restore 0.727 m of the groundwater table. The yield increased in scheme 16 was 4 kg/ha higher than that in scheme 0. Scheme 16 can restore 0.982 m of the groundwater table, which was the most conducive scheme for groundwater recharge. The WP of scheme 16 and scheme 1 was slightly different from that of scheme 0. There was a slight difference in biomass among the four schemes. The yield increased in scheme 1 was 12 kg/ha higher than that in scheme 0, which could restore 0.727 m of the groundwater table simultaneously, which was for a normal year. This research can provide a reference for the formulation of a local irrigation scheme to stabilize and increase summer maize yield on the premise of satisfying the ecological water demand of the river and restoring the groundwater table.

Exploring the genetic variability for higher water productivity in wheat crop under moisture stress conditions

Wheat is the flagship and staple food crop in India. Cultivation of wheat taking place under assured irrigation facility in India. One of the biggest difficulties faced by wheat farmers in all regions is depletion of ground water resources at an alarming rate. This study was conducted to test the hypothesis that variability with respect to water use efficiency exists in wheat genotypes and the use of higher water use efficient genotypes reduced the amount of irrigation water for harvesting the desirable level of yield. The field experiment was carried out in split plot design during rabi season of 2020-21 under two different moisture levels. Genotype DBW 110 was top ranked for WUE (1.28 kg/M3 &amp; 1.71 kg/M3) at IARI Gauria Karma. Whereas at Karnal centre, genotype 40 ESWYT 33 ranked first with WUE of 2.42 and 3.04 kg/M3 under 80 and 60 % of ET respectively. Identification and deployment of wheat genotypes having higher water use efficiency could be the water saving technology in the water scarce scenario

Effects of Unconventional Water Agricultural Utilization on the Heavy Metals Accumulation in Typical Black Clay Soil around the Metallic Ore

Unconventional water is an important water resource for agricultural utilization in the drought and water shortage of Northeast China. Additionally, exploration in making full use of it is an important way to alleviate water shortage in China. This paper analyzed the effects of unconventional water through field trials on the accumulation of heavy metals in both cucumbers and the typical black clay soil (expressed as black soil) around the Anshan metallic ore. By exploring the effects of unconventional water after secondary treatment on the accumulation characteristics of heavy metals in cucumbers and the heavy metal balance in the soil–crop system under different conditions, the study shows that there are no significant differences in the heavy metal content when the quantity of unconventional water for irrigation varies. Unconventional water for short-term irrigation does not cause pollution to either the soil environment or the crops. Nor will it cause the accumulation of heavy metals, and the index for the heavy metal content is far below the critical value of the trade standard and national standard, which indicates that the crops irrigated with unconventional water during their growth turn out to be free of pollutants. Unconventional water brings less heavy metals into the black soil than crops. The input and output quantities have only small effects on the heavy metal balance in the black soil. This paper provides a reference for the safety control and evaluation of unconventional agricultural utilization.

Optimisation of irrigation strategy in sugar beet farming based on yield, quality and water productivity

Present experiments were conducted to determine the effects of different irrigation levels on yield, yield components and quality of drip-irrigated sugar beet under sub-humid conditions. Field experiments were conducted in the 2019 and 2021 growing seasons in the Bursa province of Turkey. Experiments were carried out in completely randomised blocks design with three replications. Irrigations were scheduled based on the replenishment of 100 (S1), 66 (S2), 33 (S3), and 0% (S4) of soil water depletion within the soil profile of 90 cm using 7-day irrigation intervals. In 2019, root yields varied between 29.32 (S4)–86.31 (S1) t/ha and sugar yields between 6.33–13.57 t/ha. In 2021, root yields varied between 26.18 (S4)–74.56 (S1) t/ha and sugar yields between 6.56–12.53 t/ha. Effects of different irrigation levels on investigated parameters were found to be significant (P &amp;lt; 0.01). The crop water consumption values were significantly related to root and sugar yields (P &amp;lt; 0.01). Based on present findings, S1 treatment was recommended to get the highest root and sugar yields. In case of limited water resources, S2 (33% water shortage) treatment with the highest water productivity and irrigation water productivity values could be recommended to ensure maximum efficiency from the applied irrigation water quantity.

Chlorophyll Response to Water Stress and the Potential of Using Crop Water Stress Index in Sugar Beet Farming.

