Irrigation management as a strategy to increase yield in dwarf green coconut palms¹

Manejo da irrigação como estratégia para aumento na produtividade no coqueiro-anão-verde

ABSTRACT

The coconut palm (Cocos nucifera L.) is a perennial fruit palm of great global socioeconomic importance. To increase production and mitigate water deficit during the less rainy season, irrigation systems have been expanded across various fruit species, especially coconut palms, which are sensitive to water deficits. This study aimed to evaluate the influence of irrigation depths, based on crop evapotranspiration, on the physical variables of the fruits, fruit yield, and water productivity (in terms of fruits and coconut water) in a commercial coconut plantation in Santa Izabel do Pará, in the state of Pará, Brazil. The experiment was conducted in the municipality of Santa Izabel do Pará (PA), using a randomized block design with six blocks and four treatments corresponding to irrigation depths of 0 (rainfed), 50, 100, and 125% of crop evapotranspiration, with 24 experimental plots. The evaluation was carried out in relation to production variables: fruit mass and fruit water volume. Fruit yield and water productivity were assessed in terms of fruit number and coconut water volume. Statistical analyses were performed at a significance level equivalent to p ≤ 0.05. The variables of fruit production and yield were influenced by irrigation. Irrigation had a positive effect on water productivity in terms of fruit production; however, no differences were observed among treatments for water volume. It is concluded that irrigation is essential to maximize the production and yield of dwarf green coconut, especially in regions with prolonged dry periods.

Key words:
Cocos nucifera L.; evapotranspiration; palm tree; production

HIGHLIGHTS:

Irrigation increases the volume of water in green dwarf coconut fruits.

Plants irrigated produce heavier fruits.

Irrigation rates exceeding 100% of water requirements promote increased fruit yield.

RESUMO

O coqueiro (Cocos nucifera L.) é uma palmeira frutífera perene de grande relevância socioeconômica global. Visando aumentar a produção e mitigar o déficit hídrico no período menos chuvoso, houve expansão da utilização de sistemas de irrigação em diversas espécies frutíferas, especialmente para o coqueiro em virtude da sua sensibilidade à déficits hídricos. O estudo objetivou avaliar a influência de lâminas de irrigação, baseadas na evapotranspiração de cultura, sobre as variáveis físicas dos frutos, a produtividade dos frutos e a produtividade da água (em termos de frutos e água de coco) em um coqueiral comercial em Santa Izabel do Pará, no estado do Pará, Brasil. O experimento foi conduzido no município de Santa Izabel do Pará (PA), sob delineamento em seis blocos casualizados, com quatro tratamentos que corresponderam à aplicação de diferentes lâminas de irrigação (0 (sequeiro), 50, 100 e 125% da evapotranspiração de cultura) e 24 parcelas experimentais. A avaliação foi realizada em relação a variáveis de produção: massa do fruto e volume de água do fruto; produtividade de frutos e produtividade da água em termos de frutos e água. As análises estatísticas foram realizadas ao nível de significância equivalente a p ≤ 0,05. As variáveis de produção e produtividade de frutos foram influenciadas pela irrigação. A irrigação proporcionou efeito positivo para a produtividade da água em termos de frutos, contudo não diferiu entre os tratamentos para o volume de água. Conclui-se que a irrigação é essencial para maximizar a produção e a produtividade de coco-anão-verde, especialmente em regiões com períodos de seca prolongada.

Palavras-chave:
Cocos nucifera L.; evapotranspiração; palmeira; produção

INTRODUCTION

The coconut palm (Cocos nucifera L.) is a fruit-bearing palm tree with a diverse supply chain and byproducts of high global socioeconomic importance (Arifin, 2022; Prasath et al., 2024; Thai et al., 2024). Brazil stands out among the major tropical regions for its investment in coconut cultivation. Nationally, the Northeast region leads coconut production with over 1.7 million tons, but the North region has shown resilience, remaining the third-largest producer with production equivalent to 181,000 tons (IBGE, 2024).

