Research Article Soil Properties, Crop Yield, and Economic Return in Response to Lime Application on Acidic Nitisols of Southern Highlands of Ethiopia Getahun Haile ,1 Habtamu Berihun,2 Helina Abera,1 Getachew Agegnehu,3 and Mulugeta Lemenih 4 1Natural Resources Management Department, Dilla University, Dilla, Ethiopia 2Plant Science Department, Dilla University, Dilla, Ethiopia 3International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Addis Ababa, Ethiopia 4Targeted Technology Institute, Silver Spring, Maryland, USA Correspondence should be addressed to Getahun Haile; getahun_h@yahoo.com Received 12 December 2022; Revised 20 November 2023; Accepted 12 December 2023; Published 29 December 2023 Academic Editor: Maria Serrano Copyright © 2023GetahunHaile et al.Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Soil acidity is one of the major crop production constraints in the highlands of Ethiopia. Liming is becoming a common practice to amend soil acidity, but its efects on soil properties, crop yield, and farm income are not well studied. In this study, an on-farm liming experiment was conducted for two consecutive years (2020-2021) on acidic Nitisols (pH< 5.5) in Southern Ethiopia. Te experiment consisted of six liming rates (control, 2.74, 4.11, 5.48, 6.85, and 8.22 t·ha−1) laid out in a randomized complete block design with three replications. Soil, agronomic, and economic data were collected in 2020 and 2021 cropping seasons and analyzed. Te application of lime in the ranges of 2.74–8.22 t·ha−1 increased soil pH by 0.46–1.25 units and reduced exchangeable acidity by 2.02–3.17 units. Higher lime rates of 6.85–8.22 t·ha−1 increased soil pH sharply from 5.22 to 5.99 and 6.46, respectively, but such a rise in soil pHwas not proportionally refected in the yield increment. Higher available phosphorus contents of 7.16 and 6.01mg·kg−1 were measured at the liming rates of 4.11 and 5.48 t·ha−1, respectively. Combined over the two years, 5.45 t·ha−1 lime application yielded the highest barley total biomass of 19,199 kg·ha−1 and a grain yield of 4,328 kg·ha−1, which are 46% and 30% higher than those of the control, respectively. It also yielded the highest marginal rate of return of 477% and a gross margin of 192,857.3 ETB1·ha−1, which is 53% higher than the control. Based on our results, 5.45 t·ha−1 of lime appears to have the optimal rate for economically viable barley production in the study area or similar environments. 1. Introduction Soil acidity is a serious issue in agricultural production, afecting approximately 50% of arable lands worldwide [1, 2]. Soil acidity can reduce cereal grain yield by as much as 50%, and in extreme cases, yields can be reduced to zero [3–5]. Soil acidifcation is a very complex process and results from natural factors such as soil and climatic factors [4, 5] and/or anthropogenic factors such as the use of inorganic fertilizers [5]. Tropical and subtropical regions are among the most acid-afected areas owing to their high rainfall and associated leaching of base cations [5, 6]. Soil acidity afects plant growth and yield by causing nutrient defciencies such as P, N, Ca, K, Mg, and Mo and/or inducing aluminum and manganese toxicity [5, 7]. Soil acidity is one of the major crop production con- straints in Ethiopia [3], covering 43% of cultivated land [8], of which 28% is strongly acidic [9]. Te southern highlands of Ethiopia, where the current study took place, are among the most acid-afected areas of the country. Te severity of soil acidity in the area has forced farmers to shift crops, abandoning crops like barley in favor of pasture and a few acid-tolerant crops such as potatoes and onions. It is, therefore, important to develop afordable acid soil Hindawi International Journal of Agronomy Volume 2023, Article ID 6105725, 13 pages https://doi.org/10.1155/2023/6105725 https://orcid.org/0000-0002-9705-179X https://orcid.org/0009-0003-9457-1508 mailto:getahun_h@yahoo.com https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/ https://doi.org/10.1155/2023/6105725 management strategies to minimize its impact on crop production. Amending acid soil with lime is an efective remedy, and its use is growing in Ethiopia [5]. According to this review [5], liming can increase grain yield by 34–252% for wheat, barley, or tef crops in Sub-Saharan Africa (SSA). In the current study area, smallholder farmers are recommended to apply lime and have begun using it. However, the rate of application and the efect that liming will have on their soil, crop productivity, grain yield, and farm income (proft- ability) are not thoroughly investigated. Although several studies exist on the efects and rate of liming, its efectiveness is also shown to vary depending on the bufering capacity of the soil, soil management, methods of lime application, weather conditions, and agronomic practices such as crop types involved [5]. Terefore, site and/or crop-specifc lime application studies are required to identify optimum liming applications that efectively mitigate soil acidity and enhance crop productivity and farm income [10, 11]. Te objectives of this study were, therefore, to investigate the efects of diferent rates of lime application on soil properties, barley yield, and its economic beneft to smallholder farmers. 