Effects of Microdose Fertilizers and Irrigation Depth on Onion ( Allium cepa L. ) Growth Under Drip Irrigation in Northern Ethiopia

Abstract

The variables that most significantly affect bulb yield in Ethiopia’s irrigated agricultural onion production systems are the amount of irrigation water and the irrigated fertilizer application rates. North Ethiopia has gradually adopted drip irrigation for onion farming due to significant water savings and improved water and fertilizer use efficiencies. However, the optimal irrigation water (I) and fertilizer application rates (F) for drip irrigation are still unknown; field experiments using a random complete block design in factorial arrangement were conducted during summer season of 2019/2020 and 2020/2021 to explore the effects of irrigation water and fertilizer application rates on onion production and productivity. The trials were carried out at four recommended microdose fertilizer rates for nitrogen (N) and phosphorus (P₂O₅; F₁-125%, F₂-100%, F₃-75%, and F₄-50%) and three different irrigation water levels (I₁-100%, I₂-75%, and I₃-50%). The interaction effect of water amount and microdose fertilizer application rate significantly (p ⩽ .05) affected onion yield, yield-related components, and water productivity. A combined analysis of variance using SAS software 9.0 revealed that the interaction between irrigation depth and fertilizer rate had a significant (p ⩽ .05) impact on yield, yield-related components, and water productivity. Onion production and water use efficiency (WUE) increased significantly with increasing irrigation water and microdose fertilizer application rates. However, irrigation water less than 100% were not beneficial to the above parameters. In the two-season study, a maximum onion yield of 39.22 t ha⁻¹ was obtained at F₁I₁, with a WUE of 8.20 kg m⁻³. All the factors related to growth, yield, and yield-related components, the combination of a microdosing fertilizer application of 172.5 N and 86.25 P₂O₅ kg ha⁻¹ and 100% water per irrigation was the best drip irrigation pattern for onion. These findings provide a scientific basis for drip irrigation and microdosing fertilizer management of onions in northern Ethiopia.

Keywords

Fertilizer rate irrigation depth drip irrigation onion yield water productivity

Introduction

Onions are among the most important cash crops grown by small-scale farmers, for increasing their income and consequently improving their standard of living (Dessalegn & Aklilu, 2003). Onions are commonly used as seasoning to enhance the flavor of dishes (Enchalew et al., 2016). Most spicy dishes contain onions as important elements (Halvorson et al., 2008). It is considered as an essential part of the human diet (Metrani et al., 2020; Raber et al., 2022). It contains various minerals and vitamins (Raemaekers, 2001; Shahrajabian et al., 2020). It is also crucial in the preparation of traditional meals for Ethiopian cuisine. The bulb and lower part of the stem are most commonly used as seasoning and stew vegetables (Griffiths et al., 2002). According to Ethiopia Statistical Service (2018/2019), onion yield and productivity in Ethiopia and the Amhara region are projected to be 9.3 and 13.1 t ha⁻¹, respectively.

The application of microdosing fertilizer increases fertilizer use efficiency and yield while reducing input and investment costs (Blessing et al., 2017; Kubheka, 2015; Nouri et al., 2017). It is a highly efficient fertilizer application method with high absorption rates because fertilizer is administered very close to the plant (Sime & Aune, 2020; Vandamme et al., 2018). Compared with conventional fertilizer application methods, it has been found to improve yields by 44% to 120% and farmer profits by 52% to 134% (Fatondji et al., 2011; Tabo et al., 2011). This is especially important in irrigated agriculture, where large amounts of fertilizer must be applied to meet crop requirements while preventing leaching losses (De Baerdemaeker, 2013; Ibrahim et al., 2016). A proper combination of nutrients and irrigation water is significant to boost crop productivity and production in terms of both quantity and quality (Bajpai & Kaushal, 2020; Moursy et al., 2023; Sathya et al., 2008).

Efficient water use in irrigation systems is becoming increasingly important, especially in arid and semiarid regions where water is scarce (Deng et al., 2006; Girma & Jemal, 2015; Mekonen et al., 2022). Drip irrigation is one of the most efficient irrigation methods, allowing light and water to be provided to plants in close proximity to the amount of water they consume (S. El-Hendawy et al., 2008; Eranki et al., 2017; Fereres et al., 2003). Experience in many countries has shown that switching from surface irrigation to drip systems can reduce water use by 30% to 60% and simultaneously increase crop yields (Kifle et al., 2023).

Several researchers (Deshmukh & Hardaha, 2014; S. E. El-Hendawy et al., 2008; Feleafel & Mirdad, 2013; Vijayakumar et al., 2010) have reported that drip irrigation has a variety of benefits. Drip irrigation agrees for significant water and labor savings by reducing conventional losses of soil water evaporation, deep percolation, and runoff. In addition, drip irrigation allows for more precise and uniform application of fertilizer, which can enhance nutrient uptake by plant roots (Lepaja et al., 2024; Munir et al., 2019, 2021). Crop yield and water use efficiency increased by 3.6% to 66.4% and 5.9~60.0%, respectively, after aeration with subsurface drip irrigation (Kale et al., 2024; Yang et al., 2023). Overall, drip irrigation technology plays an essential role in improving crop yield and quality and promoting efficient water resource management in arid regions. Micro-dosing fertilizer application is the precise application of small amounts of nutrients during critical crop growth stages. There are several reasons why this method is employed. They are to increase nutrient efficiency by matching nutrient supply to plant needs, to reduce input costs for farmers, and to promote environmental sustainability by minimizing nutrient runoff and soil salinity. In addition, micro-dosing applications improve soil health by promoting microbial activity and reducing the risk of nutrient loss through volatilization and leaching. Targeted nutrient application leads to better uptake by plants, resulting in higher crop yields and profitability. In addition, micro-dosing fertilizer can be adapted to local conditions, contributing to more resilient and sustainable agricultural systems. The objectives of this study were to identify the optimum amount of micro-dose fertilizer and irrigation water for onion production and to analyze the effects of water-fertilizer interactions in a drip irrigation system.

