Skip to content
BY 4.0 license Open Access Published by De Gruyter Open Access April 6, 2022

Soil test-based phosphorus fertilizer recommendation for malting barley production on Nitisols

  • Kassu Tadesse EMAIL logo , Birhan Abdulkadir , Wubengeda Admasu , Dawit Habte , Almaz Admasu , Amare Tadesse and Anbessie Debebe
From the journal Open Agriculture

Abstract

Malting barley production in the Southeastern highlands of Ethiopia relied on almost a blanket phosphorus (P) fertilizer recommendation regardless of the diverse fertility status of the soil. This study was, therefore, conducted in Lemu–Bilbilo district at 24 fields for two cropping seasons to provide farmers with P fertilizer recommendations based on soil fertility status and to enhance malting barley production. The experiment comprised six levels of P fertilizer (0, 10, 20, 30, 40, and 50 kg P ha−1) arranged in a randomized complete block design with three replications. The critical concentrations for soil P levels were found above 13 mg P kg−1 for Olsen and 16 mg P kg−1 for Bray II, and were sufficient for malting barley production on Nitisol of the study area and other similar agro-ecologies. The mean P-requirement factors were 5.80 and 6.10 mg P kg−1 for Olsen and Bray II, respectively. Results further revealed that P fertilization, at a rate of 30 kg ha−1, gave 10 and 73% more grain yields of malting barley compared to the existing recommendation, 20 kg P ha−1, and treatment with no P fertilizer, respectively. Such information can be used as a guideline for soil-specific P fertilizer recommendations to increase the productivity of malting barley in the study area and other similar agro-ecologies, where soil test studies were not conducted.

1 Introduction

The fundamental cause for the declining per capita food production in Sub-Saharan Africa is soil fertility depletion among smallholder farms [1]. This is true in the highlands of Ethiopia too due to population pressure, unsuitable land-use system, inadequate soil and water conservation, expansion of cropping to marginal lands, and poor soil management practices [2,3].

The farming system of the Ethiopian highlands is significantly dominated by monocropping, where cereals occupied 81% of the total grain cropped land [4]. In these highland areas, teff (Eragrostis tef L.), maize (Zea mays L.), Sorghum (Sorghum bicolor L.), wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) are the most dominant cereals under production [4]. Along with other factors, these monocropped cereals have contributed to the depletion and imbalance of important plant nutrients in the soil.

Barley has a wide range of adaptation to altitudes of over 3,000 m a.s.l. [5]. In terms of area coverage, barley is the fifth important cereal crop in Ethiopia next to teff, maize, sorghum, and wheat, and third after wheat and teff in the Arsi zone, where this study was conducted [4]. Although the number of smallholder farmers growing barley in the country and its production increased from 3.47 to 4.17 million and 1.08 to 2.03 million tons during the last 14 years (2004–2017) respectively, due to the ever-growing demand for food and raw material for industry, its national mean yield is still limited to 2.16 t ha−1 (2004–2017) [4]. Compared to the global average (3.1 t ha−1) and top producing countries such Germany (6.9 t ha−1) [6], the mean national yield of the country was still low. The low yield of barley was principally ascribed to the depletion of soil fertility as a consequence of continuous nutrient uptake by the crops, application of suboptimal chemical and/or organic fertilizers, and limited use of legumes in the cropping system [7,8]. In 2017, for example, only 65,175 tons of fertilizer was used to nourish barley sown on 951,993 ha of land in the country indicating the rate of fertilizer used (68 kg ha−1) was lower compared to the existing blanket recommendation, which was 100 kg ha−1 [9].

Farmers in the study area had a better practice of using fertilizers as an important input to replenish soil fertility and obtain higher yields. For instance, in 2015, they applied 6,877 tons of fertilizer on 91,824 ha of land (75 kg ha−1) covered with barley implying better adoption of external inputs compared to the national average [10]. However, they fertilized their farms uniformly despite the differences among soil types and fertility statuses, which implies the inadequacy of soil test-based fertilizer studies. The existing fertilizer recommendation for malting barley production was 18–20 kg N–P kg ha−1 throughout the study area regardless of soil fertility conditions.

Therefore, soil test-based recommendations, which consider soil fertility statuses, are required for efficient fertilizer utilization and malting barley production. To increase agricultural productivity, the results of soil tests need to be calibrated or correlated against crop responses due to the application of important plant nutrients [11,12]. For accurate soil test interpretation, knowledge of the relationship between the number of nutrients extracted by a given soil test method and the number of plant nutrients that should be added to achieve optimum yield for each crop is required [11,13]. The objective of this study was, therefore, to establish soil test-based phosphorus fertilizer recommendations for malting barley production on Nitisols that serve as a guideline to farmers by conducting sufficient numbers of soil test-based field correlation and calibration studies.