2. Materials and Methods 2.1. Description of the Study Area. Te study was conducted in Bule District of Gedeo Zone, southern Ethiopia (Figure 1). Te area lies between 6°04′16″ and 6°23′50″N latitude and from 38°16′20″ to 38°26′11″E longitude (Figure 1(a)). Te altitude ranges from 2500 to 3200m above sea level falling in a tepid moist to cool highlands agroecological zone. According to traditional agroecology classifcation, Gedeo Zone comprises Dega (highland), Woina Dega (midland), and Kola (lowland) accounting for 26%, 65%, and 9%, respectively [12]. Te altitude of the district ranges from 1500 to 3000m.a.s.l. Te rainfall is bimodal, with the short rain from March to May and the main rain from August to October. Te annual rainfall ranges from 1401 to 1800mm, and the average minimum and maximum tem- peratures range between 12 and 20°C, respectively [12]. Te study area is part of the eastern escarpment of the southern Rift Valley System of Ethiopia. Te geology of the area is complex and characterized by tertiary and quaternary period rhyolite and basalt volcanic materials. Te surrounding landforms are characterized by diverse topo- graphic features such as plain to steep slopes, undulating to rolling plateaus, scattered moderate hills, dissected side slopes, and river gorges [13], which resulted in the formation of various soil types. Dystric Nitisols and Eutric Cambisols predominate in the area (Figure 1(b)). Te total area of the district is 25,680 ha, with the population of 125,430, of which 117,398 live in rural areas and 8,032 in town [13]. Land use comprises 11,876 ha (46%) perennial crops, 10,115 ha (39%) annual crops, 1,855 ha (7%) forest, 459 ha (1.8%) grazing land, and the remaining is a residential area [13]. Mixed subsistence agriculture is the main source of livelihood. Major annual crops grown are wheat, barley, faba bean, feld pea, linseed, vegetables, po- tato, and onion. Perennial crops such as enset, cofee, and apple are common and often intercropped with trees in the form of traditional agroforestry. Indigenous tree species like Erythrina abyssinica, Arundinaria alpina (highland bam- boo), Juniperus procera, and Hagenia abyssinica, and an exotic tree species, Eucalyptus globulus, are predominant in the landscape. 2.2. ExperimentalMaterials. Te soil of the experimental site is Nitisols. Some physical and chemical properties of the soils of the study area are provided in Table 1. Te study site was selected based on three criteria: (i) soil pH lower than 5.5, (ii) soil with no previous liming history, and (iii) agroecologically representative for barley production. Barely was the test crop used in the experiment. A high-yielding food variety (HB 1307), commonly grown in the area, was used. Urea (46% N) and NPS (19% N, 38% P2O5, and 7% S) fertilizers were applied on the experimental plots at the common rates farmers apply. Agricultural lime (CaCo3), used in the area for treating soil acidity, was applied at various rates described in Section 2.3 to investigate its efects. 2.3. Treatment and Experimental Design. Te experiment considered six levels of lime. Te initial rate of lime applied was calculated based on the exchangeable acidity (Al+3 and H+), soil bulk density (g·cm−3), and mass of soil in the upper 0–15 cm soil depth using the following formula [14]: LR,CaCo3 kg ha 􏼠 􏼡 � cmol EA/kg soil × 0.15m × 104m2 × B.D mg/m3 􏼐 􏼑 × 1000 2000 , (1) where LR is the lime requirement (kg/ha), CaCO3 is calcium carbonate, EA is exchangeable acidity, and B.D is the bulk density of soil. Te other lime rates used in the experiment were calculated as 0, 1.5, 2, 2.5, and 3 times the calculated lime requirement (LR) of the soil. Te six liming rates involved were 0 (no lime), 2.74, 4.11, 5.48, 6.85, and 8.22 t·ha−1. Te lime was broadcast uniformly by hand across the plots and incorporated into the soil a month before planting (Figure 2). Te experiment was laid out in a randomized complete block design (RCBD) with three replications. Blocking was used to control local variability in soil conditions. Te size of each plot