Field experiments were conducted in 2019 and 2021 growing seasons to evaluate the chlorophyll readings and crop water stress index (CWSI) response to full and deficit irrigation for drip-irrigated sugar beet (Beta vulgaris L.) under sub-humid climate of Bursa, Turkey. In addition, the changes of soil water content under different irrigation treatments and statistical relationships between chlorophyll and CWSI values and ETc, root yield and sugar yield were investigated. Experiments were carried out in a completely randomized blocks design with three replications. Irrigations were scheduled based on the replenishment of 100 (S1), 66 (S2), 33 (S3), and 0% (S4) of soil water depletion within the soil profile of 0–90 cm using 7 day irrigation intervals. Lower and upper baselines obtained by measurements based on the canopy temperature from the treatments full irrigated and non-irrigated were used to calculate CWSI. The variations in CWSI values were consistent with the variations of seasonal soil water contents induced by the different irrigation practices. CWSI values generally varied between 0 and 1 throughout the experimental periods. In 2019, seasonal mean chlorophyll readings varied between 203.3 and 249.1, and mean CWSI values varied between 0.12 and 0.85. In 2021, seasonal mean chlorophyll readings varied between 232.7 and 259.3 and mean CWSI values between 0.19 and 0.89. Unlike chlorophyll values, CWSI decreased with increased irrigation water amount. In both years, statistically significant relationships were determined between chlorophyll readings and CWSI and ETc, root yield and sugar yield. The greatest root yield was achieved with a seasonal mean CWSI value of 0.12. An exponential equation determined as “Root Yield = 10.804e−1,55CWSI” between seasonal average CWSI values and root yield can be used for estimation of root yield in sugar beet farming. The mean CWSI values determined by infrared thermometer technique can be used in determination of crop water stress and irrigation scheduling of sugar beet cultivation under sub-humid climatic conditions.

The importance, methods of land leveling and analysis of equipment for their implementation

It has been proved in the world and our country’s agriculture that the levelling of arable lands helps the land to improve the reclamation of lands and reduce the amount of water for irrigation. According to agro-technical requirements, the height of irregularities on the surface of the fields should not exceed ± 5 cm. Experiments and research show that crop yields decreased by 1.5-1.7 times and irrigation water consumption increased by 1.7-3.4 times when the surface roughness of the fields was ± 10-13 cm. According to the research carried out by E. B. Velichko and B. B. Shumakova, in areas where the height of irregularities reached ± 3 cm, the yield increased by 1.5 times compared to ± 5 cm, and irrigation water decreased by 1.6 times. In areas with such unevenness of ± 2 cm, the yield increased by an additional 19.9 c / ha (47%), the consumption of irrigation water for the production of 1 ton of rice decreased by 36% or 1621 m3 of the economy was achieved.

Determining the plant critical saturated water accumulation curve in maize

Water scarcity is one of the major factors limiting crop growth and productivity. Judicious water management reduces the application of irrigation water and increases grain yield, farm profits, and water use efficiency . The assessment of crop water status is the key to in-season irrigation scheduling . The plant diagnostic approach has the potential to assess the in-season crop water status for optimizing crop water use. For this purpose, a series of field and rainout shelter experiments with varying amounts of irrigation water (0–275 mm for field and 0–315 mm for rainout shelter experiments) and planting densities (6–8 ×10 4 plants ha −1 ) using seven maize cultivars were conducted from the 2017–2020 growing seasons in North China Plain to determine and validate the plant critical saturated water accumulation (SWA) curve during the vegetative growth period of maize. The result showed that the plant dry mass (DM) and the SWA ranged from 0.07 to 8.22 t ha −1 and 0.63–59.06 t ha −1 during the vegetative growth period of maize, respectively. The plant DM and SWA increased with the increase in irrigation amount. However, plant DM and plant SWA showed non-significant differences under non-water-limiting conditions. An allometric relationship between plant DM and plant SWA was used to develop the plant critical SWA curve (SWA = 8.26DM 0.89 , R 2 =0.98 ** ). A plant water diagnosis index (WDI) was then derived using the critical SWA curve to quantitatively assess the in-season water status of maize. The WDI increased with the increase of irrigation amount and ranged from 0.72 to 1.26 with a value of 1, indicating an optimum plant water status. The newly developed curve could diagnose and categorize the water-limiting and non-water-limiting plant water status and can be employed for precision irrigation management during maize cultivation.

Is the Subsurface Drip the Most Sustainable Irrigation System for Almond Orchards in Water-Scarce Areas?