2 Materials and methods

2.1 Description of the study area

This study was conducted at Lemu–Bilbilo district of Arsi zone in the southeastern highlands of Ethiopia, which is located 230 km southeast of the capital city of Ethiopia, Addis Ababa. The study sites are located at 7°26′39.3″–7°35′16.5″ N latitude and 39°13′45.6″–39°17′40.2″ E longitude, at an altitude ranging from 2,634 to 3,105 m a.s.l. The agroecology of the Lemu–Bilbilo district is categorized as humid [14]. The dominant soil type of the study area is Nitisol [15]. The study area has extended rainy season, which starts in March and continues till October. The area has a mean annual precipitation of 1,066 mm with the highest rainfall concentrations occurring in June, July, and August. The mean minimum and maximum annual temperatures of the area are 9.6 and 23.9°C, respectively. November is the coldest month with a temperature of 8.3°C while March is the hottest month with a temperature of 25.8°C.

The study was conducted at 24 fields for 2 main growing seasons from 2011 to 2012. Each year, the experiments were conducted on different sites, which previously had been sown with wheat or barley.

2.2 Soil sampling and analysis

To select representative experimental sites in the study area, 72 composite soil samples were collected from the fields at a depth of 0–15 cm, where wheat or barley was the dominant precursor crop. The soils from each site were composited into a single sample, air-dried, ground to pass a 2 mm sieve, and analyzed for the potential of hydrogen (pH) and available soil phosphorus (P). The pH and available P were determined using a ratio of 2.5 ml water to 1 g soil [16] and Mehlic method [17], respectively at the soil and plant nutrition laboratory of Kulumsa Agricultural Research Center (KARC). Among the sampled sites in the study area, 24 farmers’ fields were finally chosen for this experiment. The experimental fields were classified into low, medium, and high P groups based on the determined values. The soil (P) values considered for categorization of the ranges based on Mehlic extraction methods were <20, 21–40, and >41 mg P kg−1 for low, medium, and high, respectively (Table 1). Reliant on this classification, 21 and 3 sites were within low and medium available P ranges, respectively. Among the 24 experimental sites, 2 with low P values in the first year were later dropped due to very poor crop performance, and only 22 sites were considered in the final harvesting, data analysis, and interpretation.

Table 1

Initial soil phosphorous statuses of the soil according to Mehlic method for sites selected at Lemu–Bilbilo district of Arsi zone

Year Testing sites pH Avail. P (mg kg−11) Category Year Testing sites pH Avail. P (mg kg−1) Category
2010 Site 01 4.9 21 Medium 2011 Site 13 4.7 15.3 Low
2010 Site 02 5 18 Low 2011 Site 14 4.9 15.3 Low
2010 Site 03 5.2 14 Low 2011 Site 14 4.9 12.7 Low
2010 Site 04 5.4 16.7 Low 2011 Site 16 5 14.7 Low
2010 Site 05 5.2 21 Medium 2011 Site 17 5.1 20 Low
2010 Site 06 4.7 23 Low 2011 Site 18 4.9 19.7 Low
2010 Site 07 4.9 15 Low 2011 Site 19 5 16.7 Low
2010 Site 08 5.4 22 Medium 2011 Site 20 5.2 17.2 Low
2010 Site 09 5.1 16.7 Low 2011 Site 21 5.1 19 Low
2010 Site 10 5.2 18 Low 2011 Site 22 5.3 16 Low
2010 Site 11 5.3 20 Low 2011 Site 23 4.7 18.3 Low
2010 Site 12 5.2 16.7 Low 2011 Site 24 4.7 15.3 Low

For the correlation study, 462 composite soil samples were also collected from each plot at a depth of 0–15 cm three weeks after sowing, and analyzed for available soil P. The available soil P for the correlation study was determined using both Olsen and Bray II methods at the soil and plant nutrition laboratory of Debreziet Agricultural Research Center.

2.3 Experimental setup and procedure

The experiment comprised six levels of P fertilizer (0, 10, 20, 30, 40, and 50 kg P ha−1) that were laid out in a randomized complete block design with three replications. The seedbeds were plowed 4× using traditional plow, locally called maresha, drawn by ox before sowing. All experimental plots at each site were sown during the first two weeks of July in both years with two-row malting barley (cv. Holker) at the recommended seed rate of 125 kg ha−1. Seeds were drilled by hand at 0.20 m spacing between rows for all sites in plot sizes of 4 m by 4 m. The spacing between plots and replications was 0.5 and 1 m, respectively. The P fertilizer was side-banded close to seeds in all rows based on the treatment setup at sowing from triple superphosphate while the recommended rate of nitrogen (N) fertilizer (18 kg N ha−1) was uniformly applied to all plots including the control in splits, half at sowing and the remaining half at tillering from urea. Weeds were controlled manually. Pesticides, namely fenitrothion (ethiotrothion 50% EC) and propiconazole (Tilt 250 EC) were applied against shoot fly and scald, respectively.

