Issue 1 (201)/2025

ALSE and ACS Style
Onwuegbunam, D.O.; Oyebode, M.A.; Igbadun, H.E.; Ismail, H.; Maisamari, I.J. Actual crop coefficients and yield response factors of irrigated tomato in Afaka, Northwest Nigeria. Journal of Applied Life Sciences and Environment 2025, 58 (1), 13-31.
https://doi.org/10.46909/alse-581162

AMA Style
Onwuegbunam DO, Oyebode MA, Igbadun HE, Ismail H, Maisamari IJ. Actual crop coefficients and yield response factors of irrigated tomato in Afaka, Northwest Nigeria. Journal of Applied Life Sciences and Environment. 2025; 58 (1): 13-31. 
https://doi.org/10.46909/alse-581162

Chicago/Turabian Style
Onwuegbunam, Donatus Obiajulu, Muyideen Abubakar Oyebode, Henry Evonameh Igbadun, Habibu Ismail, and Isaac John MaisamarI. 2025. “Actual crop coefficients and yield response factors of irrigated tomato in Afaka, Northwest Nigeria.” Journal of Applied Life Sciences and Environment 58, no. 1: 13-31. 
https://doi.org/10.46909/alse-581162

Actual crop coefficients and yield response factors of irrigated tomato in Afaka, Northwest Nigeria

Donatus Obiajulu ONWUEGBUNAM^1*, Muyideen Abubakar OYEBODE², Henry Evonameh IGBADUN², Habibu ISMAIL² and Isaac John MAISAMARI¹

¹Forestry Research Institute of Nigeria/Federal College of Forestry Mechanization, Afaka, Kaduna, Nigeria; e-mail: isaacmaisamari@gmail.com

²Department of Agricultural and Bio-Resources Engineering, Ahmadu Bello University, Zaria, Nigeria; email: maoyebode@gmail.com; igbadun20@yahoo.com; habfta@yahoo.com

*Correspondence: donancy2001@yahoo.com 

Received: Oct. 02, 2024. Revised: Jan. 05, 2025. Accepted: Jan. 17, 2025. Published online: Feb. 19, 2025

ABSTRACT. In the face of the prevailing challenges of limited water for irrigated agriculture, the knowledge of crop coefficients for use in irrigation, and the yield response to moisture stresses become pertinent for developing strategies to improve agricultural water productivity. Field experiments were conducted to evaluate the crop coefficients and yield response factors of UC 82B tomato subjected to soil moisture stresses on growth-stage basis. The irrigation treatments investigated were: a full irrigation (application of 100% ETo), and three soil moisture deficit levels (20%, 40%, 60% ETo) imposed at the vegetative, flowering and maturity growth stages, in successions. The mean crop coefficient (Kc) was highest (0.99) during the mid-season under full irrigation, and lowest (0.47) during the vegetative stage under 60% ETo soil moisture deficit, while the mean value across the entire crop growth stage was 0.88. The yield response factors (Ky) were 1.26 and 1.30 for the 2017/2018 and 2018/2019 seasons, respectively. The mean Ky of was 1.28 for the entire growth cycle, implying high sensitivity of the tomato cultivar to water deficits, and that yield reduction is proportionally larger when water used is reduced because of stress. Full irrigation at the maturity stage is recommended.

Keywords: crop coefficients; deficit irrigation; Northwest Nigeria; tomato; yield response.

 

INTRODUCTION

Tomatoes (Solanum lycopersicum) has been described as the world’s most popular and most highly consumed vegetable, being a basic ingredient in assorted raw, cooked and processed foods (Hou et al., 2020; OECD, 2017). They are a good source of vitamin C, lycopene, iron, potassium, folate and other antioxidants such as beta-carotene, and phenolic compounds which are required for improved health (Çelik et al., 2023). In Nigeria, tomato is produced in commercial quantities in the Northwest region for trans-regional trade within the country (Jaliya et al., 2016).

More than 60% of irrigated arable land across the globe is under high water stress due to competing demand for the available and scarce water resources (FAO, 2020). Urgent action is therefore required in these areas to ensure more productive use of water for irrigation through measures to increase crop yield and reduce crop water use. Irrigated crop production is both contributing to, and influenced by, rising pressure on the scarce freshwater resources. The concerns over this scarcity and inefficient use of water are requires increasing water-use efficiency (FAO, 2020). A crucial parameter in irrigation water management is the crop coefficient (Kc), which is the crop’s water need relative to the reference evapotranspiration (ETo) (Ko et al., 2009). ETo is the evapotranspiration rate from a hypothetical reference crop (grass) of assumed height equal to 0.12 m, a fixed surface resistance of 70 sec m^-1 and an albedo of 0.23, closely resembling the evapotranspiration from an extensive surface of green grass of uniform height, actively growing, well-watered, free of diseases, and completely shading the ground (FAO, 1998). Practically, ETo can be directly measured with a class A evaporation pan or lysimeters. Indirectly, several climate-based models exist for estimating ETo, among which are the Penman-Monteith (FAO-PM), Blaney Criddle, and Priestly-Tailor models. ETo estimation by Penman-Monteith has been parameterized and recommended by the Food and Agriculture Organization (FAO) of the United Nations as the standard by which other models are evaluated (Dai et al., 2022). While a disadvantage of the FAO-PM method is the requirement for a large amount of measured weather data, this challenge has been overcome by the introduction of the CropWat 8.0 software which computes the ETo on inputting only five weather data, namely, minimum and maximum temperature, humidity, wind speed and sunshine hour duration (FAO, 2024).