The expansion of irrigated almond orchards in arid and semi-arid areas with scarce water available raises key issues related to the sustainability of the water resources. A 3-year field experiment was conducted on a commercial young almond orchard located in the southeast of Spain to study the effect of two drip irrigation systems (surface, DI and subsurface, SDI) on almond crop growth and their physiological responses under fully-irrigated conditions. Crop evapotranspiration (ETc) and its components (crop transpiration, Tc and soil evaporation, Es) were monitored as well as the irrigation water and nitrogen productivities. To estimate ETc, a simplified two-source energy balance (STSEB) approach was used. Although a lower irrigation water amount was applied in SDI compared to DI (differences between 10% and 13.8%), the almond crop growth and physiological responses as well as the yield components and kernel yield showed no significant differences. The ETc estimates resulted in small differences for spring and fall periods (0.1–0.2 mm day−1) for both treatments, while differences were significant during higher ETo periods (May–August), being 1.0–1.3 mm day−1 higher for the DI treatment than for the SDI treatment. The irrigation water productivity (IWP) was significantly higher in the SDI treatment than in the DI treatment. However, no significant differences between the two treatments were observed for nitrogen productivity. It can be concluded that the SDI system is a suitable strategy for irrigating almond crops, reducing consumptive water use and increasing IWP.

The Effect of Deficit Irrigation on Yield and Quality of Second Crop Sesame (Sesamum indicum L.)

This study was carried out in Bursa, Turkey which has a sub-humid climate, in order to examine the water-yield relationships and responses of yield and quality components under deficit irrigation of second crop sesame plant (Sesamum indicum L.) irrigated with drip irrigation method. Experimental treatments were application of 100% (S1), 75% (S2), 50% (S3), 25% (S4) and 0% (S5) of soil water depleted at effective rooting depth at 7-day intervals. The experiment was applied in 3 replicates according to the completely randomized blocks experimental design. According to the study results, the total amounts of irrigation water applied were between 127.0-354.7 mm. Crop evapotranspiration values varied between 246.0-449.5 mm. Seed yield, oil content and protein content were obtained as between 76.3-189.2 kg da-1, 56.3-62.6% and 18.6-20.4%, respectively. In the study, the seasonal yield response factor (ky) was determined as 1.28. Water use efficiency (WUE) of the sesame plant was found between 0.31-0.43 kg m-3. Irrigation water use efficiency (IWUE) varied between 0.50-0.57 kg m-3. As a result, irrigation treatment S1 can be suggested as an irrigation schedule in order to reach the highest seed yield (189.2 kg da-1) in the second crop sesame plant. When water resources are limited, taking into account the WUE and IWUE values, the S2 treatment (25% water deficit) can be preferred as an irrigation program in terms of water saving.

Effects of subsidy and regulation policy on soil and water resources of cotton planted lands in Harran Plain, Turkey

Cotton (Gossypium hirsutum L.) provides essential raw material used in the textile, feed, and vegetable oil sectors. Therefore, it is a strategic crop for agricultural, economic, and political strategies around the world. Accurate monitoring of the changes in the cotton production patterns is crucial for decision-makers. Turkey is among the top ten cotton producers and ranks fourth in the world for cotton imports. One third of the total cotton production in Turkey comes from the southeastern Anatolia region of the country. This study analyzed the impact of subsidy and regulation policies on fluctuations in cotton production areas and soil and water quality in Harran Plains, southeastern Anatolia region Turkey. Time-series (between 2016 and 2021) satellite images were utilized to determine actual crop rotation in the study area. Turkish Government implemented a new rule for crop subsidies in 2020 which stated that a farmer will be eligible for subsidy for two consecutive years; however the subsidy will not be paid if the same crop is planted in the third year. Cotton was cultivated in 83 % of the Harran plains prior to new subsidy regulation, which decreased to 26 % after the new regulation. Sudden decrease in cotton cultivation area clearly indicated that farmers need public support to cover the costs in agricultural production. The Gross Production Value (BPV) for each crop was calculated to determine the impact of subsidy regulation on economic value of crops in the rotation.The GPV in 2020 was 2.903,7 $ ha−1 that was 33.6 % and 20.5 % lower than 2019 and 2021, respectively. The results indicated that crop subsidies significantly altered the crop selection behavior of farmers. Water requirement of crops in rotation between 2016 and 2021 was calculated to assess the effects of subsidy changes on water consumption. Cotton cultivation over a large part of the plains during the same season caused excessive water consumption, rise in groundwater level over time, soil salinity and severe water erosion. However, cotton cultivation area as well as water consumption in Harran plain new significantly decreased with the new subsidy regulation; therefore, water consumption in 2020 was the lowest among the time frame evaluated. Total sediment losses through surface runoff from the Harran Plain was estimated as 0.83 tons ha−1 per year. The results revealed that subsidies exert significant impacts on the gross production value in the region, amount of irrigation water consumed, and quality of soil and water resources in addition to the impact on the decision of farmers for crop selection.

