Soil Test Crop Response Based P-Calibration Study on Tef (Eragrostis tef) in Yabello District of Borana Zone, Southern Oromia, Ethiopia

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Introduction

Tef (Eragrostis tef (Trotter)), a cereal crop that belongs to the grass family Poaceae, is endemic to Ethiopia and has been widely cultivated in the country for centuries (Teklu and Tefera, 2005). The crop harbors several useful traits both for farmers and consumers. Some of these beneficial traits are; the plant is tolerant to extremely environmental conditions; the seeds are not attacked by storage pests; and the seeds are gluten-free, and hence considered as a healthy food (Kibebew et al., 2011). It is extensively cultivated in Ethiopia with annual coverage of about 2.8 million hectares (Kebebew et al., 2013) [13] or it occupies about 25-32% of land under cultivation with cereal crops (Girma et al., 2018) [10]. Almost two-thirds of the Ethiopian population relies on tef as their daily staple food. As average incomes rise and urbanization accelerates in Ethiopia, the demand for tef is expected to increase significantly over time (Berhane et al., 2011). Ethiopia is not only a center of origin for tef but also a region of remarkable diversity and significance for this crop, covering vast areas of land. However, despite its importance, tef production remains relatively low and insufficient to meet the needs of both the population and the market (Anteneh, 2017). Several challenges contribute to this production shortfall, including low soil fertility and suboptimal use of mineral fertilizers. Additionally, factors such as weed competition, a lack of high-yielding cultivars, erratic rainfall patterns in lower altitudes, lodging, waterlogging, and overall low moisture levels further impede tef cultivation (Desta, 2014) [9] The Blanket fertilizer recommendations currently applied was released several years ago in Ethiopia, does not consider the differences in agro-ecological environments are inappropriate for application to current production systems and for the foreseeable future (Abuye et al., 2021) [2]. Farmers have been applying the same P fertilizer rate to their fields regardless of soil fertility variations since the temporal and spatial variations in soil fertility haven't been considered. For this reasons, the blanket recommendation will make inefficient use of these expensive nutrients which contribute to the depletion of scarce financial resources, increased production costs and potential environmental risks (Tarekegne & Tanner, 2001) [24].

According to Abdulrahman et al. (2021), calibration is the process of determining the relationship between the yield response of adding nutrients to the soil as fertilizer and the test values for the soil. It provides information how much nutrient should be applied at a particular soil test value to optimize crop growth without excessive waste. Calibration research predicts the probability of response from applying a given nutrient which must be determined experimentally in the field (Dahnke and Olsen, 1990) [8]. The calibration curve is specific for each crop type, soil type, soil pH, climate; plant species, and crop variety (Agegnehu and Lakew, 2013) [3]. Soil test based fertilizer recommendations play a vital role in ensuring balanced nutrition for crops. Therefore, fertilizer application schedules should be based on the magnitude of crop response to applied nutrients at different soil fertility levels (Santhi et al., 2002) [20]. That means fertilizer recommendations based on soil test crop responses for economic crop production should be both soil and situation (agroecology) specific. As in all other regions of the country, a fertilizer recommendation in Yabello district is also not based on soil test results.

Objectives

➢ To determine optimum level of N fertilizer for Tef in the Yabello districts ➢ To determine P-critical value and P-requirement factor for Tef under farmer’s conditions.

Materials and Methods

Description of the Study Area The study was conducted in the Yabello District, Borana Zone of Oromia Regional State, Ethiopia. It is located in the hub of Borana rangeland, 570 km south of Addis Ababa, and both the Ganale-Dawa and Rift-Valley River basins cross through it. Its altitude varies from 1000 to 1800 meters above sea level (masl) at the latitude and longitudes of 4°12´10´´– 5°16´20´´ N and 37°51´40´´ – 38°37´30´´ E, respectively (Coppock, 1994) [7]. Yabello District has bimodal rainfall, with the main rainy season locally known as Ganna (60%) is occurring during March to May and the short rainy season locally called Hagaya (30%) occurring from October to November. The mean annual rainfall in the Yabello district ranges from 400 mm to 900 mm with high altitudinal variability. The climatic data of Yabello metrological station indicated that the mean annual maximum and minimum temperature are 28.5 oC and 12.3 oC, respectively (Yabello Administrative Office, 2023; NMA, 2023).

