Different water availability in the economic water productivity in soybean cultivars

ABSTRACT The present work aims to evaluate grain productivity, water productivity, and economic water productivity of three soybean cultivars under supplementary irrigation. Two experiments were conducted during the 2018 and 2019 harvests in Santa Maria/RS, Brazil. The experimental design consisted of a random bifactorial block design with six irrigation depths as the first factor and three soybean cultivars (Glycine max L.) as the second. The irrigation system used was the conventional fixed sprinkler, with a fixed irrigation shift of seven days. Crop productivity, water productivity, and economic water productivity were evaluated. The highest productivity was for 100% of reference evapotranspiration (ETo) in both harvests. Maximum technical efficiency was obtained for depths of 73.03% (Harvest 1) and 77.94% (Harvest 2) of ETo. Both harvests presented higher water productivity and economic water productivity in the 50% and 25% ETo depths respectively. Productivity is increased with irrigation, and the economic water productivity is maximized with reduction of depth.


INTRODUCTION
_______________________________________________ Submitted on October 25 th , 2021 and accepted on May 21 rst , 2022.  1 This work is part of the first author's Doctoral Thesis.
2 Universidade Federal de Santa Maria, Departamento de Engenharia Rural, Santa Maria, Rio Grande do Sul,Brazil. rodrigues.silvana.a@gmail.com;mpeiter@gmail.com;diasrobaina@gmail.com;jhosefe.b@gmail.com;lauradiasferreira14@gmail.com;miguelchaiben@gmail.com *Corresponding author: rodrigues.silvana.a@gmail.comSoybean is the main crop in Brazil's production volume, reaching 124.8 million tons in the 2019/20 harvest with a planted area of 36.9 million hectares (CONAB, 2020).This crop has an important role in the production chain due to its many forms of use, including animal feed, oil, bran, and biodiesel.
Water deficit is the main source of the soybean productivity gap, becoming a significant concern for increasing Brazilian production in current and future climatic conditions (Battisti & Sentelhas, 2017).One of the leading causes for the oscillations in the pluviometric regime is the ENSO phenomenon (El Niño Southern Oscillation), which causes severe problems for Brazilian agriculture, such as floods and droughts, depending on its phase (El Niño or La Niña) (Nóia Júnior & Sentelhas, 2019).
When this pluviometric regime does not meet the crop's total demands, both quantitatively and temporally, it is necessary to use water supplementation as an alternative to seeking greater productivity (Gajić et al., 2018).A major challenge still facing soybean producers is how much and when to irrigate.Therefore, the relationship between crop productivity and irrigation water applied in conjunction with knowledge of the region's pluviometric demands and crop deficits can efficiently answer these questions (Zhang et al., Silvana Antunes Rodrigues et al. 2018).According to Battisti et al. (2018), irrigation increases soybean productivity in different climatic scenarios.
However, many factors define the development, growth, and productive potential of the crop, being influenced by genetic (the type of growth, relative maturity group, and presence of the juvenile gene) and climatic factors (photoperiod, solar radiation, temperature, and water availability) and management (sowing time and soil physicochemical characteristics) (Pires et al., 2005;Zanon et al., 2016).
According to Ribeiro et al. (2017), crop productivity can vary widely depending on the cultivar chosen and the region of study.These authors also state that there is no difference in the soybean yield components for the sowing densities of 300 to 600 thousand plants per hectare.With a lack of answers when comparing soybean cultivars according to water availability, it is important that restrictive factors, such as irrigation, field management, soil, and climate conditions, be considered in addition to selecting the best cultivars in each year of cultivation (Araji et al., 2018).Montoya et al. (2017) report that supplementary irrigation in soybean crops provided an increase in grain productivity, maximizing yield and profit margin.Adeboye et al. (2015) found that irrigation with total water replacement showed a better response when evaluating the economic productivity of water in soybean crops submitted to water deficits at different development stages.Additionally, Tewelde (2019) reports the importance of obtaining economic water productivity to deduct the farmers' gains concerning water consumption.Thus, evaluating irrigation management and its increases in crop yield shows the importance of water productivity in the management of irrigated agriculture (Kirchner et al., 2019).
Management alternatives aimed at higher yields, with correct management of water resources are essential for the soybean production chain.Therefore, the efficiency of water application per crop area makes production sustainable, economical and consequently more profitable.
Given the above, the present work aims to evaluate grain productivity, water productivity, and economic water productivity of three soybean cultivars under supplementary irrigation.