Research indicates that ideal microclimatic conditions for coconut cultivation should include an average temperature ranging from 22 to 34 °C (with an annual average of 27 °C), a minimum relative humidity of the air of 60%, and approximately 2,000 hours of sunlight per year (Sivakumar et al., 2021; Nery et al., 2025). This fruit tree requires 100-240 L of water per plant per day, but can require up to 350 L per plant per day (Miranda et al., 2019; Medeiros et al., 2025). Furthermore, among the meteorological factors for establishing plantations, precipitation is considered one of the most significant, since approximately 1,500 mm per year is required, with rainfall well distributed and a dry season not exceeding three months (Passos et al., 2018).

The high and constant water requirements of the coconut tree are extremely important for decision-making in water management in Amazonian coconut groves, since most regions experience a marked seasonality of precipitation in the second half of the year, which becomes one of the main bottlenecks in production (Carvalho, 2024a,b). It is worth noting that severe water deficit stress can affect several factors, including decreases in leaf water potential, spathe abortion, and a massive fall of immature fruits (Gomes et al., 2010; Araújo et al., 2022). This water shortage also extends beyond physiological damage, as it compromises fruit yield and directly threatens the economic viability of the activity and the strategic positioning of the Northern Region as a relevant production hub in the national scenario. Therefore, water management has become a determining factor for vegetative growth, development, and final orchard yield (Maheswarappa & Krishnakumar, 2019).

Considering the characteristics of the coconut palm, as well as its soil and climate requirements, and the imminent scenario of climate change, irrigation technology emerges as the main tool for mitigating seasonal water deficit in Amazonian crops (Mantovani et al., 2009; Fito & van Hulle, 2021; Li et al., 2024). Therefore, determining the ideal water depth is crucial, with crop evapotranspiration (ETc) and the crop coefficient (Kc) as key parameters that enable precise quantification of the plant’s water needs and ensure maximum water-use efficiency (Allen et al., 1998).

Studies on the ETc of coconut palms indicate values ranging from 2.3 to 5.5 mm per day in Kerala, India (Rao, 1989), with an average of 3.3 mm per day, also in India (Jayakumar et al., 1987). In Brazil, Azevedo et al. (2006) recorded a maximum ETc of 7.7 mm per day when testing increasing irrigation rates. In the context of the North region, within the State of Pará, the work of Carvalho et al. (2024a) determined an ETc of 4.18 mm per day and a crop coefficient (Kc) of 1.1 for the green dwarf coconut palm during the less rainy season in Santa Izabel do Pará.

In this context, the study aimed to evaluate the influence of different irrigation depths, based on ETc, on the physical variables of the fruits, fruit yield, and water productivity (in terms of fruits and coconut water) in a commercial dwarf green coconut orchard in Santa Izabel do Pará, Brazil.

MATERIAL AND METHODS

The experiment was conducted at Fazenda Reunidas Sococo, in Santa Izabel do Pará, in the state of Pará, Brazil (01° 13’ 40.16” S, 48° 02’ 54.35” W, and an altitude of 24 m), in a commercial dwarf green coconut plantation (7 hectares), from August 2023 to May 2025. The randomized block design was used with four treatments (0 (rainfed), 50, 100, and 125% ETc) and six blocks.

At the beginning of the experiment, the plants were 7 years old, with an average height of 7.3 m and a canopy area equivalent to 45.16 m². Planting spacing was 7.5 × 7.5 × 7.5 m in an equilateral triangle, with a density of 205 plants ha⁻¹. The cultivar Anão-verde-do-brasil-de-jiqui (AveBrJ) was used. The soil had a green cover consisting of the perennial herbaceous legume species Pueraria phaseoloides, commonly known as pueraria. The climate of the region is characterized as humid tropical (climate subtype “Am”), according to the Koppen-Geiger climate classification, with a rainy season from December to June, and a less rainy season from July to November. The region has an average annual air temperature of approximately 26 °C, a relative humidity of the air of approximately 80%, and annual rainfall exceeding 2,000 mm (Alvares et al., 2013).

The soil in the area was classified as Quartzarenic Neosol (EMBRAPA, 2018) or Entisol, based on Soil Survey Staff (2022), with a sandy-loam texture, as shown in Table 1. Soil samples were collected in a zigzag pattern in the 0-20 and 20-40 cm soil layers. The soil was collected from the crown area of the plants, totaling 20 individual samples per plot to obtain a composite sample.