Fig 1: Map of the Study Area Soil and Farming Practices The soil types of the study area are Chromic Cambisol, Eutric Cambisol, Chromic Luvisols, Epileptic Leptosol, and Pellic Vertisol and they comprise texturally five main classes: clay loam, sandy clay loam, loamy sand, clay, and loam (FAO, 2012). Chromic Luvisols were found to be the dominant soil type, which accounts for 79.4% of the total study area (Fenan et al., 2022). The major crops grown in the study area are maize (Zea mays), tef (Eragrostis tef), and haricot bean (Phaseolus vulgaris) (Desta et al., 2011) [9]. Farmers generally cultivate crops using rainfed agriculture as a crop-livestock mixed farming system, and irrigation has also become important in agricultural production activities.

Site selection and Soil sampling For deciding representative experimental locations, six sites/farmers/ fields were selected depending on its accessibility for providing good management system and composite soil samples were collected from the district and optimum nitrogen rate that the crop requires were recommended in the first year (2022) in the case of Tef production. In second and third year (2023–2024) randomly twenty sites were selected for determination of phosphorus critical (Pc) and requirement factors. Composite soil samples were collected from all sites by using Auger from the depth of (0-20cm) air dried, grounded and passed through 2mm sieve and analyzed at Yabello Pastoral and Dry Land Agriculture Research Center Soil laboratory keeping its standards/procedures.

Treatments, experimental design and procedures In the case of the first year, the experiment was consisted of three levels of P (0, 30, 40 kg/ha) and four levels of Nitrogen (0, 46, 69 and 92 kg/ha) fertilizers were combined as treatments. The treatments were arranged in factorial combination with RCBD replicated three times over six farmers. In second and third years for determination of Pc and Pf treatments consists of six levels of P (0, 10, 20, 30, 40, 50 kg/ha) and 46 kg/ha N were arranged in single factor in RCBD with three replications.

Determination of critical P concentration (Pc) Determination of Critical P Concentrations is below which there were a response while above phosphorus was not respond. Intensive composite soil samples were collected after 21 days of planting. At this time the applied phosphorus was ready to be utilized by crop. Critical P value (mg/kg) has been determined following the Cate-Nelson graphical method where soil P values were put on the X-axis and the relative grain yield values on the Y-axis.

Relative Yield = yield x 100 maximum yield The Cate-Nelson graphical method was dividing the Y axis and X axis 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 (Nelson and Anderson, 1977) [19].

Determination of Phosphorus Requirement Factor (Pf) Phosphorus requirement factor (Pf) is the amount of Phosphorus in kg needed to raise the soil P by 1ppm. Average of Olsen P-ppm after 21 days of each applied P-treatment and Phosphorus increase over the control were calculated. Finally, Pf (phosphorus requirement factor) was determined by the following formula.

Pf = kg P applied change in soil P Statistical Analysis Yield and soil available data from all sites were managed on Excel software. The collected data were subjected to analysis variance (ANOVA) using the General Linear Model (GLM) procedures of SAS software (SAS, 2002) [21]. Mean comparison of treatments were performed using Fisher's least significant difference test at p<0.05 probability level.

Economic Analysis To identify the economic significance of the treatments, partial budget analysis was employed and calculates the marginal rate of return (MRR) (CIMMYT, 1988) [5]. Since the treatments are significance, economic analysis was done for nitrogen and phosphorus fertilizers. The grain yield was adjusted by 10% to reduce the exaggeration of small plot management. The cost of fertilizer at local market on April, 2022 (Urea and NPS/TSP 30 ETB Kg-1 and 35 ETB Kg-1, respectively). Transport, broad casting, harvesting and bagging cost was estimated 15 Birr Kg-1 for study area. To use the marginal rate of return (MRR) as a basis for fertilizer recommendation, the minimum acceptable rate of return (MARR) was set to 100% (CIMMYT, 1988) [5].