2.4 Data collection

The agronomic parameters measured (computed) for the malting barley were stand count, tillers plant−1, plant height, spike m−2, grain and above-ground total biomass yields, and thousand kernel weight. Malting barley stand density was determined 4 weeks after emergence by counting the number of plants grown in 0.5 m row length from 10 randomly selected rows within each plot. Data on the number of tillers were recorded by counting tillers in 10 representative plant samples from each plot. The height of 10 plants in each plot at random was measured at physiological maturity from the soil surface to the apex of the spike. The number of spikes m−2 was determined from 0.5 m row sample randomly chosen from the middle 10 rows of each plot just before harvesting.

When the crop physiologically matured, the harvesting was carried out from the net plot area of 4 m2 (2 m by 2 m) by hand. The harvested samples were air-dried to constant moisture content, threshed manually, cleaned and the grain weights recorded. The weighed samples were adjusted to 12.5% moisture content and converted to kg ha−1 for statistical analysis. The harvest index was calculated as a percentage ratio of grain yield to biological yield. The grains were randomly collected from the cleaned samples of each plot and their respective kernel weights were determined using a seed counter device in the physiology laboratory of KARC.

2.5 Determination of critical P concentrations (PC)

Critical P values were determined following the Cate–Nelson graphical method [18], where soil P values were put on the X-axis and the relative yield values on the Y-axis. The relative malting barley grain yields in percent, which is the relationship between malting barley grain yield response to P fertilizer rates, were calculated for each of the 22 sites using equation (1):

(1) Relative yield ( % ) = Yield Maximum yield 100 .

The Cate–Nelson graphical method was employed to determine the critical P concentration. The Cate–Nelson graphical method was based on dividing the XY scatter diagram into four quadrants and maximizing the number of points in the positive quadrants while minimizing the number of points in the negative quadrants [18]. This was done by overlaying a clear plastic sheet having a pair of perpendicular lines drawn on it to produce four quadrants, roughly of the same relative size. The intersecting lines were positioned on and moved about horizontally and vertically on the graph, always with the two lines parallel to the two axes on the graph, until the number of points in the two positive quadrants was at a maximum or conversely, the number of points in the negative quadrants was at a minimum. A pair of intersecting perpendicular lines was drawn to divide the data into four quadrants. The vertical line defines the responsive and non-responsive ranges. The observations in the upper left quadrant overestimate the fertilizer P requirement while the observations in the lower right quadrant underestimate the fertilizer requirement. The point where the vertical line crosses the X-axis was defined as the optimum critical soil test level, which is critical P concentration [18].

2.6 Determination of P requirement factor (Pf)

The P requirement factor (Pf) is the quantity of P in kilogram required per hectare to raise the soil test by 1 mg kg−1. It is used to determine the amount of fertilizer required per hectare to bring the level of available P above the critical value [18]. The Pf was calculated using available P values in the soil samples collected from fertilized and unfertilized plots as shown in equation (2):

(2) P f = kg P applied Δ Soil P

The rate of P fertilizer to be applied (Pa) was calculated from the critical P concentration (PC), initial soil P values for the site (Pi), and P requirement factor (Pf) using equation (3).

(3) P a = ( P c P i ) × P f .

2.7 Data analysis

Analysis of variance (ANOVA) was carried out for each of the measured (computed) parameters using the procedure of SAS statistical package version 9.0 [19] as described by Gomez and Gomez [20]. All yield, yield component, and soil data were subjected to ANOVA using PROC ANOVA of SAS version 9.0 statistical software [19]. The significances of differences among treatment means were compared using the least significant difference (LSD) test at 5% level of probability.

3 Results

3.1 Plant growth, yield, and yield components

The ANOVA over seasons and sites indicated that P fertilizer rates significantly (p < 0.001) affected most of the variables measured for malting barley including plant population, number of tillers plant−1, plant height, kernel weight, grain, and biomass yields (Table 2). The result further indicated that season was also a large source of variation for most of the variables measured except for plant height (data not shown). There were no significant interaction effects of P fertilizer rates and season (Table 2).

Table 2

ANOVA table for the effects of phosphorous fertilizer rate, year their interaction on the yield and yield components of malting barley across sites

Effect Yield and yield components parameters
Seedling density (No) No. of tillers plant−1 Spike m−2 (No) Plant height (cm) Grain yield (kg ha−1) Biomass yield (kg ha−1) Kernel weight (mg)
Phosphorous (P) ** *** *** *** *** *** ***
Year (Y) *** *** *** ns *** *** ***
P*Y ns ns ns ns ns ns Ns
Mean 125.04 4.8 192.38 90.97 2824.61 6817.13 44.12
CV 20.53 20.57 19.77 9.46 23.98 23.08 9.99
LSD (P) 14.64 1.97 2.01 1.97 281.02 701.63 1.89
LSD (Y) 11.83 0.22 20.45 1.86 152.31 406.29 1.02

ns – not significant at 0.05 probability level; **, *** – significant at 0.01 and 0.001 probability levels, respectively.