Materials and Methods

Description of the study area

The experiment was conducted in two consecutive irrigation seasons (2019/2020 and 2020/2021) at Aybra in Sekota woreda. The location is at latitude 12°43′35.9′ and longitude 39°01′05.9′ in the northeastern Amhara region (Figure 1). The elevation of the study area is 1,917 m above mean sea level. The major soil type in the study area was cambisols (Nachtergaele et al., 2023). The soil’s texture was clay loam. The research area’s surface soil samples (0 - 30, 30 - 60 cm) were analyzed for bulk density, pH, total nitrogen (TN), available phosphorous (avail P), soil electrical conductivity (EC_e), electrical conductivity of irrigation water (EC_w), the soil water content of field capacity (FC) and permanent wilting point (PWP), and organic matter content (OM). The meteorological data was collected from the nearest station, Sekota. Daily minimum and maximum temperature, precipitation, wind speed, sunshine hour, and relative humidity were obtained. The long-term average precipitation in the area is 689.6 mm year⁻¹, peaking from July to the end of August and accounting for more than 90% of the annual precipitation (Figure 2). The average daily air temperatures range from 12.6 °C to 27.4 °C, with an average temperature of 20 °C (Figure 2). During the growing season, the average reference evapotranspiration (ET_o) in the study area was 4.0 mm day⁻¹ in 2019/2020 and 4.1 mm day⁻¹ in the year 2020/2021, ranging from 5.2 mm day⁻¹ in May to 3.2 mm day⁻¹ in July in the first year and from 5.4 mm day⁻¹ in April to 3.2 mm day⁻¹ in August in the second year (Figure 2). The study site was selected based on the local soils and climate of the area. Subsistence agriculture is practiced in the study area, with a considerable area under cultivation. Agriculture in the study area is both rainfed and irrigated.

Figure 1.

Location map of the study area.

Figure 2.

Weather conditions during the crop growing season (2019/2020–2020/2021).

Experimental design

The experimental design was used as a randomized complete block design with three replications of factorial arrangements. The experiment consisted of three irrigation levels (100%, 75%, and 50%, referred to as I₁, I₂, and I₃, respectively) and four microdose fertilizer levels, nitrogen (N) 172.5 and phosphorus (P₂O₅) 86.25, 138 N and 69 P₂O₅, 103.5 N and 51.75 P₂O₅, 69 N and 34.5 P₂O₅ kg ha⁻¹ or 125%, 100%, 75%, and 50% of the recommended fertilizer, referred to as F₁, F₂, F₃, and F₄, respectively.

To ensure the uniform establishment of onion seedlings, the same amount of irrigation water was applied to each treatment. Irrigation water was applied at 3-day intervals. A drip irrigation system was used to apply the required amount of irrigation water. Each irrigation treatment area consisted of six 3 m long lateral lines. Emitters on the lateral lines were spaced 20 cm apart and the discharge rate of each emitter was 3 L hr⁻¹. Bombay red onions were grown in the nursery bed for 45 days. Transplanted plots were arranged in rows of 1.2 m × 3 m with spacing of 20 cm by 10 cm (between rows in the lateral line and plants in rows). The recommended rate of onion fertilizer in the research area was applied at 300 kg ha⁻¹ of urea, half at planting and the other half 45 days later, and 150 kg ha⁻¹ of NPS at planting (Birhanu & Tesfaye, 2024).