Crop coefficient (Kc) is required to adjust the reference evapotranspiration (ETo) for local conditions and crop-specific growth habits, thereby enabling accurate estimation of irrigation water needs. The crop coefficient (Kc) integrates two major factors – the crop properties related to the phenological stage, and soil evaporation effects into a single value for irrigation scheduling (Kisekka et al., 2021). Kc correlates two fundamental quantities, namely, the reference evapotranspiration, and crop water use (crop evapotranspiration, ETc), which represents soil evaporation, transpiration loss through leaves, and the water used by a crop for metabolic activities, which accounts for less than 1% of total water absorption (Abdullah et al., 2021; Allen et al., 1998). Over the growing season, the crop coefficient (Kc) varies for each crop type as a function of the canopy ground-cover, the leaf area and crop height (Kisekka et al., 2021; Pereira et al., 2020). Generally, the growing period for annual crops is divided into four stages, namely, the initial stage (from the planting date to 10% ground cover), the crop development stage (from 10% ground cover to the initiation of flowering), the mid-season stage (from complete ground cover to early senescence), and the late season (from fruit maturity to harvest) (Kisekka et al., 2021; Water Conservation Factsheet, 2001). For efficient irrigation scheduling, the computation of Kc values is based on these phenological stages.

The crop coefficient values of different crops have been published by different researchers, and these have been observed to vary with location, climate and crop cultivar (Hussain et al., 2023; Pereira et al., 2020; Water Conservation Factsheet, 2001). Hence, local or regional determination of Kc becomes necessary to ensure crop-specific irrigation schedule that will ensure precision administration for efficient water conservation and high water use efficiency in the region. Information on Kc for tomatoes in Northwest Nigeria are rarely available. A few published resources on Kc in the region are those of Abdulmumin and Misari (1990) for sorghum, cotton, maize, groundnut and millet; Igbadun and Oiganji (2012) for onions in Samaru, Zaria; Zakari et al. (2019) for UC 82B tomato at Kano River Irrigation Project; Ahmed et al. (2020) for an unspecified tomato cultivar in Pampaida millennium village, Kaduna; Suleiman and Abdullahi (2022) for cowpea. Yield response factor (Ky) of crops is a critical factor in irrigation management, indicating the sensitivity of crop yield in response to the imposed water stress. Irrigating below crop water requirement has the tendency to trigger a reduction in crop yield, which effect on the yield of crops can be negligible if the moisture stress is applied during particular phenological stages of less sensitivity to moisture deficiency (Moutonnet, 2000). Tomato is sensitive to soil moisture deficit and it has been reported that the yields reduce significantly due to soil moisture deficit of as much as 50% field capacity (FC) as compared with full irrigation (Chakma et al., 2021). Estimating Ky, therefore, is essential for crops and their cultivars, especially under water-limiting conditions, in order to achieve mathematical optimization of deficit irrigation levels for application during specific or all of the periods of the crop cycle. Hence, the objectives of this study are to calculate the crop coefficients of UC 82B tomato cultivar and its yield responses as affected by deficit irrigation at the crop phenological stages.

 

MATERIALS AND METHODS

Study location

The study was carried out at the crop research field of the Federal College of Forestry Mechanization, Afaka, Kaduna, Northwest, Nigeria, located on 10.633^º N and 7.433^º E (Figure 1). The climate is defined by a marked difference between the dry and wet spells. The onset of the rainy season is mid-April, and ends by to early October. The mean annual rainfall is 1206 mm, and the temperature range is 31^ºC to 33^ºC for the maximum scale and 14^ºC to 19^ºC for the minimum scale (NIMET, 2015). The prevalent weather characteristics of the study area during the 2017/2018 and 2018/2019 irrigation seasons are presented in Tables 1a and 1b. The daily values of reference evapotranspiration (ETo) for 2017/2018 season ranged between 5.3-5.7 mm, 5.4-5.7 mm, 5.9-6.3 mm, and 6.3-6.7 mm, for December, January, February, and March, respectively. Similarly, daily ETo for 2018/2019 ranged between 5.3-6.2 mm, 5.3-5.8 mm, 5.8-6.1 mm, 6.0-6.6 mm, for December, January, February, and March, respectively. Preliminary soil sampling carried out within the 0-60cm soil profile depth showed the soil physical properties related to irrigation as presented in Table 2.