Table 1
Chemical and physical characteristics of the soil used in the experiment

Characterization Parameters	Soil layer (cm)
	0-20	20-40
pH (CaCl2)	4.43	4.10
Organic Matter (g kg-1)	8.75	3.25
Organic Carbon (g kg-1)	5.00	2.00
P (mg kg-1)	11.92	7.05
Ca+2 (cmolc kg-1)	1.07	0.40
Mg+2 (cmolc kg-1)	0.55	0.23
K+ (cmolc kg-1)	0.21	0.09
H+ + Al+3 (cmolc kg-1)	3.37	3.27
CEC (cmolc kg-1)	5.25	4.01
Base Saturation (%)	34.85	17.95
Al Saturation (%)	6.48	31.76
Sand (dag kg--1)	70.00	68.00
Silt (dag kg-1)	12.00	19.00
Clay (dag kg-1)	18.00	13.00
Field Capacity (m3 m-3)	0.195	0.195
Permanent Wilting Point (m3 m-3)	0.098	0.100

Plant nutritional management was carried out twice a year (at the beginning and end of the rainy season) with 3.3 kg of NPK formulation (10-07-20 + 1.0% Mg + 5.5% S + 3.5% Ca + 0.10% B + 0.11% Mn). During the experimental period, all management procedures adopted by the company were maintained: weeding, pest, and disease control.

A microsprinkler irrigation system was used, with one emitter per plant. The emitters were self-compensating, with a flow rate of 96 L h^-1, positioned 1 m from the base of the coconut stems. Christiansen’s Uniformity Coefficient (CUC) and application efficiency (AE) tests were performed (Criddle et al., 1956; Fernando et al., 2024), resulting in a uniformity coefficient of 96%, and application efficiency of 86%, a wetted diameter of 3 m, and a wetted surface area of 60%.

Irrigation was managed using a climate-based method, based on crop evapotranspiration (ETc) (Eq. 1), obtained from data from a nearby meteorological station in a grassy area, using the equation parameterized by Allen et al. (1998) (Eq. 2), described in FAO (Food and Agriculture Organization of the United Nations) Bulletin no. 56 on irrigation and drainage, and together with the crop coefficient (Kc) equivalent to 1.1 (Carvalho, 2024a). Irrigation depths were applied during the region’s least rainy period, with the system activated daily and operating time calculated to replenish the ETc depth from the previous day.

(1) $${\mathrm{ET}}_{\mathrm{c}}={\mathrm{ET}}_0\times \mathrm{Kc}$$

(2) $${\mathrm{ET}}_0=\frac{0.408\times \mathrm{\Delta }\times (\mathrm{Rn}-\mathrm{G})+\frac{\gamma \times 900\times {\mathrm{U}}_2\times (\text{es-ea})}{\mathrm{Tar}+273}}{\mathrm{\Delta }+\gamma \times (1+0.34\times {\mathrm{U}}_2)}$$

Where:

ET_c - crop evapotranspiration (mm per day);

ET₀ - reference evapotranspiration (mm per day);

Kc - crop coefficient (dimensionless);

∆ - slope of the vapor pressure versus temperature curve (kPa °C^-1);

Rn - daily net radiation (MJ m² per day);

G - total daily soil heat flux (MJ m² per day);

γpsychrometric coefficient (kPa °C^-1);

U₂ - average wind speed at 2 m height (m s^-1);

es - saturation vapor pressure (kPa);

ea - current vapor pressure (kPa); and,

Tar - average air temperature (°C).

A 12-m-high metal tower was installed and instrumented with the sensors shown in Table 2, meeting the minimum boundary requirements and with a ratio greater than 1:100 to avoid the influence of advection and ensure the representativeness of measurements in the study area. The sensors were connected to two data acquisition and storage systems (Datalogger CR1000 and CR10X, Campbell Scientific, Inc., Logan, UT, USA) and to a multiplexer (AM416, Campbell Scientific, Inc., Logan, UT, USA) programmed to take instantaneous readings every 30 seconds and record averages and totals every 20 min.