Layout of field experimental design

Treatment combinations

T₁ = F₁-172.5 N and 86.25 P₂O₅ kg ha⁻¹ + I₁-100% ETc by drip irrigation system

T₂ = F₁-172.5 N and 86.25 P₂O₅ kg ha⁻¹ + I₂-75% ETc by drip irrigation system

T₃ = F₁-172.5 N and 86.25 P₂O₅ kg ha⁻¹ + I₃-50% ETc by drip irrigation system

T₄ = F₂-138 N and 69 P₂O₅ kg ha⁻¹ + I₁-100% ETc by drip irrigation system

T₅ = F₂-138 N and 69 P₂O₅ kg ha⁻¹ + I₂-75% ETc by drip irrigation system

T₆ = F₂-138 N and 69 P₂O₅ kg ha⁻¹ + I₃-50% ETc by drip irrigation system

T₇ = F₃-103.5 N and 51.75 P₂O₅ kg ha⁻¹ + I₁-100% ETc by drip irrigation system

T₈ = F₃-103.5 N and 51.75 P₂O₅ kg ha⁻¹ + I₂-75% ETc by drip irrigation system

T₉ = F₃-103.5 N and 51.75 P₂O₅ kg ha⁻¹ + I₃-50% ETc with drip irrigation system

T₁₀ = F₄-69 N and 34.5 P₂O₅ kg ha⁻¹ + I₁-100% ETc with drip irrigation system

T₁₁ = F₄-69 N and 34.5 P₂O₅ kg ha⁻¹ + I₂-75% ETc with drip irrigation system

T₁₂ = F₄-69 N and 34.5 P₂O₅ kg ha⁻¹ + I₃-50% ETc with drip irrigation system

Crop water demand

The fixed crop schedule and irrigation water demand were calculated using the CROPWAT computer model version 8.0 following the FAO 56 methodology (Allen et al., 1998). The FAO CROPWAT 8.0 model was used to calculate the experimental site’s reference evapotranspiration (ETo) based on minimum and maximum air temperatures, wind speed, relative humidity, sunlight hours, and solar radiation. Crop coefficients (Kc) were employed as the reference irrigation treatment (100% of crop water demand, CWR). Because there was no site-specific Kc for onion in the study area, the values determined by FAO 56 varied according to the phenological stage of the onion crop 0.5 at growth initiation, 1.15 during bulb development, 0.75 before maturity (Allen et al., 1998). ETc was calculated by multiplying the ETo by the crop coefficient (Kc) at each crop growth stage using the CROPWAT 8.0 model and Microsoft Excel 2010 spreadsheet (Microsoft^® Corp., Redmond, Washington, USA) over the growing season Equation 1.

ETc = ETo * Kc

(1)

Where ETc is the crop evapotranspiration in mm, Kc is the crop coefficient, and ETo is the evapotranspiration of the reference crop in mm.

Once crop evapotranspiration has been accounted for, net irrigation water demand can be obtained by subtracting the effective rainfall during the study period, as shown in Equation 2.

NIR = ETc - Pe

(2)

Where NIR is the net irrigation water demand of the crop (mm) and Pe is the effective rainfall during the growing period of the crop (mm).

Rainfall occurred in the test plots from the beginning to the end of the study (Figure 2). Equation 3 was used to predict total irrigation water demand. The irrigation application efficiency of drip irrigation is assumed to be 90% (Gamni & Sinha, 2024; Zaccaria & Bali, 2024).

GIR = \frac{NIR}{Ea}

(3)

Where GIR is the total irrigation water requirement of the crop (mm) and Ea is the application efficiency (%). Irrigation water is applied directly to the plants, and conveyance and distribution losses are not considered (Abdelraouf et al., 2020; Bhalage et al., 2015).

Water productivity (WP) was calculated as the ratio of crop production per unit area of onion bulbs to crop evapotranspiration (mm), expressed in kilograms of onion bulbs per m³ of water used (Kahlon, 2017; Wakchaure et al., 2018).

WP (kg m^{- 3}) = \frac{Total yield of onion bulb}{Water delivered up to harvesting of yield}

Data collection

Meteorological data such as rainfall, temperature, humidity, wind speed, and sunshine hours were obtained from the sekota weather station, 17 km from the experimental site. Soil data such as soil texture, bulk density (Bd), pH, organic matter (OM), total nitrogen (TN), available phosphorus (AP), soil electrical conductivity (ECe), field capacity (FC), permanent wilting point (PWP), and moisture content were measured. Data on onion plant growth and yield parameters were measured and recorded in real time from 2.4 m² net plots via the standard protocols outlined below.

Plant height (cm)

At physiological maturity, the height of five randomly selected plants was measured from the soil surface to the top of the tallest leaf, and the average height was calculated (Nigatu, 2016; Nigatu et al., 2018).

Bulb weight (g)

The weight of five randomly selected bulbs per plot was determined with a sensitive balance, and the mean bulb weight was computed for further analysis (Tekle, 2015).

Bulb diameter (cm)

The average bulb size at harvest for each plot was determined by measuring the diameter of five randomly selected bulbs via calipers (Ketema et al., 2013).

Total bulb yield (t ha⁻¹)

The total onion yield was calculated by adding the marketable and nonmarketable bulb yields (Tekle, 2015). The weight of bulbs obtained from the net field area was measured in kilograms via a sensitive balance and expressed in tons per hectare.

Data analysis

The collected onion growth and yield parameters were subjected to analysis of variance (ANOVA) via R 4.2.2 software. On the basis of the results of the analysis of variance, the means were separated via least significant difference (LSD) tests at the 5% level of significance (Gomez & Gomez, 1984).

Partial budget analysis (PBA)

A partial budget analysis was used to determine the economic benefits of using fertilizer, drip material, and irrigation water for onion production. This can be used to compare the impact of technology changes on farm costs and revenues. This budgeting method is called partial because it does not include all production costs but only those that alter or vary between the farmer’s existing and planned on-farm production methods (CIMMYT, 1988).

The following data were used for the PBA:

Variable costs (NP fertilizer and water depth varied among treatments). Onion yield per hectare obtained from each treatment. It was adjusted by a 10% decrement. The farm price of harvested onion is currently approximately 15 Ethiopian birrs per kilogram. Fixed costs included drip material, land preparation, planting, weeding, seed, chemical, and harvesting costs, which were invested equally in each treatment.

The main components of the PBA, total revenue, net income, change in variable costs, change in rate of return, and marginal cost of return were calculated to be at least 100%, and on the basis of net income and the marginal rate of return, it was determined which fertilizer rates and water depths would be more profitable for farmers.