MATERIAL AND METHODS
The with well-defined seasons (Alvares et al., 2013).
According to INMET, the average annual precipitation in the region ranges from 1450 to 1650 mm with an average temperature of 18-20 °C.In this region, the distribution of rainfall during the summer is usually irregular and may not be sufficient to meet the water needs in certain periods of the crop cycle (Nied et al., 2005).The soil of the experimental area is classified as 'Argissolo Vermelho Distrófico Típico' (Santos et al., 2018).
Chemical and physical soil analyzes were performed in the area.The collection of soil samples for chemical soil analysis was conducted according to Arruda et al. (2014).
The samples were analyzed at the Soil Analysis Laboratory of the Universidade Federal de Santa Maria (UFSM), where the macro and micronutrient soil requirements were determined.
Fertilization was performed after chemical analysis in the quantities recommended by the Comissão de Química e Fertilidade do Solo do RS/SC (2016).The physical soil analyzes were performed at the Soil Analysis Laboratory of UFSM (Table 1).
The experiment site's meteorological data were obtained through the National Institute of Meteorology's automatic meteorological station, located at UFSM, situated approximately 2 km of the area.The data collected daily were maximum and minimum temperatures (ºC), relative humidity (%), wind speed (m s -1 ), and solar radiation (kJ m -2 ).Already the precipitation (mm) was collected in the experimental area using rain gauges.
Sowing for Harvests 1 and 2 was done on 12/14/2017 and 11/23/2018.The experimental design consisted of a random bifactorial block design, with four blocks, being six irrigation depths (L factor) and three soybean cultivars (Glycine max L., C factor), totaling 72 experimental units (UE).Each UE has dimensions of 4 x 4 m (16 m 2 ), this area Different water availability in the economic water productivity in soybean cultivars was considered a useful area of 12.25 m 2 .Between each UE there was a space of 4 meters, so that in the application of irrigation there was no overlapping of depths.
Thirty days before sowing, the herbicide glyphosate was applied at a dose of 3 L ha -1 .The fertilization was carried out at sowing, applying 380 kg ha -1 in the commercial formulation 5-20-20, of nitrogen (N), phosphorus (P 2 O 5 ) and potassium (K 2 O).
The three cultivars have an indeterminate growth habit and medium cycle.
A fixed conventional sprinkler irrigation system was used for the irrigation management, consisting of the mainline of 92 meters and 24 lateral lines of 24 meters.The spacing between the lateral lines was 4 m.The sprinklers Agrojet, P5 model, were distributed on the lateral lines with a 4 m spacing and installed on an elevation of 1.5 m in height (Figure 1).Christiansen's Uniformity Coefficient test (CUC) was used to verify the irrigation uniformity and calibrate the system's irrigation rate (mm h -1 ).The irrigation uniformity was 82%, and the system's application rate was 11.5 mm Irrigation was conducted with a fixed shift of seven days between irrigations when there was no precipitation to supply the crop's water demand of the crop in the period and was started soon after its emergence.Irrigation management was based on reference evapotranspiration (ETo), calculated using the Penman-Monteith-FAO equation (Allen et al., 1998).
The need for irrigation was determined according to where NI -is the irrigation requirements (mm), ETo -is the reference evapotranspiration for seven days (mm), and P ef -is the effective precipitation (mm).
Silvana Antunes Rodrigues et al.
According to Millar (1978), the effective precipitation was determined, which considers the parameters of the textural class of the soil, declivity (%), and vegetation cover.
The fraction of precipitation lost by runoff considered was 30% of the total precipitate for the place where the work was conducted.
The irrigation depths were applied for the irrigation times, according to Equation 2: .1 00 .
where IT -is the irrigation time (h); L n -is the required depth (mm); Lr -is the reference depth (mm h -1 ); and U ais the application uniformity (%).
Plants from a 4.5 m² usable area were collected at the end of the crop cycle and subsequently traced, cleaned of impurities, weighed, and the humidity was corrected to 13%.
Water productivity was determined using the methodology described by Adeboye et al. (2015), which consists of relating the total volume of water applied (effective precipitation + water depth) to the total grain production (Equation 3).

Y WP W =
(3) where WP -is the water productivity (kg ha -1 mm -1 ), Y -is the crop productivity (kg ha -1 ), and W -is the total water depth applied during the crop cycle (mm).
Furthermore, the economic productivity of the water was determined through Equation 4. .
where EWP -is the economic water productivity (US$ ha -1 mm -1 ), and p -is the average grain price (US$ kg -1 ), Y -is the crop productivity (kg ha -1 ), and W -is the total water depth applied during the crop cycle (mm).

Soybean commercialization price was determined using
the averages for the state of Rio Grande do Sul in April of 2018 and 2019, following the harvesting, with values of R$ 74.18 and R$ 68.18 per bag, respectively.Prices were converted into dollars and during this period the average quotation was R$ 3.64.
The results were subjected to analysis of variance (ANOVA) at the 5% error probability level using the Sisvar program 5.6.Regression analysis and maximum technical efficiency were performed when there was an interaction between the cultivar factors and irrigation depths.When there was no interaction, the means were compared by the Tukey test for qualitative data (soybean cultivars) and regression analysis and maximum technical efficiency for quantitative data (irrigation depths).The regression analysis was performed using the SigmaPlot 11.0 software.

RESULTS AND DISCUSSION
Figure 2 shows the average maximum and minimum temperatures, effective precipitation, and daily evapotranspiration for Harvests 1 and 2. The average daily air temperature fluctuated between 15 ºC and 32 °C for the studied harvests.There were no significant differences for both the maximum average temperature and the minimum average temperature, considering that the appropriate thermal conditions for the growth and development of soybeans are between 20 and 30 °C (Battisti & Sentelhas, 2014).