was 4 m width × 3m long (12 m2) and consisted of 10 planting rows per plot. Te spacing between rows, plots, and blocks was 0.3 m, 0.5 m, and 2 International Journal of Agronomy 1.0 m, respectively. Te barely seeds were drilled at the recommended spacing for the crop, which was 20 cm between seeds in a row, and planted at the seeding rate of 90 kg·ha−1. Plantings were carried out on the 15th and 14th of August 2020 and 2021, respectively. Urea and NPS fertilizers were applied at the recommended rate of 73.5 kg N ha−1 and 25 kg P ha−1, respectively. To minimize loss and increase N fertilizer use efciency, it was applied in two splits, i.e., 50% at sowing and the remaining 50% side dressed 30 days after planting. Te NPS fertilizer was Table 1: Some soil physical and chemical properties at 0–20 cm depth before treatment application. Soil texture Bulk density Soil chemical properties Clay (%) Silt (%) Sand (%) (g/cm3) pH OC (%) TN (%) C/N Av. P (mg/kg) Ca Mg EA CEC cmol (+)/kg 50.3 34.6 15.1 1.05 5.2 3.5 0.4 8.75 4.24 4.23 0.87 3.48 31.15 Note. EA� exchangeable acidity; CEC� cation exchange capacity; OC� organic carbon; TN� total nitrogen; C/N� carbon to nitrogen ratio; Av. P� available phosphorus; Ca+2 � exchangeable calcium; Mg+2 � exchangeable magnesium. Ethio Zones Gedeo Zone Road Study area Elevation (m) Value High : 2989 Low : 2366 CordinateSsystem:WGS 1984 UTM Zone 37 N Projection:Traverse Mercator 0 0.5 1 2 Km (a) Soil types Calcic xerosols Dystric gleysols Dystric nitisols Eutric cambisols Leptosols Orthic acrisols Orthic solonchaks Bule woreda Soil Type Map of Bule Woreda (b) Figure 1: Location map (a) and soil map (b) of the study district. Figure 2: Pictures showing application of lime, fertilizer, and other agronomic practices. International Journal of Agronomy 3 applied once as basal application during the planting time. Lime was applied in the frst year (2020) of the exper- iment only. Te second year was used to test the residual efects of its application. Seedbed preparation and weeding were performed manually following farmers’ regular prac- tices on their felds. 2.4. Soil Sampling and Analysis. Composite soil samples were collected from 0 to 20 cm depth from the experimental plots before applying the treatments and after crop harvest, both in 2020 and 2021. Te soil samples were analyzed for several physical and chemical properties following standard soil lab analytical procedures in the Soil and Water Analysis Laboratory of Horticoop Ethiopia PLC. Soil samples were air-dried and ground to pass through a 2mm sieve, except for the analysis of soil organic carbon and total nitrogen that were ground to pass through a 0.5mm sieve. Te soil physicochemical properties analyzed were soil texture, bulk density, soil pH, available phosphorus, exchangeable bases (Ca+2, Mg+2, K+, and Na+), cation exchange capacity (CEC), exchangeable acidity, exchangeable Al+3, H+, organic car- bon, and total nitrogen. Soil pH (H2O) was measured with a pHmeter in a soil to water ratio of 1 : 2.5. Organic carbon was measured by the wet oxidation method [15]. Total nitrogen was measured using the Kjeldahl method [16], and available phosphorus was determined using the Bray II method. Exchangeable cations (Ca, Mg, K, and Na) were analyzed using the am- monium acetate method. Cation exchange capacity (CEC) was determined by the ammonium acetate method at pH 7. Exchangeable acidity (exchangeable H+ and Al+3) was de- termined by extraction with 1N KCl followed by titration using the Mehlich-3 method. Soil particle size distribution was determined using the hydrometer method. Soil bulk density was determined through the volumetric method after the soil was oven-dried at 105°C for 24 hours. 2.5. Agronomic, Market, and Farm Input Data Collection. Agronomic data collected were plant height, the number of tillers per plant, spike length, total biomass, grain and straw yields, thousand-grain weight (TGW), and harvest index (HI). Plant height (cm) was measured from the base of the plant to its tip with a measuring tape at full maturity. Five plants were randomly selected per plot, and the average of their heights was analyzed. Spike length (cm) was measured from the bottom of the spike to its tip taking fve randomly selected plants per plot at physiological maturity and av- eraged for per plot value. Te number of tillers per plant was determined by counting from 5 randomly selected plants per plot at physiological maturity and averaged for per plot value.Tousand-kernel weight was calculated based on 1000 kernel weight taken from the harvested grain per plot by manually counting and weighing with a sensitive beam balance. Total dry biomass was weighed