Results and Discussion

Soil properties

The soil moisture contents at field capacity (FC) and the permanent wilting point (PWP) were 26.22% and 14.85%, respectively (Table 1). The volumetric moisture content at field capacity ranged from 26.59% to 25.86%. The average field volumetric moisture content in the top 0 to 30 cm was high at 26.59%, whereas the mean field volumetric moisture content in the 30 to 60 cm subsurface was lower at 25.86%. The soil moisture content at the permanent wilting point varied with depth, with a high value of 16.10% in the upper part (0–30 cm) and a low value of 13.61% in the subsurface soil (30–60 cm).

Table 1.

Soil Properties of the Study Area.

Soil parameters	Soil depth (cm)
Soil parameters	0–30	30–60	Average
BD (g cm⁻³)	1.38	1.57	1.47
OM (%)	1.12	1.01	1.06
pH	6.60	6.70	6.65
TN (%)	0.07	0.06	0.06
AP (ppm)	13.56	18.13	15.85
EC_e (ds m⁻¹)	0.12	0.22	0.17
Water content
FC (vol. %)	26.59	25.86	26.22
PWP (vol. %)	16.10	13.61	14.85
TAW (mm m⁻¹)	104.90	122.50	113.70
Irrigation water
pH	6.90
EC_w (ds m⁻¹)	0.22

Note. BD = bulk density; OM = organic matter; TN = total nitrogen; AP = available phosphorus; EC_e = electrical conductivity of the soil; EC_w = electrical conductivity of the water.

The total amount of available soil moisture was 113.7 mm m⁻¹, with a maximum infiltration rate of 40 mm h⁻¹. As a result, topsoil contains the highest concentration of TAW, whereas subsurface soils contain relatively low amounts (Table 1).

ANOVA result

The interaction effect of the amount of irrigation water and the amount of NP fertilizer had significant (p ⩽ 0.05) effects on plant height, bulb diameter, bulb weight, yield, and water productivity when the analysis of variance was combined (Table 2).

Table 2.

Mean square effects of water and fertilizer on onion yield and related indicators.

Source of variation	DF	Mean square values
Source of variation	DF	PH	BD	BW	YL	WP
F	3	139.12**	0.39**	243.01**	318.28**	33.87**
I	2	196.77**	0.23**	10.51**	692.80**	40.10**
F × I	6	21.80**	0.22**	48.62**	23.72**	5.51**
Error	22	0.66	0.01	0.60	0.54	0.07

Note. F = fertilizer; I = irrigation water; PH = plant height; BD = bulb diameter; BW = bulb weight; YL = yield.

A combined analysis of treatment combinations across two growing seasons can offer important information regarding the efficacy and variability of various treatments (Table 3).

Table 3.

Pooled analysis of onion yield and associated parameters across two seasons.

Parameters	Mean value season 1	Mean value Season 2	Pooled mean	Standard error	Critical difference
PH	53.47	54.05	53.76	0.42	0.87
BD	6.12	6.07	6.09	0.03	0.05
BW	59.92	59.89	59.90	0.44	0.91
YL	28.23	28.08	28.16	0.67	1.39
WP	8.10	8.14	8.11	0.20	0.41

Plant height

The interaction effect of fertilizer and irrigation amount had a significant effect on onion plant height. The plant height varied between 59.68 and 48.16 cm (Figure 3). The treatments with the highest and lowest plant heights received the recommended fertilizer rates of F₁ with I₁ and F₄ with I₃, respectively.

Figure 3.

Comparison of yield-related components under different irrigation and fertilizer management practices.

The addition of nutrients essential for onion growth and development resulted in increased in plant height (Nigatu et al., 2018). However, the application of the recommended fertilizer rates for F₄, F₃, and F₂, resulted in lower than average plant height in I₃.

The increase in plant height with adequate soil moisture application is attributed to the role of water in maintaining the expansion pressure of plant cells, the main factor in growth (Enchalew et al., 2016). On the other hand, the decrease in plant height under reduced soil moisture stress is thought to be due to the closing of stomata to conserve evaporation of soil water, resulting in reduced uptake of CO₂ and nutrients.

As a result, photosynthesis and other metabolic responses are inhibited, ultimately inhibiting plant growth (Cao et al., 2022; Pereira et al., 2020). The results of this study are consistent with the findings of El-Noemani et al. (2009), who reported that the soil moisture supply is directly proportional to plant height.

Bulb diameter

Irrigation water and fertilizer application affected the onion bulb diameter, with the I₁ and F₁ fertilizer treatments having the greatest bulb diameters, which were much greater than those of all the other treatments (Figure 3). Among the required fertilizer treatments, the bulb diameter was the smallest in the I₃ and F₃ treatments; water deficit up to I₃ resulted in a bulb diameter less than the mean value of 6.04 cm.

This finding is in agreement with those of Tolossa (2021); Bhasker et al. (2018), and Enchalew et al. (2016) who reported that higher soil moisture application, resulted in a greater photosynthetic area, greater plant height, greater number of leaves, and larger bulb diameter.

Yield and water productivity

The results of a 2-year combined analysis revealed that F₁ application of the recommended nitrogen and phosphorus from among the fertilizer amounts increased onion bulb yield (Figure 4). Onion is a shallow-rooted crop that requires high amounts of nitrogen during the growing season (Halvorson et al., 2008). Nevertheless, as the nitrogen supply decreases, the phosphorus requirements of plants also decrease. Plant water uptake and nutrient absorption are highly related. As plant roots absorb water, dissolved nutrients are transported to onion root surfaces. On the other hand, water uptake decreases, and the nutrient supply to the root system decreases.

Figure 4.

Comparison of bulb yield and water productivity under different irrigation and fertilizer management practices.