The effective precipitation showed approximate values
for both harvest years, with 369.18 mm and 374.55 mm for Harvests 1 and 2, respectively.These values were insufficient to supply the crop requirements, demanding an irrigation input to ensure production.According to Grassini et al. (2015), soybean crops require 450 to 700 mm of water to supply their water needs.For the southern region of Brazil, studies indicate that a water supply of approximately 800 mm (Zanon et al., 2016) and between 765 and 875 mm (Tagliapietra et al., 2021)  During the development of the crop, seven (Harvest 1) and six (Harvest 2) irrigations were required (Figure 3).The irrigations for each treatment of Harvest 1 totaled 30.28, 60.56, 90.84, 121.12, and 151.40 mm for depths of 25%, 50%, 75%, 100%, and 125% of ETo, respectively.The irrigation depths for each treatment of Harvest 2 were 30.17, 60.34, 90.51, 120.68, and 150.85   Different water availability in the economic water productivity in soybean cultivars The analysis of variance showed no interaction between the depth and cultivar factors at the 5% level of significance for the soybean crop productivity.However, the cultivars showed a statistical difference for productivity, water productivity, and economic water productivity in both crops studied (Table 2).Cultivar BMX Valente presented the highest productivity, water productivity, and economic water productivity values in both harvest years, with no significant difference cultivar BMX Ponta, while cultivar NS 6909 showed the lowest results.Santos et al. (2019) found that the cultivars showed a significant difference at the level of 1% error probability for grain production when evaluating the productivity and water productivity of different soybean cultivars, corroborating the results of the present study.
The three cultivars studied responded equally to irrigation, unlike in the study conducted by Gava et al. (2017), who found that some genotypes do not respond to irrigation depending on each cultivar's genetic character-istics when evaluating irrigated and non-irrigated soybean cultivars.
According to Kukal & Irmak (2020), irrigation has become a fundamental agricultural production tool, reducing crops' annual variability due to climatic variations and efficient water resource use.Soybean productivity in both harvests responded positively to the amount of water supplied, showing a very similar behavior in both situations studied (Figure 4).This is in agreement with a study conducted by Montoya et al. (2017) in Salto, Uruguay, where the authors found that the soybean crop development was similar in both years regarding the total crop cycle and accumulated thermal time.report that the highest grain yield was obtained in treatments with total irrigation, presenting an average gain of 50.6% compared to the precipitation treatment.Despite the increase in productivity with the depth of 100% in both harvests, water productivity showed the best values at depths of 50% and 25% with productivity of 15.07 and 14.17 kg ha -1 mm -1 for Harvest 1 and 2, respectively.
Consequently, the highest economic water productivity was obtained on the same irrigation depths (Table 3).
These results are similar with those found by Candogan et al. (2013), who observed the highest water productivity values for 25% of ETc.However, the authors report that this irrigation strategy can cause a 27.5% reduction in grain yield, differing from this study where reduction in the productivity of was 2.78% (Harvest 1) and 9.32% (Harvest 2).This information can facilitate decision-making when choosing the type of irrigation to provide greater water availability for an increase in productivity or smaller depths when there is water scarcity in a reservoir or for water cost savings (Candogan et al., 2013;Çetin & Kara, 2019).

Figure 1 :
Figure 1: Sketch of the experimental area.
are enough to maximize soybean productivity.The evapotranspiration values during the entire crop cycle in Harvests 1 and 2 were 336.60 and 315.76 mm, respectively.Bariviera et al. (2020) obtained evapotranspiration of 267.06 mm and precipitation of 922.28 mm with 62 precipitation events throughout the crop cycle when studying irrigated soybean crops in the 2015/16 harvest, in Mato Grosso state, which justifies the difference in evapotranspiration demand observed in the present study.

Figure 3 :
Figure 3: Precipitation (mm), evapotranspiration (mm), and irrigation depth (mm) accumulated for both crop cycles with an interval of seven days.

Figure 4 :
Figure 4: Average productivity of the soybean crop in function of the irrigation depths of Harvests 1 and 2.

Gava
et al. (2018) observed that supplementary irrigation contributes to higher productivity in intermediate cycle cultivars than in super early cycle cultivars.The three cultivars evaluated in this study are of the intermediate cycle and corroborate that irrigation contributed to the increase in productivity since crop yield increased from the 25% ETo depth.

Table 1 :
Hydro-physical characteristics of the soil in the experimental area

Table 2 :
Crop productivity (kg ha -1 ), water productivity (WP) (kg ha -1 mm -1 ), and economic water productivity (EWP) (US$ ha -1 mm -1 ) in the different soybean cultivars in Harvests 1 and 2 Mean followed by lowercase letters different in the vertical significantly differ at a 5% level of error of probability.**CV = coefficient of variation. * Silvana Antunes Rodrigues et al.