Table 2
Instrumentation of the micrometeorological tower installed in the experimental area

Meteorological variable	Instrument/Manufacturer/Model	Sensor Level (m)
Incoming global radiation	Pyranometer (CMP3. Campbell Scientific Instrument. Logan, UT, USA)	0.4 above the canopy
Wind speed	Anemometer (05106. Campbell Scientific Instrument. Logan, UT, USA)	2.2 above the canopy
Precipitation	Rain gauge (TB4. Campbell Scientific Instrument. Logan, UT, USA)	2.3 above the canopy
Air temperature	Thermohygrometer (MeteoTemp, Barani Design Technologies, USA)	0.7 and 2.1 above the canopy
Relative humidity of the air	Thermohygrometer (MeteoTemp, Barani Design Technologies, USA)	0.7 and 2.1 above the canopy

To analyze the physical variables, the fruits were collected from cluster 20 (approximately 210 days after inflorescence opening). Evaluations were performed every 21 days, with two fruits from each cluster from two plants in each experimental block. These fruits were transported to the laboratory for subsequent measurement of the following variables:

a) Fruit weight (FW): measured using a digital scale with 0.01 g precision;

b) Fruit water volume (FWV): measured using an aluminum auger and a beaker to extract the water, which was later measured in mL using a graduated cylinder.

To analyze fruit yield, the number of fruits per plant in each treatment plot within each experimental block was counted. Water productivity (WP), in terms of fruit (WPf) and coconut water volume (WPv), was calculated for the entire experimental period following the methodology described by Miranda et al. (2019) and Frizzone & Melo (2021), as outlined in Eqs. 3 and 4, respectively.

(3) $${\mathrm{WP}}_{\mathrm{f}}=\frac{\mathrm{Yf}}{\mathrm{Wd}}$$

(4) $${\mathrm{WP}}_{\mathrm{v}}=\frac{\mathrm{Pv}}{\mathrm{Wd}}$$

Where:

Yf - fruit yield (fruits ha^-1);

Pv - coconut water productivity (L ha^-1); and,

Wd - accumulated water depth (irrigation + precipitation) (mm).

All statistical analyses and graphs were performed in the R Studio environment of the R software (version 4.5.1, R Core Team, 2025). The significance level adopted for all tests was α = 0.05. For variables that did not meet the assumptions of normality and homogeneity of variances, as assessed by the Shapiro-Wilk and Breusch-Pagan tests, respectively, the most appropriate data transformation was determined using the Box-Cox analysis (Box & Cox, 1964; Shapiro & Wilk, 1965; Breusch & Pagan, 1979). The statistical procedures are detailed below.

The analysis of the physical variables - fruit weight (g) (FW) and fruit water volume (mL) (FWV) - was conducted using an Analysis of covariance (ANCOVA) using a Linear Mixed Model (LMM) (Montgomery, 2019). Cumulative rainfall (mm), calculated retroactively for each harvest date, was incorporated into the model as a covariate to represent the influence of rainfall throughout the cycle. The significance of fixed effects was determined by analysis of variance (ANOVA) with the Satterthwaite approximation (Satterthwaite, 1946; Kuznetsova et al., 2017).

To investigate the temporal dynamics of the treatments, a secondary multiple-comparison analysis was performed using a sliding window, with an LMM fitted for each harvest date. The mean marginal estimates (MMEs) were compared across all treatment pairs using Tukey’s test to identify periods of significant difference. Finally, the overall effect of treatments over the entire period was assessed using ANOVA in a randomized block design, with means compared using Tukey’s test and experimental precision measured by the coefficient of variation.

As with physical variables, the temporal dynamics of the effects of irrigation depth on yield were investigated using a sliding-window multiple-comparison analysis. For each harvest date, the data were fitted to an LMM, and the MMEs between treatment pairs were compared using Tukey’s test to identify periods with significant differences (Tukey, 1949; Searle et al., 1980; Lenth, 2024). The cumulative effect of treatments on total yield was then analyzed using ANOVA, with irrigation depth as a fixed effect and block as a random effect and means compared using Tukey’s test. Experimental precision was assessed using the coefficient of variation.

The effects of treatments on water productivity were analyzed cumulatively across the entire experiment. A randomized block design was used to control spatial variability. Treatment means were then compared using Tukey’s test, and experimental precision was assessed using the coefficient of variation.