Description of test crop

The test crop, UC 82B tomato, is an early determinate cultivar popularly grown in the area for its high yielding and excellent fruit quality, being firm in shape, reddish and with good keeping quality. It has a yield potential of 30 tha^-1 (Olusola and Oluwasina, 2023). Observations of the crop growth parameters were scheduled to match the irrigation intervals of three days. Hence, the crop phenological stages were obtained by visual observations and records of the relative canopy ground cover percentages. Following FAO (1998) description, growth stages were taken as: the initial stage (from transplanting to establishment or 10% ground cover); development stage (from 10% ground cover to effective full cover); mid-season stage (from effective root cover to start of maturity) and late season (from early senescence to harvest).

 

Table 1a
Mean weather data for 2017/2018 irrigation season

Month	Minimum temp. (oC)	Maximum temp. (oC)	Humidity (%)	Wind (km/day)	Sunshine (hours)	ETo (mm/day)	Rain (mm)
Dec 2017	15.2	31.9	31	179	8.7	5.47	0.0
Jan 2018	17.9	34.0	27	159	9.1	5.65	0.0
Feb 2018	19.1	34.1	25	166	9.1	6.15	0.0
Mar 2018	22.3	35.7	28	165	9.3	6.57	0.0

Source: Field data (2017/2018)

 

Table 1b
Mean weather data for 2018/2019 irrigation season

Month	Minimum temp. (oC)	Maximum temp. (oC)	Humidity (%)	Wind (km/day)	Sunshine (hours)	ETo (mm/day)	Rain (mm)
Dec 2018	17.7	35.0	31	169	9.1	5.71	0.0
Jan 2019	20.4	32.9	23	154	8.9	5.59	0.0
Feb 2019	15.1	32.6	27	179	9.2	6.03	0.0
Mar 2019	20.9	35.2	33	170	9.3	6.47	0.0

Source: Field data (2018/2019)

 

Table 2
Irrigation-related soil physical characteristics of the experimental site

Depth (cm)	FC (%)	PWP (%)	Bd (g/cm3)	Clay (%)	Silt (%)	Sand (%)	Textural class
0-15	20.7	9	1.45	9.79	30.59	59.62	SL
15-30	22.1	8.9	1.46	16.47	28.72	54.81	SL
30-45	22.8	9.7	1.46	16.1	29	54.9	SL
45-60	23.5	12	1.47	29.32	21.03	49.65	SCL

B_d: bulk density; FC: Field capacity; PWP: permanent wilting point; SCL: sandy clay loam; SL: sandy loam
Source: Field data (2017/2018)

 

 

The phenological stages of the cultivar, in calendar and growing degree days (GDD), are presented in Tables 3a and 3b for the two irrigation seasons. The growing degree days (GDD) were computed as function of the calendar days, minimum and maximum temperatures, and base temperature of 10^oC (Equation 1).

where GDD is growing degree days; T_max is maximum temperature (^oC); T_min is minimum temperature (^oC); T_base is base temperature (^oC).

The crop height and canopy ground cover at the various phenological stages are presented in Table 4.

Experimental procedures

Deficit irrigation trials on crop growth stage basis were conducted between 12^th December and 11^th March in each of the 2017/2018 and 2018/2019 irrigation seasons. The experimental treatments were laid in randomized complete block (RCBD) and replicated three times. Deficit irrigation and crop growth stages were the treatment factors, and the deficit levels are 80% ETo, 60% ETo and 40% ETo, imposed at the vegetative, flowering, and maturity stages. Full irrigation (100% ETo) at the three growth stages was the control. The experimental treatments are described in Table 5.

The inter-row spacing was 55 cm while the intra-row spacing was 45.7 cm. The intra-row spacing (between plants along the row) fitted into the spacing between emitters on the lateral. The field layout comprised ten plots of dimensions 5 m by 1.1 m each (each plot represented a treatment), replicated three times and hence, 55 m² per block (replication). The spacing gave approximate plant density of 40,000 stands ha^-1 (FAO, 2013).

Irrigation was applied by means of a drip irrigation system with 12.7 mm diameter driplines having inline emitters of 2.5 lh^-1 flow rate, spaced every 45.7 mm. Water was applied as per the deficit irrigation levels for each treatment based on the drip irrigation running time expressed as Equation (2) (Kumari et al., 2014).

where T _drip is drip irrigation time (hours); Np is number of plants served by one lateral; V is volume of water applied per plant in drip irrigation system (litre); Ne is number of emitters in one lateral; Q is average emitter discharge (litre/hr); EU is the system emission uniformity.