The grain and biomass yields of malting barley were significantly (p < 0.001) affected by the application of P (Table 2). The highest grain (3,450 kg ha−1) and biomass (8,231 kg ha−1) yields of malting barley were obtained from the application of 40 kg P ha−1. However, it was not statistically different from the applications of 30 kg P ha−1 (3,178 and 7,637 kg ha−1, respectively) and 50 kg P ha−1 (3,293 and 8,152 kg ha−1, respectively). The lowest grain (1,993 kg ha−1) and biomass (5,103 kg ha−1) yields of malting barley were obtained from unfertilized plots (Figure 1a and b).

Figure 1 
                  Effect of phosphorous fertilizer rate on the grain (a) and biomass (b) yields of malting barley.
Figure 1

Effect of phosphorous fertilizer rate on the grain (a) and biomass (b) yields of malting barley.

The kernel weight, number of spikes, plant height, and number of tillers plant−1 of malting barley were significantly (p < 0.001) affected by the amount of P fertilizer application (Figure 2a–d, respectively). The biggest kernel weight (46.26 mg; Figure 2a), the maximum number of spikes (234 plants m−2; Figure 2b), and tillers (6; Figure 2d) were obtained from the application of the highest P rate (50 kg P ha−1). However, the values of kernel weight (45.49 mg; Figure 2a) and the number of spikes (223 plants m−2; Figure 2b) at 50 kg P ha−1 were not significantly different from the application of 40 kg P ha−1. The application of P at a rate of 30 kg P ha−1 also resulted in a statistically equivalent number of spikes (220 plants m−2; Figure 2b). The highest height (96 cm; Figure 2c) was recorded from the application of P fertilizer at a rate of 40 kg ha−1 though it was not significantly different from the application of P fertilizer at a rate of 30 and 50 kg ha−1. The least seed weight (42.01 mg; Figure 2a), the lowest number of spikes (136 plants m−2; Figure 2b) and the number of tillers per plant (4; Figure 2d) as well as the lowest plant height (85 cm; Figure 2c) was obtained from the control plot with no P (Figure 2a–d, respectively).

Figure 2 
                  Effect of phosphorous fertilizer rate on kernel weight (a), population (b), plant height (c)  and number of tillers (d) of malting barley.
Figure 2

Effect of phosphorous fertilizer rate on kernel weight (a), population (b), plant height (c) and number of tillers (d) of malting barley.

3.2 Response of available soil phosphorus to P fertilizer rate

The available soil P extracted three weeks after sowing using both Olsen and Bray II methods showed statistically significant differences among the plots treated with different levels of P fertilizer. The highest available soil P was recorded from plots treated with 50 kg ha−1 (16.53 and 18.21 mg P kg−1 soil using Olsen and Bray II methods, respectively). The application of 40 kg ha−1 (15.54 and 16.59 mg P kg−1 soil using Olsen and Bray II methods, respectively) also gave statistically equivalent available soil P (Figure 3). The lowest available soil P was extracted from the control plot (9.04 and 10.93 mg P kg−1 soil using Olsen and Bray II methods, respectively) (Figure 3). The mean increase in available soil P values both in Olsen and Bray II methods over the unfertilized (control) plots are shown in Tables 3 and 4.

Figure 3 
                  Response of available soil phosphorus to P fertilizer rate.
Figure 3

Response of available soil phosphorus to P fertilizer rate.

Table 3

Determination of phosphorus requirement factors (Pf) for Olson method calculated, based on soil test P from different fertilizer rate treatments on malting barley on Nitisols of Lemu–Bilbilo district of Arsi zone

Phosphorus rate (kg ha−1) Soil test P (Olsen method, mg kg−1) P increase over control (mg kg−1) P requirement factor (Pf)
Range Average
0 6.80–11.40 9.04
10 8.21–12.68 10.86 1.82 5.49
20 10.20–16.56 13.24 4.20 4.76
30 10.90–17.70 14.12 5.08 5.91
40 10.97–18.58 15.54 6.50 6.15
50 12.85–22.32 16.53 7.49 6.68
Mean
5.02 5.80
Table 4

Determination of phosphorus requirement factors (Pf) for Bray II method calculated, based on soil test P from different fertilizer rate treatments on malting barley on Nitisols of Lemu–Bilbilo district of Arsi zone

Phosphorus rate (kg ha−1) Soil test P (Bray II method, mg kg−1) P increase over the control P requirement factor (Pf)
Range Average
0 8.75–13.56 10.93
10 9.07–15.23 12.99 2.07 4.83
20 9.87–16.87 14.37 3.44 5.81
30 10.00–20.88 15.98 5.06 5.93
40 10.20–21.00 16.59 5.66 7.07
50 13.00–25.25 18.21 7.28 6.87
Mean
4.70 6.10