RESULTS AND DISCUSSION

During the experimental period, meteorological conditions differed between the less rainy (dry) and rainy seasons. Global solar radiation (Rg) remained similar between the periods, averaging 15.2 MJ m⁻² per day in the drier season and 15.1 MJ m⁻² per day in the rainy season. The average air temperature (Tar) was 27.6 °C in the dry season and 26.6 °C in the rainy season, remaining within the ideal range for coconut palms (an overall average of 27.0 °C) and without imposing thermal limitations on the crop (Figure 1A).

Figure 1
Monthly meteorological monitoring for the experimental period (08/2023 - 05/2025) in the study area. Global solar radiation (Rg), air temperature (Tar), and relative humidity of the air (A); vapor pressure deficit (DPV), wind speed (U2), reference evapotranspiration (ET₀), and crop evapotranspiration (ETc) (B); rainfall (C), and gross irrigation water depths (D)

The most significant differences were observed in the variables that govern atmospheric demand. During the less rainy season, relative humidity of the air (RH) was lower (85.33%) (Figure 1A), and wind speed (U₂) was 63% higher (1.24 m s⁻¹) compared to the rainy season (RH = 94.68%; U₂ = 0.76 m s⁻¹). Consequently, the vapor pressure deficit (VPD) was almost three times greater in the dry season (0.55 kPa) compared to the rainy season (0.19 kPa) (Figure 1B).

The greater atmospheric demand during the less rainy season, as evidenced by the VPD, resulted in significantly higher reference (ET₀) and crop (ETc) evapotranspiration rates, averaging 3.35 and 3.69 mm per day, respectively. During the rainy season, these values dropped to 2.28 and 2.51 mm per day (Figure 1B).

The study was marked by the influence of a moderate-to-strong El Niño event (June 2023 to June 2024), which intensified the drought in northern Brazil. Thus, the total accumulated precipitation throughout the study was 3,372 mm, with an irregular distribution that culminated in extreme events, such as a minimum of 4.0 mm in November 2024, highlighting the impact of the phenomenon on local water conditions (Figure 1C). With two well-defined periods of rainfall and water deficit, the region is historically characterized by a minimum rainfall of 40 mm in October (INMET, 2025).

Considering the above, this means that in 2024, the month with the minimum rainfall represented only 10% of the historical rainfall, characterizing an extreme event. The gross depths applied in each treatment are shown in Figure 1D and were equivalent to 591, 1.191, and 1.522 mm for the 50, 100, and 125% ETc treatments, respectively.

Analysis of the wind roses (Figure 2) indicated distinct patterns between the periods. During the rainy season, wind direction was more evenly distributed (predominantly between 22.5° and 135°), with a high prevalence of calm winds (≤ 0.5 m s⁻¹), accounting for 58.23% of the occurrences. In contrast, during the less rainy season, the wind direction was more concentrated (22.5 to 112.5°), with a lower percentage of calm winds (38.48%) and a higher frequency of winds exceeding 3.0 m s⁻¹. Despite differences in distribution and intensity, the resulting vector pointed predominantly to the northeast for both periods.

Figure 2
Wind rose graphs for the rainy (A) and less rainy (B) seasons

Analysis of covariance (ANCOVA) revealed a significant interaction between irrigation depths and accumulated rainfall for all physical variables of the fruit analyzed (Table 3). The model predictions demonstrate that the response to irrigation is strongly dependent on rainfall levels (Figure 3). The effect of irrigation is most pronounced in low rainfall scenarios and progressively decreases with increasing rainfall availability, a pattern consistent with fruit weight (FW) and fruit water volume (FWV).