after air-drying all the harvested above-ground parts of the plants from each plot. Grain yield was determined after carefully separating the grain from the straw by threshing manually and weighing with a sensitive beam balance. Te grain yield was adjusted to 12.5% seed moisture content. Grain yield and biomass were quantifed per plot and converted to per ha basis for statistical analysis. Economic data such as lime cost and crop and straw prices were collected from local markets. Quantity andmarket data for all inputs and outputs were gathered from the local area. Farm gate prices were collected for inputs during planting/sowing seasons, and for outputs, prices at the time of crop harvest were collected. All costs and benefts were in Ethiopian birr (a local currency) and expressed per hectare basis (birr per ha). Accordingly, the average price of 30 birr kg−1 for barley grain and 4.11 birr kg−1 for barley straw were used to convert the adjusted yields to gross benefts. Te market prices of 4.5 birr kg−1 for lime and 50 birr per person-day for labor cost were used for variable cost estimation. 2.6. Agronomic and Soil Data Analysis. Te collected data were subjected to the analysis of variance (ANOVA) using SAS statistical package version 9.0. Each of the agronomic and soil data was subjected to ANOVA separately for both years and after combining the data from the 2 years. When the efects were found signifcant at a 5% or lower probability levels, mean separation was conducted with the least sig- nifcant diference (LSD) using Tukey HSD all-pairwise comparisons. Pearson correlation coefcients (r) were performed among agronomic and soil traits using the mean values. To assess the efects of treatments on barley growth and yield, six single degrees of freedom of orthogonal contrasts were also performed using the procedure of SAS. Te total variability for each trait was quantifed using a pooled analysis of variance over years using the following model: Pijk⥄ �⥄μ⥄ +⥄Yi⥄ +⥄Rj(i)⥄ +⥄Tk⥄ +⥄TY(ik)⥄ +⥄eijk, (2) where Pijk is the total observation, µ is the grand mean, Yi is the efect of the ith year, Rj(i) is the efect of the jth replication within the ith year, Tk is the efect of the kth treatment, TY(ik) is the interaction of the kth treatment with the ith year, and eijk is the random error. 2.7. Partial Budget Analysis. A fnancial return analysis was performed to investigate the economic feasibility of liming for barley production.Te output data (grain yield and straw yield) and input data (market price for labor, lime, etc.) were collected for two consecutive seasons (2020 and 2021) and averaged for analysis. Te average grain and straw yields of barley were adjusted downwards by 10% to refect the dif- ference between the experimental plot yield and the yield farmers would expect from the same treatment under their own management. For a lime treatment to be considered worthwhile for smallholder farmers, the marginal rate of return (MRR) should at least be between 50% and 100% [17]. However, researchers in other parts of the country suggested an MRR of 100% as a realistic value for risk-avert small- holder farmers. Hence, for this study, an MRR of 100% was 4 International Journal of Agronomy taken as a benchmark. Te 6.85 and 8.22 t·ha−1 treatments were excluded from the marginal analysis. For each pair of the remaining treatments, a percentage marginal rate of return (% MRR) was calculated. MRR was calculated using the following formula: MRR(%) � ChangeNB Change TVC ∗ 100, (3) where TVC� total variable cost, NB� net beneft, and MRR�marginal rate of return. 3. Results and Discussion 3.1. Efect of Liming on Soil Properties. Liming signifcantly afected soil pH, including its residual efect. All lime-treated soils had higher mean pH values in 2020 and 2021 than the control plot (Table 2). Soil pH increased progressively with increased quantity of lime applied. Te highest pH values of 6.54 and 6.37 in 2020 and 2021, respectively, were obtained from soils of the plots that received the largest quantity of lime (8.22 t·ha−1), whereas the lowest values (5.04 and 4.97, respectively) were measured in the soils of the control plots (Table 2). Te combined data from the 2 years also showed a sig- nifcant (p< 0.001) efect of liming on soil pH (Table 3). A signifcantly high pH value of 6.46 was recorded from soils of the plots that received the largest quantity of lime (8.22 t·ha−1), while the lowest pH value of 5.01 was measured from the soils of the control plots. Soil pH increased by 0.46, 0.47, 0.77, and 1.25 units with the applications of 2.74, 4.11, 5.48, 6.85, and 8.22 t·ha−1 lime, respectively. Tough the efects of year on soil pH are not