3.3 Relationship between yield and soil analysis

3.3.1 Critical phosphorus concentration (PC)

The relationship between malting barley grain yield response to P fertilizer rates (relative yield) and the corresponding soil test P values extracted using both Olsen and Bray II methods for all P treatments (0–50 kg P ha−1) are shown in Figures 4 and 5. The critical P concentrations (PC) were determined from these scatter diagrams plotted using relative grain yields of malting barley and the corresponding soil test P values for all P levels. The determined PC values using the Cate–Nelson method in this study were 13 mg P kg−1 for Olsen and 16 mg P kg−1 for Bray II methods. The corresponding mean relative malting barley grain yield responses were about 89 and 88% for Olsen and Bray II methods, respectively (Figures 4 and 5).

Figure 4 
                     Scatter diagram showing the relationship between soil test P using Olsen method and relative yield of malting barley, and the critical P level.
Figure 4

Scatter diagram showing the relationship between soil test P using Olsen method and relative yield of malting barley, and the critical P level.

Figure 5 
                     Scatter diagram showing the relationship between soil test P using the Bray II method and relative yield of malting barley, and the critical P level.
Figure 5

Scatter diagram showing the relationship between soil test P using the Bray II method and relative yield of malting barley, and the critical P level.

3.3.2 Phosphorus requirement factor (Pf)

The overall result indicated that the application of different rates of phosphate fertilizer was reflected in the Pf, and soil test results could be used as a basis for fertilizer rate recommendations. The calculated Pf, which were used to calculate the total amount of P fertilizer required to bring the level of available P above the critical level, using values from plots that received different levels of P fertilizers (0–50 kg P ha−1) for both Olsen and Bray II methods are shown in Tables 3 and 4. The Pf values using the Olsen-P were, therefore, 5.49, 4.76, 5.91, 6.15, and 6.68 mg P kg−1 for plots treated with 10, 20, 30, 40, and 50 kg P ha−1, respectively. The corresponding Pf values using the Bray II-P were 4.83, 5.81, 5.93, 7.07, and 6.87 mg P kg−1 for plots fertilized with 10, 20, 30, 40, and 50 kg P ha−1, respectively. The calculated mean Pf for Lemu–Bilbilo district were, therefore, 5.8 mg P kg−1 for Olsen and 6.1 mg P kg−1 for Bray II (Tables 3 and 4).

3.3.3 P-Requirement factor as a basis for P fertilizer recommendation

The calculated amounts of P fertilizer required for the fields, where this experiment was conducted based on the P-requirement factor and Bray II method indicated that P fertilization was necessary for all of the sites because soil test P values were below the established critical level, 16 mg P kg−1. Hence, applications of P fertilizer ranging from 14.88 to 44.23 kg P ha−1 were required. Considering the average value for the entire Lemu-Bilbilo district, the mean phosphorus fertilizer requirement was 30.95 kg P ha−1 (70.89 kg P2O5 ha−1), which fitted well with the new agronomic recommendation, 30 kg P ha−1.

Similarly, applications of P fertilizers were also necessary for all of the 22 experimental sites based on the Olsen P method because soil test P values were below the established critical level, 13 mg P kg−1. Hence, applications of P fertilizer ranging from 9.28 to 35.96 kg P ha−1 were required. When the average value for the whole Lemu-Bilbilo district was considered, the mean P fertilizer requirement was 22.96 kg P ha−1 (52.59 kg P2O5 ha−1), which fitted well with the existing recommendation, 20 kg P ha−1.

4 Discussions

The P fertilization significantly enhanced the growth, yield, and yield components of malting barley. The grain and biomass yields of malting barley increased linearly in response to the application of P fertilizer up to 40 kg P ha−1 (Figure 1a and b). The non-significant result after 30 kg P ha−1 indicated that application of P at a rate of 30 kg ha−1 can be sufficient in the absence of soil test results. The grain yield advantages of 73, 59, 45, and 26% relative to the control were obtained due application of 10, 20, 30, and 40 kg P ha−1, respectively (Figure 1a). The corresponding biomass yield augmentation owing to the application of 10, 20, 30, and 40 kg P ha−1 were 61, 50, 36, and 15% against the control (Figure 1b). Compared to the existing recommendation, 20 kg P ha−1, application of 30 kg P ha−1, the current recommendation, resulted in 10% grain yield and 10% biomass yield advantages (Figure 1a and b). The result implies that the existing blanket recommendation for the study area, 20 kg P ha−1, was sub-optimal, and needs to rise to 30 kg P ha−1, which is the new agronomic optimum of this study, in areas where soil test-based P calibration results unavailable. Bekele et al. [2], Wakene et al. [21], Agegnehu and Lakew [22] and Sintayehu et al. [23] documented the positive effect of the application of P fertilizer on grain and biomass yields of malting barley.