Estimation of reference evapotranspiration (ETo)

Daily reference evapotranspiration (ETo) was computed using daily values of the following weather parameters: maximum and minimum temperatures (^oC), relative humidity (%), wind speed (km/day; m/s), and sunshine hour duration (h), for the study area.

 

Table 3a
Crop growth stages (calendar and growing degree days) – 2017/2018 season

	Days	Tmax	Tmin	Tbase	GDD	GDD	∑GDD
Initial	10	31.9	15.2	10	13.55	135	135
Development	21	34	17.9	10	15.95	335	470
Mid	33	34.1	19.1	10	16.6	548	883
Late	24	35.7	22.3	10	19	456	1004

Tmax: max. temp. (^oC); Tmin: min. temp. (^oC); Tbase: base temp. (^oC); GDD is growing degree days
Source: Field data (2017/2018)

 

Table 3b
Crop growth stages (calendar and growing degree days) – 2018/2019 season

	Days	Tmax	Tmin	Tbase	GDD	GDD	∑GDD
Initial	10	35	17.7	10	16.35	164	164
Development	22	32.9	20.4	10	16.65	350	514
Mid	33	32.6	15.1	10	13.85	457	807
Late	25	35.2	20.9	10	18.05	433	890

Tmax: max. temp. (^oC); Tmin: min. temp. (^oC); Tbase: base temp. (^oC); GDD is growing degree days
Source: Field data (2018/2019)

 

Table 4
Crop height and canopy ground cover

Season	Parameter	Phenological stage
		Initial	Development	Mid-season	Late season
2017/2018	Days	10	21	33	24
	Canopy cover (%)	15	45	92	90
	Crop height (cm)	18	43	62	86
2018/2019	Days	10	22	33	25
	Canopy cover (%)	16	47	90	91
	Crop height (cm)	17	45	64	89

 

Table 5
Treatment Descriptions

Treatment number	Treatment tag	Treatment Description
T1	V0F0M0	Zero deficit; full irrigation (100% ETo) at all crop growth stages (control)
T2	V20F0M0	20% ETo deficit (vegetative stage); full irrigation (flowering and maturity stages)
T3	V40F0M0	40% ETo deficit (vegetative stage); full irrigation (flowering and maturity stages)
T4	V60F0M0	60% ETo deficit (vegetative stage); full irrigation (flowering and maturity stages)
T5	V0F20M100	20% ETo deficit (flowering stage); full irrigation (vegetative and maturity stages)
T6	V0F40M0	40% ETo deficit (flowering stage); full irrigation (vegetative and maturity stages)
T7	V0F60M0	60% ETo deficit (flowering stage); full irrigation (vegetative and maturity stages)
T8	V0F0M20	20% ETo deficit (maturity stage); full irrigation (vegetative and flowering stages)
T9	V0F0M40	40% ETo deficit (maturity stage); full irrigation (vegetative and flowering stages)
T10	V0F0M60	60% ETo deficit (maturity stage); full irrigation (vegetative and flowering stages)

ETo: Reference evapotranspiration; V, F, M are the vegetative, flowering and maturity stages, respectively
Source: Field survey (2017/2018, 2018/2019)

 

The data were inputted into the Food and Agriculture Organization (FAO) CropWat 8.0 model which computes the ETo based on the FAO Penman-Monteith evapotranspiration equation (Equation 3), widely accepted for calculating ETo (FAO, 2024).

where ET_o is reference evapotranspiration (mm day^-1); R_n is net radiation at the crop surface (MJ m^-2 day^-1); G is soil heat flux density (MJ m^-2 day^-1); T is air temperature at 2 m height (^ºC); u₂ is wind speed at 2 m height (m s^-1), e_s is saturation vapour pressure (kPa); e_a is actual vapour pressure (kPa); (e_s – e_a) is saturation vapour pressure deficit (kPa); D is slope vapour pressure curve (kPa ^ºC^-1); g is psychrometric constant (kPa ^ºC^-1).

Soil moisture measurements

A conductive soil moisture meter with a 60 cm long probe was calibrated for use in monitoring the soil moisture contents all through the irrigation seasons. The field calibration involved the volumetric measurement of soil moisture contents corresponding to each moisture value read off by the instrument, to develop a relationship – an equation to correct the sensor measurements (Equation 4).

Vol. MV = 2.5082 MMR

(4)

where MV = Moisture value; MMR = Moisture meter reading

The soil moisture contents for each treatment were monitored every three days throughout the crop growing season by taking moisture measurements in each replication, within the soil profile depths as follows: 0-15 cm, 15-30 cm, 30-45 cm, and 45-60 cm. The effective rooting depth for determinate tomatoes has been estimated to be 0.60 m (Keller and Karmeli, 1974; Water Conservation Factsheet, 2002). The soil moisture measurements were taken immediately before irrigation and one hour after irrigation (Abendipour, 2016), at a distance of 15cm from the emitting point (Ismail et al., 2007).