Table 3
Summary of analysis of covariance (ANCOVA) for the effects of irrigation depths and accumulated precipitation on the physical variables of fruit weight (FW) and fruit water volume (FWV) of green dwarf coconut fruits

Source of Variation	Degrees of Freedom	Mean Squares
		FW	FWV
Depths	3	2.94	10.87
Accumulated precipitation	1	21.04	51.86
Depth: Accumulated precipitation	3	1.81	7.56
Variation Components
Residuals		97.70%	96.50%
Between blocks		0.00%	1.80%
Between plants		2.30%	1.70%
Marginal R2		0.24	0.24
Conditional R2	0.25	0.27

Figure 3
Relationship between accumulated precipitation during fruit development and the physical variables of the fruits: fruit weight (A) and fruit water volume (B) of coconuts under different irrigation depths

In the accumulated rainfall range of 400-1200 mm, a clear contrast is observed between treatments. The model predictions (Figure 3) indicate that higher irrigation depths, especially 125% ETc, yield superior physical variables, whereas the rainfed treatment shows the lowest performance. However, as precipitation increases beyond this range, predictions across all treatments converge, eliminating differences due to soil water replenishment from rainfall.

The temporal evolution graphs of the physical variables (Figures 4A and B) demonstrate that the irrigated treatments maintained their value. In contrast, the rainfed treatment showed a reduction in variable values after the less rainy period. This observed behavior is consistent with other studies, which indicate that water deficit in coconut trees reduces the size and water volume of the fruits, an effect that can persist for a long period (Passos et al., 2018). Water supplementation via irrigation is therefore essential to mitigate stress and avoid compromising production.

Figure 4
Evolution of the physical variables of the fruit: fruit weight (A) and fruit water volume (B) of coconuts under different irrigation depths throughout the experimental period

Analysis of the temporal dynamics of the treatments (Figure 5) reveals the moments at which irrigation significantly affected the physical variables of the fruit. It was observed that all irrigated treatments, at some point, outperformed the rainfed treatment, although the response time varied between the water depths and variables. For fruit weight (Figure 5A), the effects of the 100 and 125% ETc irrigation depths were observed more quickly than those of the 50% ETc irrigation depth. For water volume (Figure 5B), the response patterns also varied.

Figure 5
Temporal dynamics of the estimated differences between irrigation depths under the physical variables of the fruit: fruit weight (A), and fruit water volume (B), and the multiple comparison between the respective treatments

In general, the 125% ETc treatment stood out for providing the fastest positive effect across all variables analyzed and for promoting greater stabilization of values over time. This result highlights the superiority of this water depth compared to the rainfed management currently used by the company. In line with the results, the literature reports that irrigation promotes immediate physiological improvements in plants, such as maintaining leaf water potential and increasing stomatal conductance. These factors overcome metabolic limitations to photosynthesis and ensure a continuous supply of photoassimilates, thereby positively influencing the physical variables of coconut fruits, such as weight and coconut water (Maheswarappa & Krishnakumar, 2019; Carvalho et al., 2024b).

Although irrigation during dry periods boosts fruit production and physical variables, the response is considerably slower in plants already stressed by previous droughts. Recovery of indicators such as fruit water volume and biomass occurs gradually, and full recovery can take a long time. ranging from a few months to up to three years (Nainanayake et al., 1989; Rajagopal et al., 1989; Carr, 2011).

Thus, the dynamics of production recovery are inherent to the long reproductive development cycle of the green dwarf coconut palm. Furthermore, it is strongly dependent on the irrigation strategy adopted, including the frequency and volume of water application, which must be carefully adapted to local conditions, such as soil type and general agronomic management of the area (Surendran et al., 2019). Table 4 demonstrates a significant effect of irrigation depth and presents the results of the Tukey multiple-comparison of means test.

Table 4
Summary of analysis of variance (ANOVA), Tukey’s multiple comparison test of means and standard deviation for the effects of irrigation depths on the physical variables of green dwarf coconut fruits: fruit weight (FW) and fruit water volume (FWV)

Source of variation	Degrees of freedom	Mean squares
		FW	FWV
Treatment	3	46.66	1.8
Block	5	9.3	1.03
Residual	15	7.03	4.07
Treatment		Averages
		FW	FWV
Rainfed		1.845.13 (± 94.69) b	271.30 (± 18.64) b
50% ETc		1,973.61 (± 81.05) ab	296.17 (± 27.66) ab
100% ETc		2,008.98 (± 85.08) a	301.40 (± 23.91) ab
125% ETc		2,064.69 (± 87.24) a	312.22 (± 23.76) a
Coefficient of variation (%)		4.24	6.83

The results indicate superiority of irrigation over rainfed management, with emphasis on irrigation at 100 and 125% ETc. Both treatments showed the best results, with increases of 8.9 and 11.9% in fruit weight (FW) and 11.1 and 15.1% in fruit water volume (FWV), respectively. In general, the results obtained for the analyzed variables were statistically similar for all irrigated treatments, with differences only observed when compared to the rainfed treatment.