signifcant, a relatively higher pH of 5.71 was obtained in 2020, while a pH of 5.62 was obtained in 2021 (Table 3). Tese results concur with studies that indicated positive efects of liming on soil pH including strong residual efects, which could last for fve to seven years depending on texture, bufering capacity of the soils, and the quality of lime applied [5, 10, 18]. For instance, Buni [10] found an increase in soil pH, ranging from 0.48 to 1.1 units following the application of lime rates from 0.55 to 2.2 t·ha−1 in Ethiopia. Other studies [18, 19] also reported a marked increase in soil pH in re- sponse to liming in southern and western Ethiopia, respectively. Soil EA and exchangeable H+ and Al3+ were signif- cantly (p � 0.001) decreased in response to lime applica- tion during the two years of the experiment (Table 2). Te lowest EA of 0.16 cmol/kg was obtained from the plot treated with the highest rate of lime (8.22 t·ha−1) followed by 0.49 cmol/kg in plots treated with 5.54 t·ha−1 lime, while the highest EA values of 2.59 and 4.15 cmol·kg−1 soil were obtained from control plots in 2020 and 2021, re- spectively (Table 2). Exchangeable Al3+ was not detected in plots treated with lime rates of 5.54, 6.85, and 8.22 t·ha−1 in 2021 (Table 2). Te increase in soil pH following liming could be at- tributed to the release of base cations such as Ca+2 and Mg+2 to displace acidic cations such as Al+3 and H+ from the soil colloids and subsequently precipitate in the form of Al(OH)3 [5]. When lime is added to acid soil that contains high Al3+ and H+ concentrations, the soil solution will become charged with Ca2+.Tis ion will get in exchange with H+ and Al3+ ions on the exchange complex and consequently in- crease the soil pH. Similarly, the observed low concentration of acid causing cations (H+ and Al3+) in plots treated with lime is in line with the fndings of [10] who reported de- creased Al+3 concentrations between 0.88 and 1.19 cmol/kg units following lime treatment in Ethiopia. Other studies (e.g., [11, 18, 19]) on liming of acidic soils reported improved soil chemical properties and crop yield. Te combined data from the two years also showed signifcantly (p< 0.001) lower EA and exchangeable Al3+ and H+ (Table 3). Te highest soil EA and exchangeable H+ and Al+3 were recorded from the control plots (Table 3). In contrast, the lowest EA of 0.31 cmol/kg was measured from plots treated with the liming rate of 8.22 t·ha−1. Similarly, the application of 8.22 t·ha−1 of lime resulted in lower ex- changeable H+ of 0.15 cmol/kg compared to 1.13 cmol/kg soils in the control plot. Exchangeable acidity was signif- cantly reduced by 2.02, 2.8, 3.06, and 3.17 cmol/kg at lime application rates of 2.74, 4.11, 5.48, 6.85, and 8.22 t·ha−1, respectively (Table 3). A slightly higher EA of 1.4 cmol Table 2: Mean values of selected soil chemical properties (pH, available P, OC, TN, EA, Ex H+, and Ex Al3+) as afected by diferent rates of lime application on Nitisols in southern Ethiopia. Lime rate (t·ha−1) pH Available P (mg/kg) OC (%) TN (%) Ca2+ EA (cmol/kg) H+ (cmol/kg) Al3+ (cmol/kg) 2020 2021 2020 2021 2020 2021 2020 2021 2020 2020 2021 2020 2021 2020 2021 Control (0) 5.04d 4.97c 5.63a 4.68a 5ab 4.22a 0.48ab 0.49a 4.8 d 2.59a 4.15a 0.47a 1.79a 2.13a 2.36a 2.74 5.29cd 5.18c 6.94b 3.83a 5.07ab 4.29a 0.48ab 0.49a 8.15cd 0.88b 1.94b 0.26b 1.39ab 0.61b 0.55b 4.11 5.66bc 5.67b 6.95b 5.08a 5.12a 4.24a 0.49ab 0.5a 10.43bcd 0.33b 1.04bc 0.14c 0.80bc 0.19b 0.72ab 5.54 5.64bc 5.70b 7.05b 4.19a 5.01ab 4.17a 0.51a 0.65a 11.52bc 0.36b 0.49c 0.16c 0.49cd 0.20b ND 6.85 6.11ab 5.83b 7.95ab 3.78a 4.95ab 4.15a 0.48ab 0.48a 14.34ab 0.71b 0.59bc 0.22bc 0.59cd 0.49b ND 8.22 6.54a 6.37a 7.92ab 4.9a 4.8b 3.86b 0.46b 0.46a 17.91a 0.45b 0.16c 0.14c 0.16d 0.31b ND Signifcance level ∗∗ ∗∗∗ NS NS NS ∗∗ NS NS ∗ ∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗ ∗ LSD (0.05) 0.55 0.44 1.89 1.34 0.3 0.24 0.04 0.22 6.18 0.66 1.41 0.10 0.61 0.57 CV (%) 5.34 4.48 13.41 18.6 3.33 3.27 4.69 25.19 30.33 41.09 38.14 23.89 30.42 38.12 27.96 Note. Signifcant at ∗p≤ 0.05, ∗∗p≤ 0.01, and ∗∗∗p≤ 0.001. Within a column, means followed by diferent letters are signifcantly diferent at p< 0.05. LSD: least signifcant diference; CV: coefcient of variation; NS: not signifcant; ND: not detected. International Journal of Agronomy 5 Ta bl e 3: Ef ec ts of lim e ap pl ic at io n on so il ch em ic al pr op er tie s co m bi ne d ov er 2 ye ar s on N iti so ls in so ut he rn Et hi op ia . Tr ea tm en t pH (H 2O ) A v. P (m g kg − 1 ) C EC C a2 + (C m ol kg − 1 ) K + (C m ol kg − 1 ) O C (% ) TN (% ) C :N ra tio EA (C m ol kg − 1 ) H + (C m ol kg − 1 ) A l+ 3 Ye ar 20 20 5. 71 7. 74 a 28 .6 1 9. 