Estimation of actual crop evapotranspiration

The actual crop evapotranspiration or seasonal crop water use (ETc) was calculated using the soil water balance approach (Equation 5):

Vol. MV = 2.5082 MMR

(4)

where MV = Moisture value; MMR = Moisture meter reading.

The soil moisture contents for each treatment were monitored every three days throughout the crop growing season by taking moisture measurements in each replication, within the soil profile depths as follows: 0-15 cm, 15-30 cm, 30-45 cm, and 45-60 cm. The effective rooting depth for determinate tomatoes has been estimated to be 0.60 m (Keller and Karmeli, 1974; Water Conservation Factsheet, 2002). The soil moisture measurements were taken immediately before irrigation and one hour after irrigation (Abendipour, 2016), at a distance of 15cm from the emitting point (Ismail et al., 2007).

Estimation of actual crop evapotranspiration

The actual crop evapotranspiration or seasonal crop water use (ETc) was calculated using the soil water balance approach (Equation 5):

where ETc is the actual crop evapotranspiration (mm day^-1); I is the irrigation depth (mm); P is the precipitation (mm); D is deep percolation loss; R is runoff (mm) and ΔSW is the change in soil water storage within the profile depth of 0-60 cm. During the study, there was no rainfall (P = 0), no runoff and no deep percolation loss as drip irrigation was used (R = 0; D = 0). Hence, Equation (6) reduces to the form:

As there was no soil profile contribution, the water table depth below the ground surface being above 3 m, ETc was computed as the soil moisture values measured between successive irrigations (Equation 7) (Michael, 2009):

where ETc is the mean daily crop water use between successive soil moisture observations (cm/day); (GMC_1i – GMC_2i) is change in gravimetric soil moisture content (g/g) between two measurement dates in the i_th soil layer; Ai is Bulk density of i^th layer of sampled soil; D_i is depth of i^th layer (mm); n is number of soil layers sampled; t is number of days between successive soil moisture content sampling.

Crop coefficients (Kc)

The single crop coefficient method was used, whereby crop transpiration and soil evaporation effects are combined into a single value. Given the reference evapotranspiration (ETo) and actual crop evapotranspiration (ETc), the crop coefficient was computed as given in Equation (8) (Allen et al., 1998).

where Kc is the crop coefficient; ETo is the reference evapotranspiration for the experimental year (mm), and ETc is the actual crop water use (mm). The Kc for each crop growth stage was calculated by taking the averages of the coefficients every three days throughout the growth cycle.

Water use–yield relationship

The Stewart model (Cheng et al., 2016; Stewart and Hagan, 1973; Wang et al., 2017) was used in determining the relationship between the crop water use and yield, with relative yield reduction and relative water use being dimensionless parameters. The yield response to evapotranspiration represents the yield losses as affected by reduction in evapotranspiration. The slope of the relationship between decrease in yield and the unit decrease in crop water use (ET) is the yield response factor (Ky) expressed as Equation (9) (Doorenbos and Kassam, 1979; Vaux and Pruitt, 1983).

where Ky is the yield response factor, Ya is the actual yield, Ym is the maximum yield, ETa is the actual evapotranspiration, ETm is the maximum evapotranspiration.

Statistical analyses

The variances among the means of the fruit yield and crop water use (evapotranspiration) were statistically compared by means of an ‘analysis of variance (ANOVA)’ using the MINITAB analytical software, and the specific differences among pairs of means were evaluated by means of the Duncan’s multiple range test (DMRT) 0.05 probability level.

 

RESULTS AND DISCUSSION

Crop coefficients (K_c) due to full and deficit irrigation

The crop coefficients of the tomato crop irrigated with 100% ETo at all the growth stages and those irrigated below 100% ETo at specific growth stages in the two seasons – 2017/2018 and 2018/2019 (pooled) are shown in Table 6.

T₁ is the full irrigation treatment while T₂ to T₁₀ are the deficit treatments. The tomato cultivar had an 88 day-after-transplanting (DAT) growing cycle which was partitioned as initial, development, mid-season and late stages, equivalent to 10, 21, 33 and 24 days, respectively.

Crop coefficients under full irrigation

Under full irrigation the mean Kc values corresponding to each of the initial, development, midseason and late stages, in that order, are: 0.57, 0.73, 0.99 and 0.79. The observed Kc trend in the tomato growth cycle was such that Kc values are lowest at the periods just after transplanting up to crop establishment. These are designated Kc_initial. Thereafter, Kc increased at the development stage with increase in canopy cover until it attained the peak value at mid-season and remained so up to maturity. This is the Kc_mid. Thereafter, Kc decreased from maturity stage up to harvesting (late stage or end of season), and that is the Kc_end. This trend is common for most agricultural crops (Cerekovic et al., 2010; Doorenbos and Pruitt, 1977; FAO, 2021). The mean Kc value (Kc_mean) in the full irrigation treatments across all the phenological stages is 0.83.