Results and Discussions

Selected soils physicochemical properties before planting The results of particle size distribution, pH, OM, TN and Av. P of the soil were summarized and presented in Table 1. Accordingly, the percentages of sand, clay, and silt content were represented by soil particle size distributions with values ranging from 29 - 81%, 10 - 48%, and 9 – 43% for percent sand, clay and silt content, respectively. As the rating suggested by Hazelton, P. and Murphy, B. (2007) [11], moderate to very high level of sand, low to high level of clay and very low to high level of silt contents. The pH (H2O) values of the soil samples collected before sowing were ranged from 5.99-7.09 (Table1) consequently the soils of the study site lie in general from moderately acid to neutral soil reaction (Murphy (1968 and Jones J., 2003) [18, 12] The range values for soil organic matter (OM) was 0.79 to 2.69%. As per the ratings of (Tekalign, 1991) [25], OM contents for soils of the experimental sites rated into very low to moderate class. The values of total nitrogen (TN) content varied from 0.11 to 0.23% rated as low to moderate as ratings suggested by (Landon, 1991) [17]. The values of available phosphorus (Av. P) ranged from 5.5 to 9.1 mg/kg which rated low to moderate based on the critical values for determined by the Olsen method established by (Clements and McGowen (1994)) [6]. Cation exchange capacity (CEC) values were ranged from 14.8 to 20.7 cmol+/kg according to (Hazelton and Murphy, 2007) [11], rated into low to medium (Table 1). This classification indicates that the soil has a moderate capacity to hold cations, which can affect nutrient availability for plants. Soils with low to medium CEC may require more frequent fertilization to ensure that plants receive adequate nutrients. The reasons for the extremely low to low categories of these important soil plant nutrients might include leaching, continuous mono-cropping based on cereals (primarily tef), low or restricted inputs of fertilizers from organic and inorganic sources, nutrient fixation, or loss from soil erosion.

Table 1: Selected soils physicochemical properties status for the experimental sites of Yabello District (2022-2024). Farmer’s name pH EC %sand %clay %silty Textural class %OC %OM Av P Tot. N CEC Jatani 7.09 2.12 35 22 43 Loam 2.69 4.64 5.5 0.11 15.6 Jarso 6.70 2.68 67 20 13 sandy clay loam 1.90 3.27 9.0 0.16 18.2 Abduba 6.35 1.61 81 10 9 loamy sand 0.79 1.37 8.9 0.20 14.8 Beko 6.35 1.53 25 47 28 Clay 1.08 1.87 9.1 0.17 17.3 Bute 6.22 0.85 59 22 19 sandy clay loam 1.00 1.72 9.0 0.23 20.7 Guracha 5.99 1.78 29 48 23 Clay 2.54 4.38 8.2 0.22 16.8 Mean 6.45 5.79 1.26 2.17 9.0 0.18 17.2 Determination of Optimum Nitrogen Fertilizer The analysis of variance indicated that the interaction effect of P and N fertilizer rates had a significant (p < 0.05) impact on the yield of tef. The highest tef yield (1748.23 kgha-1) was obtained from the application of 40 kg P with 46 kg N ha-1 followed by 1679.3 kg and 1644.4 kg of tef yield which were obtained from the application of 30 kg of P with 46 kg N (ha-1), and 40 kg of P with 69 kg N (ha-1), respectively (Table 2). This result shows the existence of a positive interaction of P, and N fertilizers for the production of tef crops, and the responsiveness to the application of high-level fertilizer phosphorus. While the lowest yield (872.30 kg ha-1) was recorded from control (unfertilized plot). In agreement with this results Amante et al. (2023) [4] found that the main and interaction effects of both P and N fertilizer rates shows highly significant difference (P<0.05) for tef grain yield in Bora district. The lowest (1,017 kg/ha) mean grain yield of the crop was obtained from the control (without fertilizers application) and the highest (1,592 kg/ha) mean grain yield was recorded from the application of 200 kg P/ha with 115 kg N/ha.