Irrigation with I₁ at 3-day intervals improved yields more than when I₂ and I₃ were applied, but there were no significant differences between the deficit treatments. Although the soil moisture status was not monitored during irrigation, the difference in moisture between the two depths was not significant. As a result, these two treatments should result in similar soil moisture conditions.

The interaction effect of irrigation and fertilizer had a significant (p ⩽ .05) effect on onion water productivity (Figure 4). However, water productivity decreased with increasing irrigation depth, whereas fertilizer application significantly increased water productivity at all irrigation levels. Thus, onion water productivity decreased when the recommended F₁ fertilizer rate was set at I₁ compared with when the recommended F₁ fertilizer rate was set at I₃.

When the recommended microdosing fertilizer rate for F₁ was applied at the I₃ irrigation rate, water savings of 50% were possible. As a result, compared with full irrigation, 50% deficit irrigation saved a considerable amount of water (2,382.25 m³ ha⁻¹) without significantly reducing yields (Table 4). Therefore, it may be possible to divert this stored water to other irrigable land and increase the irrigated area to compensate for the reduction in crop yields. As a result, 0.99 ha of additional land could be irrigated, yielding 29.85 t ha⁻¹ onion productions.

Table 4.

Shows the relationship between water savings and yield reduction in onion production.

Treatments	Irrigation water (m³ ha⁻¹)	Tuber yield (t ha⁻¹)	Water saved (%)	Yield reduction (%)
T₁	4,776.00	37.18	0	0
T₂	3,582.50	31.59	25	15.03
T₃	2,393.75	30.15	50	18.90
T₄	4,776.00	35.12	0	0
T₅	3,582.50	28.64	25	18.45
_T6	2,393.75	23.41	50	33.34
T₇	4,776.00	28.88	0	0
T₈	3,582.50	27.13	25	6.06
T₉	2,393.75	18.93	50	34.45
T₁₀	4,776.00	27.01	0	0
T₁₁	3,582.50	21.15	25	21.69
T₁₂	2,393.75	18.96	50	29.80

The experimental results of the field trial confirmed that deficit irrigation strategies and appropriate microdosing of fertilizer can increase crop productivity and WUE and conserve irrigation water. This may be especially important for areas facing drought and limited water resources for onion agricultural production. Similar findings have reported that optimizing water and fertilizer application improves photosynthesis (Wang et al., 2014; Zhang et al., 2017) and that increasing biomass yield (Mon et al., 2016) can ultimately increase crop yield and crop water and fertilizer use efficiency (Albrizio et al., 2010; Dar et al., 2017; Li et al., 2010). Mansouri-Far et al. (2010) and Fan et al. (2021) reported that irrigation water can be saved and yields can be maintained under water deficit conditions (as a drought stress-sensitive crop).

Partial budget analysis

A partial budget analysis was conducted on onion bulb yields. The results revealed that the highest net returns were obtained when I₁ irrigation water was applied for 3 days at the F₁ recommended nitrogen and phosphorus fertilizer application rates, which would be profitable only if the rate of return was greater than 100% (CIMMYT, 1988). However, as Table 5 below shows, its marginal rate of return (MRR) is 42.92%, which is well below 100%. Other rates, such as the (F₁:I₂), (F₁:I₃), (F₂:I₂), (F₂:I₃), (F₃:I₂), (F₃:I₃), (F₄:I₁), (F₄:I₂), and (F₄:I₃) rates, are dominated by the 3-day interval of the microdosing fertilizer rate and irrigation depth. All of these rates were rejected because the recommended fertilizer rate of F₃ and irrigation depth of I₁ at 3-day intervals increased costs and did not increase net benefits. Thus, the partial budget analysis revealed that the recommended microdosing fertilizer application of F₃ and the 3-day interval irrigation depth of I₁ provided the greatest benefit to farmers over the other fertilizer application rates (Table 5).

Table 5.

Partial budget analysis of the effects of irrigation and fertilizer on yield (t ha⁻¹).

Treatments	Unadjusted yield	Adjusted yield	Total benefit	Variable cost	Net benefit (ET, birr)	MRR (%)
T₁	39.22	35.298	529,470	8,789	520,681	42.92
T₂	30.82	27.738	416,070	8,789	407,281	D
T₃	30.22	27.198	407,970	8,789	399,181	D
T₄	33.51	30.159	452,385	7,034	445,351	14.92
T₅	31.31	28.179	422,685	7,034	415,651	D
T₆	24.08	21.672	325,080	7,034	318,046	D
T₇	31.44	28.296	424,440	5,279	419,161	3.38
T₈	25.81	23.229	348,435	5,279	343,156	D
T₉	18.20	16.38	245,700	5,279	240,421	D
T₁₀	30.87	27.783	416,745	3,524	413,221	D
T₁₁	22.62	20.358	305,370	3,524	301,846	D
T₁₂	19.70	17.73	265,950	3,524	262,426	D

Conclusions and Recommendations

The effects of nitrogen and phosphorus and the irrigation rate on onion yield and yield components were evaluated. The irrigation water quantity and microdosing fertilizer application rate are the major limiting factors for onion production and productivity. Therefore, the combined interaction of irrigation water and the microdosing fertilizer rate under drip irrigation is a suitable and the most efficient fertilizer application method for sustainable production in water-scarce areas such as Wag-himra, Ethiopia.