72 a 0. 41 a 5. 01 a 0. 49 10 .3 8a 0. 89 a 0. 23 a 0. 65 20 21 5. 62 4. 41 b 28 .1 3 11 .1 9b 0. 49 b 4. 16 b 0. 51 8. 36 b 1. 40 a 0. 87 b 0. 53 Si gn if ca nc e le ve l N S ∗ N S ∗ ∗ ∗ N S ∗ N S ∗ N S LS D (0 .0 5) 0. 37 0. 69 3. 89 9. 6 0. 11 0. 05 0. 12 0. 96 0. 99 0. 55 0. 2 Li m e ra te (t ·h a− 1 ) C on tr ol (0 ) 5. 01 d 5. 62 ab 27 .4 3 4. 80 b 0. 41 ab 4. 67 a 0. 49 9. 62 3. 37 a 1. 13 a 2. 25 a 2. 74 5. 23 cd 5. 39 ab 28 .6 5 8. 15 b 0. 41 ab 4. 68 a 0. 49 9. 67 1. 41 b 0. 83 ab 0. 58 b 4. 11 5. 66 bc 7. 16 a 29 .6 10 .4 3a b 0. 47 a 4. 68 a 0. 5 9. 45 0. 68 bc 0. 47 bc 0. 21 c 5. 54 5. 67 bc 6. 01 ab 28 .4 1 11 .5 2a b 0. 45 ab 4. 59 ab 0. 58 8. 46 0. 42 bc 0. 32 c 0. 10 c 6. 85 5. 97 ab 5. 86 ab 28 .1 2 14 .3 4a b 0. 35 ab 4. 55 ab 0. 48 9. 63 0. 65 c 0. 41 c 0. 25 c 8. 22 6. 46 a 6. 42 b 28 .0 2 17 .9 1a 0. 39 b 4. 33 b 0. 46 9. 4 0. 31 c 0. 15 c 0. 15 c Si gn if ca nc e le ve l ∗∗ ∗ ∗ N S ∗∗ ∗∗ ∗ N S N S ∗∗ ∗ ∗∗ ∗ ∗∗ ∗ LS D (0 .0 5) 0. 49 1. 63 3. 38 3 4. 2 0. 26 7 0. 16 1. 36 0. 77 0. 42 0. 17 C V (% ) 4. 81 14 .8 2 6. 57 6 10 .2 3. 21 17 .6 3 21 .5 6 28 .2 1 22 .2 5 28 .7 9 N ot e. Si gn if ca nt at ∗ p ≤ 0. 05 ,∗ ∗ p ≤ 0. 01 ,a nd ∗∗ ∗ p ≤ 0. 00 1; N S: no ts ig ni fc an t. W ith in a co lu m n, m ea ns fo llo w ed by di fe re nt le tte rs ar e sig ni fc an tly di fe re nt at p < 0. 05 .L SD :l ea st sig ni fc an td if er en ce ;C V : co ef ci en to fv ar ia tio n. 6 International Journal of Agronomy (+) kg−1 soil was measured in 2021 than an EA of 0.84 cmol (+) kg−1 in 2020 (Table 3). A complete absence of Al3+ was observed in plots that were treated with higher rates of lime in the second year (Table 2), and this indicates the complete replacement of Al3+ ions with Ca2+ ions. Tis is also refected in the sig- nifcant efect that liming had on exchangeable Ca++. In the 2020 cropping period, signifcantly higher exchangeable Ca2+ of 17.91 cmol/kg was measured from a plot treated with 8.22 t·ha−1 lime, followed by 14.34 cmol·kg−1 soil from the application of 6.85 t·ha−1. On the contrary, the lowest ex- changeable Ca+2 content of 4.79 cmol·kg−1 was measured in the soils of the control plots (Table 2). Exchangeable Ca+2 increased progressively with the increased rate of lime ap- plication. Exchangeable K+ was not signifcantly (p< 0.05) infuenced by lime rates (Table 3). However, in terms of absolute values, lime rates of 4.11 and 5.45 t·ha−1 had the highest exchangeable K+ concentrations of 0.47 and 0.45 cmol·kg−1 soil, respectively, compared to the K value of 0.41 cmol·kg·ha−1 measured from the control treatment (Table 3). Te interaction efect of lime and year was not signifcant for most soil and agronomic variables except for EA and H+ (Figure 3). A signifcantly higher EA of 4.15 cmol/kg of soil was measured from the control treatment without lime application in the 2021 cropping season, followed by 2.59 cmol/kg soil from the control treatment in the 2020 cropping season, while the lowest EA of 0.16 cmol/kg was measured from the application of 8.22 t/ha lime in the 2021 cropping season, followed by 0.33 cmol/kg from the appli- cation of 4.11 t/ha lime in the 2020 cropping season (Fig- ure 3). Liming and year also had a signifcant (p= 0.001, Figure 3) interaction efect on exchangeable H+. A signif- cantly higher exchangeable H+ of 1.79 cmol/kg was measured from the control treatment in the 2021 cropping season, followed by 2.74 t/ha lime year 2 and control, while the lowest amount of exchangeable H+ of 0.14 cmol/kg was measured from the interaction of year 1 and 4.11 t/ha lime and year l and 8.22 t/ha lime (Figure 3). Te observed low concentrations of H+ in the plot treated with lime indicate the dislocation of Ca carbonate into Ca2+ and Co3−, thereby resulting in the replacement of H+ ions by CO3 − ions. Despite the efects on several soil properties, the application of lime did not signifcantly increase plant nutrient availability (e.g., available P and N) in both the 2020 and 2021 cropping seasons (Table 2). However, in terms of absolute values, higher available P was measured in all plots treated with lime compared to the control in the frst year of the experiment (Table 2). Furthermore, applications of lime at the rates of 4.11 and 5.45 t·ha−1 increased available P from 4.24 mg/kg before treatment to 7.16 in 2020 and 6mg/kg in 2021. Tese are the largest change in available P among all treatments applied (Tables 1 and 3). Te efect of lime application on available P combined over the 2 years was also not sig- nifcant (p> 0.05) (Table 3). Liming increases P availability by deactivating the active Al3+ ions that hinder P availability. Te application of lime increased P by enhancing the release of P fxed