 

Table 6
Pooled values of Kc for the phenological stages

Treatment	Parameter	Growth stage (Days)
		Initial (10)	Development (21)	Mid-season (33)	Late (24)	Seasonal (88)
	ETo (mm)	56.1	116.3	192.9	149.7	551
T1 (V0F0M0)	ETc (mm)	32.0	84.3	190.4	118.9	425.6
	Kc	0.57	0.73	0.99	0.79	0.83
T2 (V20F0M0)	ETc (mm)	30.8	80.9	187.5	110.9	410.1
	Kc	0.55	0.70	0.97	0.74	0.80
T3 (V40F0M0)	ETc (mm)	28.6	73.4	185.5	100.9	388.4
	Kc	0.51	0.63	0.96	0.67	0.75
T4 (V60F0M0)	ETc (mm)	26.3	65.2	170.4	91.6	353.3
	Kc	0.47	0.56	0.88	0.61	0.69
T5 (V0F20M0)	ETc (mm)	31.9	79.6	187.1	110.2	408.8
	Kc	0.57	0.69	0.97	0.74	0.79
T6 (V0F40M0)	ETc (mm)	28.1	71.9	178.8	99.1	377.9
	Kc	0.50	0.62	0.93	0.66	0.73
T7 (V0F60M0)	ETc (mm)	25.8	63.6	158.1	96.1	343.6
	Kc	0.46	0.55	0.82	0.64	0.67
T8 (V0F0M20)	ETc (mm)	28.0	76.0	179.4	96.6	380.0
	Kc	0.50	0.66	0.93	0.65	0.74
T9 (V0F0M40)	ETc (mm)	27.9	73.0	171.0	87.2	359.1
	Kc	0.50	0.63	0.89	0.58	0.70
T10 (V0F0M60)	ETc (mm)	27.4	68.1	154.3	74.1	323.9
	Kc	0.49	0.59	0.80	0.49	0.63

 

This is the unified Kc for irrigation scheduling for this cultivar regardless of irrigation deficit. The mean Kc was higher in 2018/2019 season than 2017/2018 season by 0.03, equivalent to 4% increase; this is not significant. The Kc values for both seasons, therefore, depict an established trend for the cultivar in the study area and are adaptable in new locations and climes with similarities in evapotranspiration as Kc values differ largely with the crop cultivar characteristics (Dutta et al., 2016) and to some extent with climate (Fernandández et al., 2000).

Crop coefficient (K_c) at initial growth stage

The Kc value for the initial stage (0.57) is within the range given by Jabow et al. (2013); less in value than those of Ahmed et al. (2020) and Zakari et al. (2019); and more than the values presented by FAO (2021). It has been reported that Kc differs from one region to the other (Ko et al., 2009) and the differences are attributable primarily to specific cultivar or variety, the changes in local climatic conditions, and seasonal differences in the crop growing patterns (Allen et al., 1998). Environmental conditions across regions vary and lead to differences in crop development stages and varietal selection, which in turn affect Kc values (Allen et al., 2005)

Crop coefficient value at crop development stage

For the crop development stage, the crop coefficient was computed as 0.73 in both seasons. It is within the range obtained by FAO (2021) (Kc = 0.70–0.80), but lower than that presented by Dirirsa et al. (2017) (Kc = 0.86), Ahmed et al. (2020) (Kc = 1.09), and Zakari et al. (2019) (Kc = 0.81). As pointed out earlier, Kc variation even for same crop is due to a number of factors of which difference in growing conditions is key. This is corroborated by Doorenbos and Pruitt (1977) and Zakari et al. (2019).