Table 2: Interaction effect of N and P fertilizers on Tef (DZ_CR-385) grain yield at Yabello District in 2022 cropping season. N Rate kg ha -1 P2O5 Rate kg ha -1 0 30 40 0 872.30i 1276.80 f 1067.10 h 46 1131.60 g 1679.3b 1748.23 a 69 1345.40 e 1611.76c 1644.4 bc 92 1330.20e 1490.50 d 1602.0c LSD(0.05) 1.79 CV (%) 21.33 Partial Budget Analysis To identify treatments with the optimum return to the farmer‘s investment, marginal analysis was performed on non-dominated treatments. For a treatment to be considered worthwhile to farmers (a 100% marginal rate of return (MRR)) was considered as the minimum acceptable rate of return (CIMMYT, 1988) [5]. As indicated in Table 3, the partial budget and dominance analysis showed that the highest net benefit 103603.1 Birr ha-1 was obtained in the treatment that was treated with 46 kg ha-1 of N and 40 kg P ha-1, while the lowest net benefit 54578.6 Birr ha-1 was obtained in the control treatment. Hence, 46 kg N ha-1 is economically optimal for tef production in Yabello District.

Table 3: Partial budget and marginal analysis for TSP and N rates of Tef N P2O5 GY (Kg/ha) Adj. GY(Kg/ha) TVC (ETB) GNB(ETB) NB(ETB) MRR (%) 0 0 872.3 778.9 3836.6 58415.3 54578.6 0 40 1067.1 952.8 11358.3 71457.8 60099.4 -D 46 40 1782.7 1591.7 15775.1 119378.3 103603. 543.0 92 30 1490.5 1330.8 16742.5 99813.0 83070.5 264.3 TSP cost = 3500 Birr ku-1, UREA cost = 3000 Birr ku-1, teff grain = 75 Birr kg-1, TVC = Total variable cost (Birr ha-1 ) AGY = Adjusted grain yield down wards by 12.5% (kg ha-1 ), GNB = Gross Net Benefit, NR = Net return (Birr ha-1), MRR (%) = Marginal rate of return, Control = unfertilized. Yield and Yield Components Responses to Phosphorus Fertilizer Rates The responses of yield and yield components of tef to phosphorus fertilizer were presented in Table 4. Phosphorus fertilizer among the treatments had a substantial impact on grain yield as well as the yield components of tef, according to the mean analysis of variance across all experimental locations. The results showed that the maximum phosphorus application rate (50 kg/ha) produced the largest biomass (4.20 tonne ha-1), spike length (35.71 cm), plant height (88.48 cm), and tiler number (3.56), while the control produced the lowest yield. Accordingly; the highest grain yield (1498.29 kg/ha) obtained at 46 N kg/ha and 40 kg/ha P while the lowest (978.68 kg/ha) obtained from the control plot. This might be due to NP fertilizer induced vigorous vegetative growth, which in turn, resulted in increased biological yield.

These results are in agreement with the results reported by Legesse, 2017 which showed, the application of phosphorus fertilizer rates of 10, 20, 30, 40, and 50 kg ha-1 increased grain yields of tef by 48, 58, 64, 65 and 70 %, respectively, compared to the control (without P fertilizer). Besides, this result supported with the finding of Khan et al (2010) [16] and Shazma et al (2016) [23] who stated applications of optimum NP fertilizer enhanced grain yield. Additionally; Shazma et al (2016) [23] also obtained the decline grain yield and yield components due to application NP fertilizer beyond optimum rate. The findings of this study demonstrate the positive impact of phosphorus application on tef yield and growth parameters. The significant differences among treatments suggest that higher phosphorus rates contribute to improved growth metrics, leading to increased biomass and grain yield. The results support the hypothesis that phosphorus is a limiting nutrient for tef production.