by Al/Fe and converting plant unavailable P into available P [20–23]. Asrat et al. [19] reported a signifcant improvement in available P from 5.36 to 7.04mg·kg−1 due to the application of 3.75 t·ha−1 lime. A similar study by the authors of [9] also reported P release in the range of 15.1–17.3mg·kg−1 com- pared to available P measured from untreated soil (4.2–7.1mg·P·kg−1) with an initial pH value of 4.0. Year of cultivation had a signifcant (p � 0.05) efect on available P. Overall, improvement in soil nutrient availability due to 5.00 4.00 3.00 2.00 1.00 0.00 Ex ch en ge ab le ac id ity (c m ol /k g) b a cd bc d cd d d cd d d d control 2.74 t/ha 4.11 t/ha 5.56 t/ha 6.85 t/ha 8.22 t/ha Liming rate Year Year 1 Year 2 Ex cc he ng ea bl e H + (c m ol /k g) 2.00 1.50 1.00 0.50 0.00 bcd a a cd b d d bcd cd bc d cd control 2.74 t/ha 4.11 t/ha 5.56 t/ha 6.85 t/ha 8.22 t/ha Liming rate Year Year 1 Year 2 Figure 3: Te interaction efects of liming and year on exchangeable acidity and H+ on Nitisols in southern Ethiopia (diferent letters in the columns are signifcantly diferent at p< 0.05). International Journal of Agronomy 7 Ta bl e 4: Yi el d an d yi el d co m po ne nt s of ba rle y as af ec te d by di fe re nt le ve ls of lim e on N iti so ls in so ut he rn Et hi op ia . Li m e ra te (t ha − 1 ) pH (c m ) N T SL (c m ) G Y (k g/ ha ) A G B (k g/ ha ) SY (k g/ ha ) H I TG W (g ) 20 20 20 21 20 20 20 21 20 20 20 21 20 20 20 21 20 20 20 21 20 20 20 21 20 20 20 21 20 20 20 21 C on tr ol (0 ) 92 .7 3b 76 .2 5b 6 1. 2 6. 35 7. 14 c 31 79 b 34 72 .3 b 12 01 0b 14 23 6a 88 31 b 10 76 3. 7 26 .6 7a 24 .6 7a b 41 .4 7a 59 2. 74 96 .4 ab 79 .2 ab 7. 17 1. 27 6. 57 7. 69 ab c 33 08 b 38 19 .7 ab 13 26 3. 3a b 17 36 1. 3a 99 55 ab 13 54 1. 7 25 ab c 22 .6 7b 39 .5 a 67 .6 7 4. 11 10 4. 7a b 85 .3 9a b 5. 77 1. 4 6. 33 7. 82 ab c 34 34 .3 ab 46 87 .7 a 13 74 3. 3a b 16 02 7. 7a 10 30 9a b 11 34 0. 7 25 .3 ab c 31 a 41 .5 3a 66 .6 7 5. 54 10 5. 10 ab 88 .8 1a 6. 52 1. 67 6. 8 7. 98 ab 37 94 .3 a 48 61 .3 a 16 52 3. 3a b 21 87 4. 7a 12 72 9a 17 01 4 23 bc 22 b 38 .4 64 .6 7 6. 85 99 .5 7a b 80 .3 9a b 9. 31 1. 53 6. 8 7. 38 bc 35 29 .3 ab 39 93 .3 ab 13 62 6. 7a b 18 40 2. 7a 10 09 7. 3a b 14 41 0 26 ab 22 b 37 .3 7 71 .3 8. 22 10 8. 63 a 88 .9 7a 7. 33 1. 6 7. 87 8. 18 a 36 10 .7 ab 39 93 .3 ab 16 17 6. 7a 17 01 3. 3a 12 56 6a 13 02 0 22 .3 3c 23 .6 7a b 38 .1 3 65 .6 7 Si gn if ca nc e le ve l ∗ ∗ N S N S N S ∗ ∗ ∗ ∗ ∗ ∗ N S ∗ ∗ N S N S LS D (0 .0 5) 14 .2 5 11 .3 8 4. 44 0. 59 1. 92 0. 75 44 2. 31 11 69 .7 33 19 .6 81 80 .4 29 43 .3 14 .6 3. 34 7. 97 7. 3 14 .7 8 C V (% ) 7. 74 7. 52 34 .7 9 22 .5 6 15 .5 7 5. 36 6. 99 15 .5 9 12 .8 3 25 .7 1 15 .0 5 72 07 .3 7. 77 17 .9 9 10 .2 1 12 .4 N ot e. pH � pl an th ei gh t, N T � nu m be ro ft ill er s, SL � sp ik e le ng th ,G Y � gr ai n yi el d, A G B � ab ov e- gr ou nd bi om as s( kg /h a) ,S Y � st ra w yi el d (k g/ ha ), H I� ha rv es ti nd ex ,a nd TG W � th ou sa nd -g ra in w ei gh t( gm ). 8 International Journal of Agronomy liming was minimal, which may imply the need for in- tegrated soil management for enhancing nutrient availability [24]. Combined data from the two years showed a signif- cantly higher available P of 7.74mg/kg in 2020 compared to 4.41mg/kg in 2021. Te observed lower available P in the second year could be associated either with the refxation of P due to the lowering in soil pH or the increase in ex- changeable acidity in that year. Applications of lime did not signifcantly afect TN in both the 1st and 2nd year of the experiment (Table 2). However, in absolute terms, a higher TN of 0.65% and 0.51% was measured from plots treated with 5.54 t/ha in the 2021 and 2020 cropping seasons, followed by 0.5% and 0.49% in plots treated with 4.11 t/ha in the same year (Table 2). Te increased TN in plots treated with lime indicates the potential of lime for enhancing OM decomposition. Soil OC was signifcantly (p< 0.01) af- fected by lime application in 2021, while the infuence of lime on soil OC in the 2020 cropping period was not signifcant (Table 2). In the 2021 cropping season, a signifcantly lowOCof 3.86% was measured from plots treated with the highest rate of 8.22 t/ha lime (Table 2), implying that higher rates of lime application may not be benefcial for microbial activities and associated OM decomposition. On the contrary, data combined over the two years showed a signifcant (p< 0.05) efect of lime application on OC (Table 3). Te lowest signifcant OC of 4.33% was ob- tained from the application of the highest rate of lime (8.22 t/ ha). Low soil OC contents in plots treated with the highest rate of lime (8.22 t/ha) compared to the control plots could be associated with rapid changes in pH, which might not be benefcial for microbial activities and OC decomposition. 