Crop coefficients (K_c) at mid-season

The midseason recorded the highest Kc values of 0.99 for the two seasons. This period corresponded with the flowering period to the start of maturity (including bloom, fruit-set and the majority of fruit sizing) and represents the period of maximum canopy coverage. The Kc value is slightly less than those of Hanson and May (2006a), Jabow et al. (2013), Dirirsa et al. (2017), Zakari et al. (2019), Ahmed et al. (2020), FAO (2021), which are within the range 1.02-1.25. They are, however, similar to the values obtained by Hanson and May (2006 b) (Kc = 0.96, 0.99) in a two-year trial (2001, 2003) out of four (2001-2004); and higher than the mid-season Kc value obtained by Amayreh and Al-Abed (2005) (Kc = 0.82) under surface drip irrigation and black mulch. While the FAO Kc values are generalized and recommended across different climatic conditions, the Kc values obtained in this study reflect the effect of the tomato cultivar, drip irrigation system, the crop management practices adopted and the environment under which the study was carried out. It has been established that different cultivars of same crop may have different crop water use and evapotranspiration pattern, hence the variation of Kc from one region to the other (Abedinpour, 2015, 2016). The Kc values obtained herein are required for appropriate estimation of the crop water requirements, and hence, efficient irrigation of tomato crop which is a major fruit vegetable grown on economic scale in Northwest Nigeria. Kc at mid-season is considered for irrigation system design as it is normally the highest Kc value obtained for irrigated crops (Herrarte, 2020). This is so because the capacity of the irrigation system should be such as will be able to provide the adequate quantity of water at the adequate time, and frequency, whenever the demand is peak, so that there can be assurance of water application throughout the entire crop phenological cycle. In other words, the irrigation system must be able to supply the peak water demand, which is determined for the maturity stage in the most critical period of the year, in order to allow for maximum cop growth potential, yield and profitability. Based on the study the design Kc for UC 82B tomato in Afaka, Northwest Nigeria, and areas with climatic similarities, is 0.98–1.00. This can apply to other cultivars with physiological similarities.

Crop coefficients (K_c) at late season

In the late season, Kc values for the 2017/2018 and 2018/2019 seasons were 0.75 and 0.84, respectively, with mean value as 0.80. These Kc values and those of Zakari et al. (2019), Ahmed et al. (2020) and FAO (2021) are similar. The values are higher than those of Cerekovic et al. (2010) and Jabow et al. (2013) (Kc = 0.70 and 0.52, respectively) but lower than Kc (= 0.88) obtained by Dirirsa et al. (2017) in the late season.

Yield response factors

The mean changes in yield due to soil moisture stress levels at the various growth stages are shown in Tables 7a and 7b, for the 2017/2018 and 2018/2019 irrigation seasons, respectively.

There is a significant difference in the yield due to the moisture stresses at P(0.05). The highest yield reductions of 7.7 and 8.4 tha^-1 occurred in the first and second seasons, respectively, when 60% ETo moisture deficit was administered during the maturity stage while the least yield reductions of 0.6 and 0.5 tha^-1 occurred in the 2017/2018 and 2018/2019 seasons, respectively, when 20% ETo moisture deficit was administered during the vegetative stage. The mean tomato yield response to soil moisture stress (yield response factor, Ky) for each of the two seasons, obtained as the slope of the linear relationship between seasonal yield reduction 

and the associated seasonal crop water use deficit

at the various growth stages are presented in Figure 2 and Figure 3.

The general trend showed that the yield decreased in response to increasing water deficits, that is, Ky increased as water deficits increased. This corroborates previous researches that deficit irrigation depresses tomato fruit yield due to soil moisture stress conditions (Cui et al., 2020; Patanè et al., 2011).

The Ky values based on the different treatments of varied water application depth on growth-stage basis were obtained as 1.26 and 1.30 in the 2017/2018 and 2018/2019 seasons, respectively. The mean Ky for both seasons was 1.28. The implication, therefore, is that the tomato cultivar is exhibits high sensitivity to soil moisture deficits and that moisture stress exacerbates the effect of moisture reduction on yield, leading to proportionally greater losses.

 

Table 7a
Yield response to growth-stage-based deficit irrigation (2017/2018)

Moisture stress imposed at:	Treatment	Ya (tha-1)	∆Y	Ym (tha-1)	ETa (mm)	ETm (mm)	1-(Ya/Ym)	1-(ETa/ETm)
None	T1 (V0F0M0)	18.5a	0.0	18.5	397.0a	397.0	0.00	0.00
Vegetative stage	T2 (V20F0M0)	17.9b	0.6		391.0b		0.032	0.015
	T3 (V40F0M0)	17.8bc	0.7		385.0c		0.038	0.030
	T4 (V60F0M0)	17.5cd	1.0		367.0d		0.054	0.076
Flowering stage	T5 (V0F20M0)	17.4d	1.1		371.0d		0.060	0.066
	T6 (V0F40M0)	17.1e	1.4		360.0e		0.076	0.093
	T7 (V0F60M0)	16.4f	2.1		343.0f		0.11	0.136
Maturity stage	T8 (V0F0M20)	15.4g	3.1		337.0g		0.17	0.151
	T9 (V0F0M40)	15.3g	3.2		323.0h		0.17	0.186
	T10 (V0F0M60)	10.8h	7.7		312.0i		0.42	0.214
	SE± Significance	0.756 **			1.922 **

Mean values followed by same letter(s) within a column are not statistically different (P = 0.05) based on DMRT. ** = highly significant at P ≤ 0.01

 

Table 7b
Yield response to growth-stage-based deficit irrigation (2018/2019)