Table 4: Responses of biomass, SL, TN, PH and grain yield to combined application of optimum N and P levels for tef production at Yabello District Phosphorus rate (kg/ha) SL(cm) PH(cm) TN Biomass (ton/ha) Grain Yield (kg/ha) 50 35.71a 88.48 3.56ab 4.20 1457.29a 40 29.71c 81.73 3.21abc 4.17 1498.67a 30 32.63b 91.41 3.71a 3.96 1341.9ab 20 30.16c 91.78 2.98bc 3.93 1261.89bc 10 29.2c 76.98 2.81c 3.87 1119cd 0 25.89d 82.74 1.81d 3.74 978.68d Mean 30.6 85.5 3.0 3.98 184.6 CV 6.4 22.6 22.8 7.8 7.95 LSD 1.8 ns 0.6 ns 1276.24 Means with the same factor and column followed by the same letter are not significantly different at a α < 0.05 Determination of Phosphorus Critical Concentration (Pc) The critical phosphorus concentration (Pc) was calculated using the scatter diagram derived from the relative grain yields of tef and the subsequent soil test phosphorus values for all levels (0-50 kg P ha-1). The Cate-Nelson graphical method was used to identify the critical points of phosphorus; scatter points were divided into two populations, and the two perpendicular lines were moved vertically and horizontally until the maximum number of points in the two positive quadrants (or, conversely, the minimum number of points in the negative quadrants). Finally, the point where the vertical line crosses the x-axis was defined as critical soil test levels. Accordingly, the phosphorus critical concentration above which the responses of the crop become minimal was 14 ppm for tef crop production in Yabello District.

Fig 2: Relative grain yield Vs P olsen plot chart for P critical level determination Determination of Phosphorus Requirement Factor (Pf) The phosphorus requirement factor, which is the amount of phosphorus in kg needed to raise the soil phosphorus by 1 ppm enables us to determine the amount of fertilizer required per hectare to bring the level of available phosphorus above the critical level. The average Olsen phosphorus (ppm) after 21 days of each applied phosphorus treatment and the phosphorus increase over the control were calculated.

The phosphorus requirement factor was also determined from the difference between available soil test phosphorus values and from plots that received 0-50 kg P ha-1. As a result, the district's Pf ranged from 3.45 to 8.06 (Table 5), and the study area's overall average Pf of all treatments was 5.79.

Table 5: Phosphorus requirement factor for tef in Yabello district Phosphorous rate (kg/ha) Av P (ppm) /Olsen method/ P increase over control P requirement factor (Pf) Range Average 0 2.6-13.4 8.6 Average 5.79

Conclusions and Recommendations

Calibration provides information how much nutrient should be applied at a particular soil test value to optimize crop growth without excessive waste. However, the present study, soil test based crop response phosphorus calibration study for tef production in Yabello District was conducted for three consecutive years (2022- 2024). The results revealed that agronomic parameters of Tef were found to be significantly influenced by both the N and combined NP fertilizer rates. The economic analysis showed that the highest net benefit of 103603 Birr ha-1 with a 543% marginal rate of return was obtained in the treatment that was treated with 46 kg N ha-1 of urea and 40 TSP kg ha-1. Therefore, uses of 46 N kg/ha fertilizer for Tef production at the district and areas having similar soil conditions and agro-ecology is advisable. In this soil test-based crop response phosphorus calibration study, the phosphorus critical (Pc) concentration (14 ppm) and the phosphorus requirement factor (pf), with a value of 5.79, were determined for tef production. Since both are the nutrients that most limit yield in the study area, it can be concluded that soil test crop response-based fertilizer application, in particular a combined application of optimum nitrogen and phosphorus calibration study, significantly improves yield and yield component of tef production in Yabello District. Therefore, additional field testing may be necessary to verify the results before distributing the technology to end users.

Acknowledgments

The authors would like to acknowledge the Oromia Agricultural Research Institute (IQQO) for their generous financial support. This funding has been essential in facilitating our research activities and ensuring we have the necessary resources to conduct our work effectively. We express our special gratitude to the Yabello Pastoral and Dry Land Agriculture Research Center and the entire soil fertility team for their cooperation. Their expertise and commitment have greatly enhanced our research process, allowing us to gather valuable data and insights. Additionally, we would like to thank the experts from the Yabello Agricultural Office, along with the development agents and farmers. Your endless support has been invaluable, and we are particularly grateful for your generosity in allowing us to use land for our studies without incurring any costs. This collaboration has been crucial in enabling us to address important agricultural challenges in the region.

Conflict of Interest

The authors declare no conflict of interest