As the rate of P increased, there were corresponding increases in kernel weight, number of spikes and tillers per plant as well as plant height indicating the significant role of P in plant growth and seed production. Increasing the level of P from 0 to 40 and 50 kg ha−1 resulted in 3.48 and 4.25 mg increments in kernel weight, respectively (Figure 2a).

Compared to the control, application of P at rates of 40 and 50 kg ha−1 gave 72 and 64% growths in plant population (Figure 2b), and 36 and 40% improvements in the number of tillers per plant (Figure 2d). This implies that P is very important in increasing the plant population by increasing the number of productive tillers of the crop. The contribution of P in increasing plant tillers was demonstrated by the significantly small number of tillers in non- and low-P treated plots (Figure 2d). The current result agrees with the finding of Wakene et al. [21], who reported that the number of fertile tillers of barley was significantly increased by P fertilizer application. Prystupa et al. [24] also indicated that the number of productive tillers plant−1 was significantly affected by N and P fertilizers application, where the maximum and lowest numbers of productive tillers were recorded from the highest and lowest (no) N and P fertilizer rates, respectively. Muhammad et al. [25] also reported similar results on wheat. Heluf and Mulugeta [26] observed similar increments in the number of panicles m−2 of rice plants due to the applied P fertilizer by enhancing the production of effective tillers.

Similarly, P-fertilization enhanced the plant height of the malting barley (Figure 2c). The application of P from 30–50 kg ha−1 brought 9–12% growths in plant height of malting barley. Muhammad et al. [25] also reported a similar result in wheat. Mengel and Kirkby [27] reported that phosphorus deficiency in small grains is usually expressed as stunted growth.

Generally, the available soil P increased linearly as the level of applied P fertilizer increased (Figure 3). The residual effect of P fertilization and consequently its vital role in enhancing malting barley yield could be testified by the mean increase in available soil P values both in Olsen and Bray II extraction methods over the unfertilized (control) plots. Compared to the control (no P), the available soil P left in the soil after harvesting of malting barley using Olsen extraction method augmented from 1.82–7.49 mg P kg−1, respectively due to application of P at rates of 10–50 kg ha−1 (Table 3). The corresponding increment using Bray-II extraction method for the same rate of P fertilizer application was 2.07–7.28 mg P kg−1, respectively (Table 4).

The determination of critical phosphorus concentration (PC) serves as a basic tool to make an informed decision whether to apply or not to apply P fertilizer to the soil. The Cate–Nelson method was employed to plot the scatter diagrams using both Olsen and Bray-II extraction methods. Thus, the critical P concentration (PC) values for the study area were 16 mg P kg−1 for Bray II and 13 mg P kg−1 for Olsen methods. The critical P concentrations of 10 mg P kg−1 using Olsen and 16 mg P kg−1 using Bray II test methods for wheat in the southeastern mid highland of Ethiopia on Haplic Luvisols and Eutric Vertisols were reported by Bekele et al. [2]. Agegnehu et al. [11] also reported 13.5 mg P kg−1 for malting barley and 13 mg P kg−1 for food barley, respectively using the Bray II test on Nitisols. The disparities in the critical P concentrations even on the same soils might have attributed to many factors such as the differences in crops and varieties, types and amounts of available soil nutrients, initial soil P, amounts of N fertilizer applied, climate especially temperature and rainfall, and standards and accuracies of soil testing laboratories.

When the initial available soil P is found below the determined critical soil P-value, P fertilizer is required to be supplied to achieve an optimum yield of malting barley. Thus, the rate of P fertilizer required per hectare for the study area and similar agro-ecologies, where soil test studies were not conducted could be calculated using the soil critical P concentration (PC), initial soil P determined for each site before sowing (Pi) and the P requirement factor (Pf) (equation (3)) to make P fertilizer rate recommendations. This helps to obtain a higher yield of malting barley by making use of optimum P fertilizer application, which in turn helps to avoid both under- and over-application of P fertilizer. The sub-optimal P fertilizer application avoids lower yields whereas the over-application of P fertilizer helps growers to save money by reducing the rate of fertilizer for lower marginal return and prevents environmental pollution due to leaching of excess P.

The current result is in agreement with Bekele et al. [2], who tested the Bray II and Olsen soil P extraction methods for different soil types in Ethiopia and found that the Bray II method was most appropriate for soils with pH < 6.5 and the Olsen method for soils with pH > 6.5. Bray II soil P extraction method best suited to this study area as it was conducted on Nitisol, where the soil pH was lower than 6.5. It also fitted the agronomic recommendation. However, in cases of inconveniences to extract soil P using the Bray II method, the Olsen soil P extraction method can be considered as an alternative by establishing a relationship with the Bray II method. In cases when extraction of soil P using both Bray II and Olsen methods are impossible, the new fertilizer recommendation, 30 kg P ha−1, can be employed as a guideline.