The maximum bulb diameter, bulb weight, plant height, and total bulb yield were related to the F₁-recommended microdosing fertilizer rate and the I₁ irrigation water rate. However, to maximize onion water productivity, F₁-dosing fertilizer should be combined with I₃ water deficit irrigation.

On the basis of the partial budget analysis, the combination of the F₁, F₂, and F₃ recommended microdosing fertilizer rates and I₁ irrigation water rates is economical and can be recommended for onion production in the study area and similar agro ecosystems.

Footnotes

Acknowledgements

The Amhara Agricultural Research Institute and the Sekota Dry-Land Agricultural Research Center are responsible for support, logistics, and advice on research progress.

Author Contributions

AW: gathered, analyzed, and interpreted data, as well as writing and editing the paper. MA, TA, and GB were data collected, monitoring the experiment, data management, and data analysis.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Aemro Wale

Data Availability

The data will be provided upon request from the corresponding author(s).

References

Abdelraouf

R. E.

El-Shawadfy

M. A.

Ghoname

A. A.

Ragab

(2020). Improving crop production and water productivity using a new field drip irrigation design. Plant Archives, 20(1), 3553–3564.

Albrizio

Todorovic

Matic

Stellacci

A. M.

2010. Comparing the interactive effects of water and nitrogen on durum wheat and barley grown in a Mediterranean environment. Field Crops Research, 115, 179–190.

Allen

R. G.

Pereira

L. S.

Raes

Smith

(1998). FAO irrigation and drainage paper no. 56. Food and Agriculture Organization of the United Nations, 56(97), e156.

Bajpai

Kaushal

(2020). Soil moisture distribution under trickle irrigation: A review. Water Supply, 20(3), 761–772.

Bhalage

Jadia

Sangale

(2015). Case studies of innovative irrigation management techniques. Aquatic Procedia, 4, 1197–1202.

Bhasker

Singh

Gupta

Sharma

Gupta

(2018). Effect of drip irrigation on growth and yield of onion (Allium cepa L.). Journal of Spices and Aromatic Crops, 27, 32–37.

Birhanu

Tesfaye

(Eds.). (2024, May 15–17). Proceedings of the 16th Annual Regional Conferences on Completed Research Activities on Soil and Water Management. Bahir Dar, Ethiopia. Amhara Agricultural Research Institute (ARARI).

Blessing

O. C.

Ibrahim

Safo

E. Y.

Yeboah

Abaidoo

R. C.

Logah

Monica

U. I.

(2017). Fertilizer micro-dosing in West African low-input cereals cropping:Benefits, challenges and improvement strategies. African Journal of Agricultural Research, 12, 1169–1176.

Cao

(2022). Irrigation water use and efficiency assessment coupling crop cultivation, commutation and consumption processes. Agricultural Water Management, 261, 107370.

10.

CIMMYT. (1988). From agronomic data to farmer recommendations: An economics workbook.

11.

Dar

E. A.

Brar

Mishra

Singh

(2017). Simulating response of wheat to timing and depth of irrigation water in drip irrigation system using CERES-Wheat model. Field Crops Research, 214, 149–163.

12.

De Baerdemaeker

. (2013). Precision agriculture technology and robotics for good agricultural practices. IFAC Proceedings Volumes, 46, 1–4.

13.

Deng

X.-P.

Shan

Zhang

Turner

N. C.

(2006). Improving agricultural water use efficiency in arid and semiarid areas of China. Agricultural Water Management, 80, 23–40.

14.

Deshmukh

Hardaha

(2014). Effect of irrigation and fertigation scheduling under drip irrigation in papaya. Journal of AgriSearch, 1, 216–220.

15.

Dessalegn

Aklilu

(2003). Onion Research results and experiences in dry bulb and seed production in Ethiopia (p. 39). Vegetable Crops Improvement Research Ethiopian Agricultural Research Organization, Melkassa Agricultural Research Center.

16.

El-Hendawy

S. E.

Abd El-Lattief

E. A.

Ahmed

M. S.

Schmidhalter

(2008). Irrigation rate and plant density effects on yield and water use efficiency of drip-irrigated corn. Agricultural Water Management, 95, 836–844.

17.

El-Hendawy

Hokam

Schmidhalter

(2008). Drip irrigation frequency: The effects and their interaction with nitrogen fertilization on sandy soil water distribution, maize yield and water use efficiency under Egyptian conditions. Journal of Agronomy and Crop Science, 194, 180–192.

18.

El-Noemani

Aboamera

Aboellil

Dewedar

(2009). Growth, yield, quality and water use efficiency of pea (Pisum sativum L.) plants as affected by evapotranspiration (ETo) and sprinkler height. Minufiya Journal of Agricultural Research, 34, 1445–1466.

19.

Enchalew

Gebre

Rabo

Hindaye

Kedir

Musa

Shafi

(2016). Effect of deficit irrigation on water productivity of onion (Allium cepal.) under drip irrigation. Irrigation and Drainage Systems Engineering, 5, 2.

20.

Eranki

El-Shikha

Hunsaker

Bronson

Landis

(2017). A comparative life cycle assessment of flood and drip irrigation for guayule rubber production using experimental field data. Industrial Crops and Products, 99, 97–108.

21.

Ethiopia Statistical Service. (2018/19). Agricultural sample survey: Report on area and Production of crops (p. 136).

22.

Fan

Kang

Wang

Fang

(2021). A novel approach to dynamically optimize the spatio-temporal distribution of crop water consumption. Journal of Cleaner Production, 310, Article 127439.