These findings are consistent with literature. Studies such as those by Camboim Neto & Ramos (2022) also reported a positive influence of increased irrigation depth on fruit weight and water volume. Additionally, the study by Fernandes et al. (2024) corroborates the idea that irrigation provides stability, preventing reductions in fruit weight and, consequently, increasing water volume compared to rainfed plants.

Figure 6 illustrates the evolution of fruit yield (fruits ha^-1) over the experimental period for the different irrigation treatments, and Figure 7 addresses the dynamics of the temporal effect of different irrigation depths on yield. A decline in yield for the rainfed treatment was observed during the less rainy period, when irrigation depths were applied.

Figure 6
Evolution of fruit yield (fruits ha^-1) of coconut throughout the experimental period

Figure 7
Temporal dynamics of the estimated differences between irrigation depths on the fruit yield of coconut plants

The analysis of the temporal dynamics of fruit yield (Figure 7) reveals that the 100 and 125% ETc levels had a more significant effect, occurring more quickly than the 50% ETc level, compared to the rainfed treatment. The higher levels showed an impact after the first irrigation period or within three months.

In comparisons between the irrigated treatments, 100 and 125% ETc levels also proved superior to the 50% ETc level by approximately three months (Figure 7). After this initial period of differentiation, the effects stabilized, a phenomenon attributed to both the general physiological recovery of the plants and the second irrigation event immediately after the rainy season.

The effects of irrigation depth on cumulative fruit production throughout the experimental period are shown in Table 5, which demonstrates a significant effect of the treatments and presents the results of the Tukey test.

Table 5
Summary of analysis of variance (ANOVA), Tukey’s multiple comparison test of means, and standard deviation for the effects of irrigation depths on the fruit yield accumulated throughout the experimental period

Source of variation	Degrees of freedom	Mean squares
Treatment	3	0.10*
Block	5	0.03
Residual	15	0.01
Treatment	Average accumulated fruit yield (fruits ha-1)
Rainfed	33,291 (± 3,339) b
50% ETc	37,276 (± 5,494) ab
100% ETc	40,744 (± 5,777) a
125% ETc	43,994 (± 5,678) a

The cumulative yield analysis demonstrated the superiority of the irrigated treatments. The 100 and 125% ETc irrigation depths, although statistically similar, showed yield increases of 22.4 and 32.1%, respectively, compared with the rainfed treatment.

Although there was no significant difference between the treatments (100 and 125% ETc), a 7.9% superiority in fruit yield was observed under the 125% ETc irrigation regime, equivalent to more than 3,200 fruits per hectare. This positive difference from a productive standpoint should also be analyzed from an economic point of view, since changes in irrigation management can be decisive for the producer’s profitability and business continuity, due to the need for investment and changes in existing irrigation systems to more intensive structures, in addition to water and energy costs and the return on investment time.

This result can be attributed to the better recovery of the water status of the irrigated plants. This condition likely conferred greater capacity to sustain fruit development during the drought, resulting in less abortion and, consequently, higher yield. This conclusion is supported by the literature, such as that of Ollagnier & Ochs (1978), who state that the yield potential of the coconut tree is reached only when the applied water depth is equal to or greater than the maximum evapotranspiration of the crop.

The analysis of the effects of irrigation depths on water productivity (WP), both in terms of fruit yield (WPf) and coconut water volume (WPv), can be seen in Table 6, which demonstrates that the treatments only had an effect on WPf. Table 6 also presents a comparison of the results using Tukey’s test.