5 Conclusion

The result of this study indicated that phosphorus fertilization increased the productivity of malting barley on Nitisols of the southeastern highlands of Ethiopia. Application of phosphorus fertilizer at a rate of 30 kg ha−1 has been found agronomical optimum for increasing the yield and yield components of malting barley. The result further revealed that the existing blanket recommendation of 20 kg P ha−1 has been found sub-optimal in response to the ever-increasing soil fertility depletion of the study area. The critical P concentrations using the Cate–Nelson method were 13 mg P kg−1 for Olsen and 16 mg P kg−1 for Bray II extraction methods. The corresponding mean relative malting barley grain yield responses were about 89% and 88% for Olsen and Bray II extraction methods, respectively. The calculated P-requirement factors for Lemu–Bilbilo district were 5.8 mg P kg−1 for Olsen and 6.1 mg P kg−1 for Bray II extraction methods. The results can be used as a basis for soil test-based phosphorus fertilizer recommendations for improving the productivity of malting barley on Nitisol areas of southeastern Ethiopian highlands, and other similar agro-ecologies with no established values. To make use of the soil test-based fertilizer recommendations, the number and capacities of soil laboratories should be increased and strengthened.

Acknowledgments

We acknowledge Assela Malt Factory and four Brewing Industries for the provision of funding for the execution of this research activity. The authors are also thankful to Kulumsa Agricultural Research Center for the provision of logistics. All members of the Land and Water Resources Research team are gratefully acknowledged for their unreserved efforts for proper soil, crop, and data management.

  1. Funding information: This work was supported by Assela Malt Factory and four Brewing Industries, namely BGI (St. George), Harer, Bedele and Meta Abo.

  2. Author contributions: This study was carried out in collaboration among all authors. KT designed the study, carried out the field and laboratory works, supervised the experiments, performed the data analysis and wrote the original draft of the manuscript; BA designed the study, carried out the field and laboratory works, supervised the experiments, reviewed and edited the manuscript; WA carried out the field and laboratory works, supervised the experiments, reviewed and edited the manuscript; DH supervised the experiments, reviewed and edited the manuscript; AA, AT and AD carried out the field and laboratory works and supervised the experiments.

  3. Conflict of interest: The authors state no conflict of interest.

  4. Data availability statement: The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

[1] Bationo A, Lamers J, Lehmann J. Recent achievement of sustainable soil management in SubSaharan Africa. Nutr Cycl Agroecosyst. 2015;102:1–3.10.1007/s10705-015-9700-ySearch in Google Scholar

[2] Bekele T, Assen Y, Sertsu S, Gorfu A, Hassena M, Tanner DG, et al. Optimizing fertilizer use in Ethiopia: correlation of soil analysis with fertilizer response in Hetosa Wereda, Arsi zone. Addis Ababa, Ethiopia: Sasakawa-Global; 2002.Search in Google Scholar

[3] Okalebo JR, Othieno CO, Woomer PL, Karanja NK, Semoka JRM, Bekunda MA, et al. Available technologies to replenish soil fertility in East Africa. In: Bationo A, Waswa B, Kihara J, Kimetu J. editors. Advances in integrated soil fertility management in sub-saharan Africa: challenges and opportunities. Dordrecht, Netherlands: Springer; 1977. p. 45–62.10.1007/978-1-4020-5760-1_3Search in Google Scholar

[4] CSA (Central Statistical Agency of Ethiopia). Report on area and production of major crops for 2017/2018 (private peasant holdings, Meher Season). Addis Ababa, Ethiopia, Statistical Bulletin No. 532; 2018.Search in Google Scholar

[5] Bayeh M, Birhane L. Barley research and development in Ethiopia – an overview. In: Mulatu B, Grando S, editors. Barley Research and Development in Ethiopia. Aleppo, Syria: ICARDA/EIAR; 2011. p. 1–18.Search in Google Scholar

[6] FAOSTAT Statistical Database. Food and Agricultural Organization of United Nations, Rome, Italy: FAO. 2019.Search in Google Scholar

[7] Agegnehu G, Nelson PN, Bird MI. The effects of biochar, compost and their mixture and nitrogen fertilizer on yield and nitrogen use efficiency of barley grown on a Nitisol in the highlands of Ethiopia. Sci Total Env. 2016;569–570:869–79.10.1016/j.scitotenv.2016.05.033Search in Google Scholar PubMed

[8] Zeleke G, Agegnehu G, Abera D, Rashid S. Fertilizer and soil fertility potential in Ethiopia: Constraints and opportunities for enhancing the system. Washington DC, USA: International Food Policy Research Institute, IFPRI; 2010.Search in Google Scholar