23.

Fatondji

Tabo

Bationo

B. A.

Fosu

Sawadogo

(2011). Enhancing rainwater and nutrient use efficiency for improved crop productivity, farm income and rural livelihood in the Volta Basin (CPWF Project Report). CPWF.

24.

Feleafel

Mirdad

(2013). Hazard and effects of pollution by lead on vegetable crops. Journal of Agricultural and Environmental Ethics, 26, 547–567.

25.

Fereres

Goldhamer

D. A.

Parsons

L. R.

(2003). Irrigation water management of horticultural crops. HortScience, 38, 1036–1042.

26.

Gamni

Sinha

B. L.

(2024). Hydraulic performance evaluation of drip system. International Journal of Advanced Biochemistry Research, 8(9), 901–903.

27.

Girma

Jemal

(2015). Irrigation system in Israel: A review. International Journal of Water Resources and Environmental Engineering, 7, 29–37.

28.

Gomez

K. A.

Gomez

A. A.

(1984). Statistical procedures for agricultural research. John wiley & Sons.

29.

Griffiths

Trueman

Crowther

Thomas

Smith

(2002). Onions a global benefit to health. Phytotherapy Research, 16, 603–615.

30.

Halvorson

A. D.

Bartolo

M. E.

Reule

C. A.

Berrada

(2008). Nitrogen effects on onion yield under drip and furrow irrigation. Agronomy Journal, 100, 1062–1069.

31.

Ibrahim

Abaidoo

R. C.

Fatondji

Opoku

(2016). Fertilizer micro-dosing increases crop yield in the Sahelian low-input cropping system: A success with a shadow. Soil Science and Plant Nutrition, 62, 277–288.

32.

Kahlon

(2017). Effect of planting methods and irrigation levels on water productivity of onion (Allium cepa L.). Indian Journal of Agricultural Research, 51, 510–513.

33.

Kale

R. B.

Gavhane

A. D.

Thorat

V. S.

Gadge

S. S.

Wayal

S. M.

Gaikwad

S. Y.

Singh

Khandagale

K. S.

Bhat

Mahajan

(2024). Efficiency dynamics among onion growers in Maharashtra: A comparative analysis of drip irrigation adopters and non-adopters. BMC Plant Biology, 24(1), 237.

34.

Ketema

Dessalegn

Tesfaye

(2013). Effect of planting methods on maturity and yield of onion (Allium cepa var cepa) in the Central Rift Valley of Ethiopia. Ethiopian Journal of Agricultural Sciences, 24, 45–55.

35.

Kifle

Mengist

Gebre

(2023). Participatory evaluation and demonstration of onion response to deficit irrigation at Gibe Woreda, Ethiopia. Journal of Agricultural Science and Food Research, 14, 163.

36.

Kubheka

B. P.

(2015). Integrating microdosing of fertilizers with biological control agents for maize production in the Eastern Cape, South Africa. University of Kwazulu-Natal.

37.

Lepaja

Kullaj

Balaj

(2024). The influence of drip irrigation on water efficiency in pear cultivation. Journal of Ecological Engineering, 25(7), 241–245.

38.

Dong

Qiao

Liu

Zhang

(2010). Root growth, available soil water, and water-use efficiency of winter wheat under different irrigation regimes applied at different growth stages in North China. Agricultural Water Management, 97, 1676–1682.

39.

Mansouri-Far

Sanavy

S. A. M. M.

Saberali

S. F.

(2010). Maize yield response to deficit irrigation during low-sensitive growth stages and nitrogen rate under semi-arid climatic conditions. Agricultural Water Management, 97, 12–22.

40.

Mekonen

B. M.

Gelagle

D. B.

Moges

M. F.

(2022). The current irrigation potential and irrigated land in Ethiopia: A review. Asian Journal of Advances in Research, 5(1), 274–281.

41.

Metrani

Singh

Acharya

P. K.

Jayaprakasha

S. Patil

. (2020). Comparative metabolomics profiling of polyphenols, nutrients and antioxidant activities of two red onion (Allium cepa L.) cultivars. Plants, 9, 1077.

42.

Mon

Bronson

Hunsaker

Thorp

White

French

(2016). Interactive effects of nitrogen fertilization and irrigation on grain yield, canopy temperature, and nitrogen use efficiency in overhead sprinkler-irrigated durum wheat. Field Crops Research, 191, 54–65.

43.

Moursy

M. A. M.

ElFetyany

Meleha

A. M. I.

El-Bialy

M. A.

(2023). Productivity and profitability of modern irrigation methods through the application of on-farm drip irrigation on some crops in the Northern Nile Delta of Egypt. Alexandria Engineering Journal, 62, 349–356.

44.

Munir

M. S.

Bajwa

I. S.

Ashraf

Anwar

Rashid

(2021). Intelligent and smart irrigation system using edge computing and IoT. Complexity, 2021, 1–16.

45.

Munir

M. S.

Bajwa

I. S.

Cheema

S. M.

(2019). An intelligent and secure smart watering system using fuzzy logic and blockchain. Computers & Electrical Engineering, 77, 109–119.

46.

Nachtergaele

van Velthuizen

Verelst

Wiberg

Henry

Chiozza

Yigini

(2023). Harmonized world soil database version 2.0. Food and Agriculture Organization of the United Nations.

47.