Table 6
Summary of analysis of variance (ANOVA), Tukey’s multiple comparison test of means, and standard deviation for the effects of irrigation depths for water productivity (WP) in terms of fruit yield (WPf) and coconut water volume (WPv) in one hectare of green dwarf coconut

Source of variation	Degrees of freedom	Mean squares
		WPf	WPv
Treatment	3	0.01*	0.28
Block	5	0.09	0.07
Residual	15	0.003	0.03
Treatment		Averages
		WPf (fruits ha-1 mm-1)	WPv (L ha-1 mm-1)
Rainfed		1.62 (± 0.29) a	0.37 (± 0.07) a
50% ETc		1.34 (± 0.19) ab	0.39 (± 0.08) a
100% ETc		1.17 (± 0.17) b	0.36 (± 0.07) a
125% ETc		1.16 (± 0.14) b	0.36 (± 0.06) a
Coefficient of variation (%)		15.88	13.93

The analysis of WP, detailed in Table 6, revealed distinct behaviors for each indicator evaluated. For WPf, the irrigation depths of 100 and 125% ETc were significantly lower than the rainfed treatment. However, they did not differ statistically. The 50% ETc depth, in turn, showed no significant difference compared to the rainfed treatment. Conversely, productivity, measured as WPv, did not differ significantly among treatments, indicating that this index remained stable.

In agronomic terms, water use efficiency is the ratio of crop yield to the water used, and it can vary with factors such as irrigation management, DPV conditions, and plant nutritional status. In the present study, the stability of WPv suggests that the plants showed a physiological adjustment proportional to the volume of water supplied, with lower water production in plants with lower water availability; however, the conversion rate per unit of water was maintained through stomatal conductance control. The observations made by Azevedo et al. (2006) corroborate this information, since the authors report that the direct impact of increased water supply through irrigation occurs mainly in the number of fruits and size rather than in the formation of coconut water.

The results for WPf indicate an inverse relationship between water productivity (fruit per unit of irrigation water) and irrigation water volume, corroborating the studies by Tolk & Howell (2003) and Leite et al. (2013). Under the conditions observed in this study, plants exposed to the highest irrigation depths may exhibit luxury consumption, characterized by sustained increases in stomatal conductance and transpiration over time, without corresponding gains in CO₂ uptake (Hatfield et al., 2001; Hatfield & Dold, 2019). Conversely, treatments with lower water supply optimize the conversion of water into biomass, mainly through physiological adjustments that increase water productivity, as discussed by Gomes & Prado (2007).

CONCLUSIONS

• 1. Irrigation is essential to maximize yield and production-related variables of dwarf green coconut in regions with prolonged drought, increasing fruit weight and coconut water volume compared with non-irrigated plants.

• 2. Irrigation depths of 100 and 125% ETc are effective in improving fruit physical traits and fruit yield.

• 3. Crop water-use efficiency responds differently to irrigation depth, altering productivity per fruit, while remaining stable in productivity per volume of coconut water produced.

• 4. When irrigation exceeds crop water requirements, the management goal should prioritize increasing fruit yield, as this tends to increase fruit weight, which is positively related to coconut water volume.

• 5. From an economic perspective, increasing irrigation depth is viable until total costs (fixed and variable) equal the marginal revenue generated by the additional fruit production.

• 6. Irrigation levels above crop water requirements can enhance production security under adverse conditions or extreme events, such as high temperatures and rainfall deficits.

• 1
  Research developed at Fazenda Reunidas Sococo, Santa Izabel do Pará, PA, Brazil.
• Financing statement:
  Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) - Grant of a Doctoral scholarship to the author Fernandes. G. S. T. (Edital n° 12/2020. process 154794/2021-0); Productivity grant for the author Souza. P. J. de O. P. de (Edital n° 09/2022. process 311681/2022-0), and research funding through the Universal project (process 403902/2021-5). Fundação Amazônia de Amparo a Estudos e Pesquisas (FAPESPA/CNPq) - (Call project 008/2022. process 2023/158057). Sococo Agroindústria da Amazônia S/A.
• Ref. 300093

Data Availability Statement:

The authors declare that there are no supplementary data.

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Edited by

• Editors:
  Toshik Iarley da Silva & Hans Raj Gheyi

Publication Dates

• Publication in this collection
  03 Aug 2026
• Date of issue
  2026

History

• Received
  22 Aug 2025
• Accepted
  12 Apr 2026
• Published
  20 July 2026