[9] CSA (Central Statistical Agency). Report on Area and production of major crops for 2016/2017 (private Peasant Holdings, Meher Season). Vol. I. Addis Ababa, Ethiopia: Statistical Bulletin No. 584; 2017.Search in Google Scholar

[10] CSA (Central Statistical Agency). Report on farm management practices: Private peasant holdings, Meher season 2014/2015 (private Peasant Holdings, Meher Season). Vol. III. Addis Ababa, Ethiopia: Statistical Bulletin No. 578; 2015.Search in Google Scholar

[11] Agegnehu G, Nelson PN, Bird MI, van Beek C. Phosphorus response and fertilizer recommendations for wheat grown on nitisols in the central ethiopian highlands. Commun Soil Sci Plant Anal. 2015;46(19):2411–24.10.1080/00103624.2015.1081922Search in Google Scholar

[12] McKenzie RH, Kryzanowski L. Soil testing methods calibrated to phosphate fertilizer trials. Better Crop. 1997;81:7–19.Search in Google Scholar

[13] Watson M, Mullen R. Understanding Soil Tests for Plant-available Phosphorus. Ohio, USA: Ohio State University; 2007.Search in Google Scholar

[14] MoA (Ethiopian Ministry of Agriculture). Agro-ecological Zonation of Ethiopia. Addis Ababa, Ethiopia; Ministry of Agriculture; 2000.Search in Google Scholar

[15] IUSS Working Group WRB. World reference base for soil resources 2014: A framework for international classification, correlation and communication. World Soil Resources Reports No. 103. Rome, Italy: Food and Agricultural Organization of the United Nations; 2014.Search in Google Scholar

[16] Peech M. Hydrogen-ion activity. In: Black CA, editor. Methods of soil analysis. Madison, Wisconsin, USA: American Society of Agronomy; 1965. p. 914–25.10.2134/agronmonogr9.2.c9Search in Google Scholar

[17] Mehlich A. Mehlich 3 soil test extractant: a modification of Mehlich 2 extractant. Commun Soil Sci Plant Anal. 1984;15:1409–16.10.1080/00103628409367568Search in Google Scholar

[18] Nelson LA, Anderson RL. Partitioning soil test-crop response probability. In: Peck TR, editor. Soil testing: correlating and interpreting the analytical results. Madison, W.I., USA: American Society of Agronomy; 1977. p. 19–39.10.2134/asaspecpub29.c2Search in Google Scholar

[19] SAS Institute. SAS/STAT Software Version 9.0. Cary, NC, USA: SAS Institute; 2002.Search in Google Scholar

[20] Gomez KA, Gomez AA. Statistical Procedures for Agricultural Research. New York, USA: John Willey & Sons, Inc; 1984.Search in Google Scholar

[21] Wakene T, Walelign W, Wassie H. Effects of nitrogen and phosphorus fertilizer levels on growth and development of barley (Hordeum vulgare L.) at Bore district, Southern Oromia, Ethiopia. Am J Life Sci. 2014;2(5):260–6.10.11648/j.ajls.20140205.12Search in Google Scholar

[22] Agegnehu G, Lakew B. Soil test phosphorus calibration for malting barley (Hordem vulgare L.) production on Nitisols of central Ethiopian highlands. Trop Agric (Trinidad). 2013;90(4):177–87.Search in Google Scholar

[23] Sintayehu D, Duga D, Getachew L. Agronomic and economic analysis of N and P fertilizer on malt barley at Bekoji. In: Kibebew A, Weldeyesus S, editors. Proceedings of the 13th Biennial Conference. Addis Ababa, Ethiopia: Crop Science Society of Ethiopia; December 31, 2008–2 Jan. 2009.Search in Google Scholar

[24] Prystupa P, Salfer GA, Savin R. Leaf appearance, tillering and their coordination in response to N × P fertilization in barley. Plant Soil. 2003;255:587–94.10.1023/A:1026018702317Search in Google Scholar

[25] Muhammad BK, Muhammad IL, Rehmat U, Shuaib K, Muhammad A. Effect of different phosphatic fertilizers on growth attributes of wheat (Triticum aestivum L.). J Am Sci. 2010;6(12):1256–62.Search in Google Scholar

[26] Heluf G, Mulugeta S. Effects of mineral N and P fertilizers on yield and yield components of flooded lowland rice on vertisols of Fogera plain, Ethiopia. J Agr Rural Dev Trop. 2006;107(2):161–76.Search in Google Scholar

[27] Mengel K, Kirkby EA. Principles of Plant Nutrition. Worblaufen-Bern, Switzerland: International Potash Institute; 1987.Search in Google Scholar

Received: 2020-07-29
Revised: 2022-03-08
Accepted: 2022-03-09
Published Online: 2022-04-06

© 2022 Kassu Tadesse et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

Downloaded on 9.6.2023 from https://www.degruyter.com/document/doi/10.1515/opag-2022-0078/html
Scroll to top button