Moisture stress imposed at:	Treatment	Ya (tha-1)	∆Y	Ym (tha-1)	ETa (mm)	ETm (mm)	1-(Ya/Ym)	1-(ETa/ETm)
None	T1 (V0F0M0)	19.5a	0.0	19.5	390.0a	390.0	0.00	0.00
Vegetative stage	T2 (V20F0M0)	19.0a	0.5		385.0b		0.026	0.013
	T3 (V40F0M0)	18.4b	1.1		369.0c		0.056	0.054
	T4 (V60F0M0)	17.7cd	1.8		354.0d		0.092	0.092
Flowering stage	T5 (V0F20M0)	18.3b	1.2		365.0c		0.062	0.064
	T6 (V0F40M0)	18.1bc	1.4		356.0d		0.072	0.087
	T7 (V0F60M0)	17.1d	2.4		336.0e		0.123	0.139
Maturity stage	T8 (V0F0M20)	17.1d	2.4		333.0e		0.123	0.146
	T9 (V0F0M40)	15.9e	3.6		328.0f		0.185	0.159
	T10 (V0F0M60)	11.1f	8.4		298.0g		0.431	0.236
	SE± Significance	0.711 **			1.580 **

Mean values followed by same letter(s) within a column are not statistically different (P = 0.05) based on DMRT. ** = highly significant at P ≤ 0.01

 

 

 

The mean Ky value (1.28) is more than the generalized Ky for tomato (1.05) (Doorenbos and Kassam, 1979) which has been adopted worldwide for a wide range of applications (Smith and Steduto, 2012). Zakari et al. (2019) obtained Ky value of 0.85 for same tomato cultivar (UC 82B) at Kano, Nigeria, with mean yield of 11.4 t/ha, under ‘no mulch’ condition, using basin irrigation system.

Differences in Ky values are fundamentally due to irrigation methods employed, hence, the water application efficiency, environmental factors, agronomic management practices, severity of water stress, growth stage at which water stress is imposed and cultivar differences (Celebi, 2014; Cui et al, 2020; Shrestha et al., 2010). Doorenbos and Kassam (1979) classified crops with Ky above 1.15 as being highly sensitive to moisture stress. By this criterion, the UC 82B tomato cultivar grown in Afaka Kaduna, Northwest Nigeria has high sensitivity to water deficiency due to the determined Ky value (1.28) for the entire growth stages.

As maintained by Kirda (2002), increasing the irrigated areas of crops having Ky above 1.15 with the water saved by restraint will not compensate for any yield loss on such crops. Generally, tomato has been classified as a C-3 crop (Eriksen et al., 1981), characterized by a reduced capacity to withstand short-term drought stress (Hura et al., 2007), thus leading to economic yield loss. Onwuegbunam et al. (2023) recommended full irrigation throughout the entire crop growth stages for UC 82B tomato in the study area as the economic gains from cultivation of additional land with saved water was negligible under deficit irrigation, the cash inflow being outweighed by the cash outflow.

 

CONCLUSIONS

Based on the mean crop coefficient (Kc) value of 0.83 across the entire crop cycle, UC 82B tomato requires about 83% of the reference evapotranspiration rate. The crop coefficients obtained at each phenological stage fall within several other values obtained in other studies for a wide variety of tomatoes. With the adopted irrigation strategy, the water stress was moderate during the vegetative stage, high during flowering, but severe during the maturity stage. More frequent irrigations will be required at the maturity stage considering the crop water need at this stage as depicted by the growth-stage Kc.

The yield response factor (Ky) being 1.28 implies that the cultivar has higher sensitivity to soil moisture stress than the generalized Ky for tomato (1.05) which has been adopted worldwide for a wide range of applications. The very high Ky values imply that increasing the irrigated areas with the water saved by deficit application would not compensate for the yield loss on the tomato cultivar. Under limiting water conditions, therefore, mild deficit irrigation during both vegetative and flowering stages, and full irrigation strategy during the maturity stage (from fruit set to fruit maturity) are recommended for UC 82B tomato, and other determinate cultivars with similar physiology.

 

Author contributions: Conceptualization: DOO and HEI; Methodology: DOO, MAO and HEI; Analysis: HI and MAO; Investigation: DOO and IJM; Re-sources: DOO and IJM; Data curation: DOO; Writing: DOO; Review: HI and MAO; Supervision: MAO, HEI and HI. All authors declare that they have read and approved the publication of the manuscript in this present form.

Data availability: The data supporting the findings of the research are available upon request from the lead authors.

Funding: There was no external funding for this study.

Acknowledgment: The authors acknowledge the Federal College of Forestry Mechanization, Afaka, Kaduna, Nigeria, for facilitating the use of their experimental areas for this research.

Conflicts of interest: Authors declare that there are no conflicts of interest.

 

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