Nigatu

(2016). Assessment of onion production practices and effects of N: P2O5: S fertilizers rates on yield and yield components of onion (Allium cepa l.) under irrigated farming system in Dembiya District, Amhara Region, Ethiopia. Bahir Dar University.

48.

Nigatu

Alemayehu

Sellassie

A. H.

(2018). Optimum rate of NPS fertilizer for economical production of irrigated onion (Allium cepa L) in Dembyia district of Amhara region, Ethiopia. Ethiopian Journal of Science and Technology, 11, 113–127.

49.

Nouri

Garba

Wortmann

C. S.

(2017). Optimizing fertilizer use within the context of integrated soil fertility management in Niger. Fertilizer use optimization in sub-Saharan Africa. CABI GB.

50.

Pereira

L. S.

Paredes

Jovanovic

(2020). Soil water balance models for determining crop water and irrigation requirements and irrigation scheduling focusing on the FAO56 method and the dual Kc approach. Agricultural Water Management, 241, Article 106357.

51.

Raber

Jackson

Basen-Engquist

Bradley

Chambers

Gany

F. M.

Halbert

C. H.

Lindau

S. T.

Pérez-Escamilla

Seligman

(2022). Food insecurity among people with cancer: Nutritional needs as an essential component of care. JNCI: Journal of the National Cancer Institute, 114, 1577–1583.

52.

Raemaekers

R. H.

(2001). Agriculture en Afrique tropicale. DGIC.

53.

Sathya

Pitchai

G. J.

Indirani

Kannathasan

(2008). Effect of fertigation on availability of nutrients (N, P & K) in soil A review. Agricultural Reviews, 29, 214–219.

54.

Shahrajabian

M. H.

Wenli

Cheng

(2020). Chinese onion, and shallot, originated in Asia, medicinal plants for healthy daily recipes. Notulae Scientia Biologicae, 12, 197–207.

55.

Sime

Aune

J. B.

(2020). On-farm seed priming and fertilizer micro-dosing: Agronomic and economic responses of maize in semi-arid Ethiopia. Food and Energy Security, 9, e190.

56.

Tabo

Bationo

Amadou

Marchal

Lompo

Gandah

Hassane

Diallo

M. K.

Ndjeunga

Fatondji

(2011). Fertilizer microdosing and “warrantage” or inventory credit system to improve food security and farmers’ income in West Africa. In Bationo

Waswa

Okeyo

Maina

Kihara

(Eds.), Innovations as key to the Green Revolution in Africa (pp. 113–121). Springer.

57.

Tekle

(2015). Growth, yield and quality of onion (Allium cepa L.) as influenced by intra-raw spacing and nitrogen fertilizer levels in central zone of Tigray, Northern Ethiopia. Haramaya University.

58.

Tolossa

T. T.

(2021). Onion yield response to irrigation level during low and high sensitive growth stages and bulb quality under semi-arid climate conditions of Western Ethiopia. Cogent Food & Agriculture, 7, Article 1859665.

59.

Vandamme

Ahouanton

Mwakasege

Mujuni

Mujawamariya

Kamanda

Senthilkumar

Saito

(2018). Phosphorus micro-dosing as an entry point to sustainable intensification of rice systems in sub-Saharan Africa. Field Crops Research, 222, 39–49.

60.

Vijayakumar

Novosyadlyy

Yakar

Leroith

(2010). Biological effects of growth hormone on carbohydrate and lipid metabolism. Growth Hormone & IGF Research, 20, 1–7.

61.

Wakchaure

Minhas

Meena

K. K.

Singh

N. P.

Hegade

P. M.

Sorty

A. M.

(2018). Growth, bulb yield, water productivity and quality of onion (Allium cepa L.) as affected by deficit irrigation regimes and exogenous application of plant bio–regulators. Agricultural Water Management, 199, 1–10.

62.

Wang

Liu

Feng

Xie

Zhu

Guo

(2014). Effects of different irrigation and nitrogen regimes on root growth and its correlation with above-ground plant parts in high-yielding wheat under field conditions. Field Crops Research, 165, 138–149.

63.

Yang

Cheng

Fan

Wang

Qian

(2023). Review on drip irrigation: Impact on crop yield, quality, and water productivity in China. Water, 15(9), 1733.

64.

Zaccaria

Bali

K. M.

(2024). Surface drip irrigation. In Adeboye

M. O. S. U.

Sharma

A. M. P. M.

(Eds.), Micro irrigation for crop production (pp. 215–255). Elsevier Science.

65.

Zhang

Wang

Gong

Sui

(2017). Nitrogen fertigation effect on photosynthesis, grain yield and water use efficiency of winter wheat. Agricultural Water Management, 179, 277–287.

Effects of Microdose Fertilizers and Irrigation Depth on Onion ( Allium cepa L. ) Growth Under Drip Irrigation in Northern Ethiopia

Abstract

Keywords

Introduction

Materials and Methods

Description of the study area

Experimental design

Layout of field experimental design

Treatment combinations

Crop water demand

Data collection

Plant height (cm)

Bulb weight (g)

Bulb diameter (cm)

Total bulb yield (t ha−1)

Data analysis

Partial budget analysis (PBA)

Results and Discussion

Soil properties

ANOVA result

Plant height

Bulb diameter

Yield and water productivity

Partial budget analysis

Conclusions and Recommendations

Footnotes

Acknowledgements

Author Contributions

Declaration of Conflicting Interests

Funding

ORCID iD

Data Availability

References

Total bulb yield (t ha⁻¹)