Effect of Irrigation Scheduling at Different Phonological Phases on Growth and Yield of Mustard (Brassica juncea l.) in Northern Telangana

Optimum crop yield is not possible without the timely application and right amount of irrigation water. Since rainfall during rabi is inadequate and uncertain, scheduling of irrigation during critical stages could boost the growth, yield and water productivity of mustard. So, in order to identify critical stages of irrigation for mustard in Northern Telangana Zone, a field experiment was conducted during rabi, 2021-22 at Agricultural college, Jagtial to investigate the effect of irrigation scheduling at different phenological phases on growth and yield of mustard. The experiment was laid out in randomized complete block design with twelve treatments and replicated thrice. Treatments includes two irrigations each at vegetative and flowering stage (T1), two irrigations each at vegetative and siliqua development (T2), two irrigations each at flowering and siliqua development (T3), three irrigations each at vegetative, flowering and siliqua development (T4), three irrigations each at vegetative, pre-flowering and siliqua development (T5), three irrigations each at pre-flowering, siliqua initiation and siliqua development (T6), four irrigations each at vegetative, pre-flowering, flowering and siliqua development (T7), four irrigations each at vegetative, pre-flowering, flowering and siliqua initiation (T8), four irrigations each at vegetative, pre-flowering, siliqua initiation and siliqua development (T9), four irrigations each at pre-flowering, flowering, siliqua initiation and siliqua development (T10), five irrigations each at vegetative, pre-flowering, flowering, siliqua initiation and siliqua development (T11) and scheduling of irrigation at IW/CPE ratio of 1.0 (T12). The results of the experiment revealed that maximum plant height (146 cm), LAI (0.89), dry matter accumulation (416 g m-2), number of siliquae plant -1 (124), number of filled seeds siliquae-1 (13.65), seed yield (1113 kg ha-1) and stover yield (2224 kg ha-1) were recorded with five irrigations each at vegetative, pre-flowering, flowering, siliqua initiation and siliqua development (T11). However, it was on par with irrigation scheduled at IW/CPE ratio of 1.0 (T12). While, the lowest plant height (102 cm), LAI (0.42), dry matter accumulation (198 g m-2), number of siliquae plant -1 (63), number of filled seeds siliquae-1 (10.43), seed yield (431 kg ha-1) and stover yield (923 kg ha-1) was recorded with scheduling two irrigations at vegetative and siliqua development (T2).

Ertragskomponenten und Wasserstressindex von Mungbohnen bei Defizitbewässerung

This study was conducted in 2018 growing season to determine the response of mung bean to water stress. Effects of different irrigation levels on mung bean yield and yield components and potential use of crop water stress index (CWSI) in mung bean irrigation scheduling were also investigated. Five different irrigation levels (I100, I75, I50, I25 and I0) were applied through drip irrigation system. Amount of irrigation water supplied varied between 20–445 mm. Plant water consumption (ET) values varied between 125–521 mm. The highest yield (163 kg/da) was obtained from full-irrigation (I100) and the lowest yield (39.7 kg/da) was obtained from rain-fed (I0) treatment without irrigations. Plant heights varied between 58.6–21.2 cm, the first pod heights between 17.4–29.3 cm, number of branches per plant between 1.00–2.77 and number of pods per plant between 3.2–18.9. Water use efficiency (WUE) values varied between 0.31–0.50 kg/m3 and irrigation water usage efficiency (IWUE) values varied between 0.37–0.77 kg/m3. Crop water stress index (CWSI) values varied between 0.13–0.93. The lower limit (LL) equation was obtained as Tc-Ta = −2.9674 × VPD + 4.1341 (R2 = 0.66) and the upper limit (UL) was identified as 9.7 °C. Highly significant (p < 0.01) correlations were seen between CWSI and yield. Based on present findings, I75 was recommended under water deficit conditions. CWSI values of between 0.13–0.22 can be used to initiate irrigations for drip-irrigated mung bean.