3.2. Efects of Liming on Barley Yield and Yield Components. Te application of lime signifcantly (p< 0.05) afected grain yield, total biomass, and plant height (Table 4). Separate analysis of data from the two years showed that the highest grain yields of 4,861 and 3,794.3 kg·ha−1 were obtained in 2021 and 2020 from plots treated with 5.45 t·ha−1, respectively. Tese are 40% and 19.4% higher than the yields obtained from the control plot, respectively (Table 4). Te higher grain and biomass yield in 2021 than 2020 from the application of 5.54 t·ha−1 of limemay refect a higher residual efect of liming on crop yield than fresh application. Similarly, a signifcantly higher biomass of 21,875 and 16,523 kg·ha−1 was obtained from plots treated with 5.45 t·ha−1 in the 2021 and 2020 cropping seasons, respectively, which are 53.7% and 37.6% higher than biomass collected from the control plot in the respective years (Table 4). Signifcantly higher plant heights of 108.63 and 88.97 cm were measured from plots treated with 8.22, followed by 88.97 and 88.81 cm from plots treated with 5.45 t·ha−1 lime in 2020 and 2021, respectively (Table 4). Tese results agree with a recent review [5] that reported a grain yield increment in the range of 34–252% in wheat, barley, and tef in response to liming in SSA. Te recent study by (32) also revealed that the application of lime in combination with inorganic fertilizer increased tef yield by 43–54% and wheat yield by 28–32%. Te combined analysis of data from the two years in- dicates a signifcant efect of liming on yield and other yield components except for spike length and thousand-grain weight (Table 5). Interyear variations in barley yield and yield components were also signifcant except for the harvest index (HI) (Table 5). However, the interaction of the lime rate and year was not signifcant (Figure 3). Applications of diferent rates of lime had a highly signifcant (p< 0.01) efect on plant height and a signifcant efect (p< 0.05) on the number of tillers per plant, straw yield, HI, grain yield, and total biomass with exception of spike length and thousand- grain weight (Table 5). Across the two years, the application of lime at the rate of 5.45 1 t·ha−1 resulted in the highest barley grain yields of 4,328 kg·ha−1 and the total biomass of 19,199 kg·ha−1 which are 30% and 46% higher than grain and biomass yield collected from the control plot, respectively (Table 5). Conversely, the lowest grain yield of 13123 kg·ha−1 Table 5: Yield and yield components of barley as afected by lime and year combined over 2 years on Nitisols in southern Ethiopia. Treatments Plant height (cm) Tillers per plant (no.) Spike length (cm) Total biomass (kg/ha) Grain yield (kg/ha) Straw yield (kg/ha) HI (%) TGW (g) Year 2020 101.19 7.0a 6.8b 14224b 3476b 10748b 24.4 39.4b 2021 83.17 1.4b 7.7a 17486a 4138a 13348a 23.7 45.8a Signifcance level ∗∗ ∗ ∗ ∗ ∗ ∗ NS ∗∗ LSD (0.05) 6.5 0.47 0.52 3236 558 2494 1.3 10.7 Lime rate (t·ha−1) Control 84.5b 3.6b 6.7 13123c 3326b 9797c 25.3ab 50.2 2.74 87.8ab 4.2ab 7.1 15312ab 3564ab 11749ab 23.3ab 53.6 4.11 95ab 3.6b 7.1 14886b 4061ab 10825b 27.3a 54.1 5.54 97ab 4.1ab 7.4 19199a 4328a 14872a 22.5c 51.5 6.85 90ab 5.4a 7.1 16015ab 3761ab 12254ab 23.5ab 54.3 8.22 98.8a 4.5ab 8.0 16595ab 3802ab 12793ab 22.9b 51.9 Signifcance level ∗∗ ∗ NS ∗ ∗ ∗ ∗ NS LSD (0.05) 12.8 1.4 1.4 4227 881 3492 5.1 10.6 CV (%) 7.6 21.1 11.1 19.6 12.7 21.1 11.7 12.2 Note. Signifcant at ∗p≤ 0.05, ∗∗p≤ 0.01, and ∗∗∗p≤ 0.001; NS: not signifcant. Within a column, means followed by diferent letters are signifcantly diferent at p< 0.05. LSD: least signifcant diference; CV: coefcient of variation. International Journal of Agronomy 9 and the total biomass of 3326 kg·ha−1 were obtained from the control treatment (Table 5). Grain yield response to the lime rate in ascending order was 2.74 (7%)< 6.85 (13%)< 8.22 (14%)< 4.11 (22%)< 5.48 (30%) t·ha−1 (Table 5). Tese results indicate that high lime rates such as 6.85 and 8.22 t·ha−1, despite sharply increasing soil pH had their pH efects, were not refected in a pro- portional increase in barley yield. Te sharp increase in pH might adversely afect microbial activities, OM de- composition, N cycle and nutrient imbalance, and barley growth and yield [20, 24]. For instance, lower soil OC and TN were measured from plots that received the highest lime rate of 8.22 t·ha−1 (Tables 2 and 3). Te same trend was observed with the application of a low rate of lime, i.e., 2.74 t·ha−1, indicating that both low and high rates could afect barely yield negatively. Other yield components data such as straw yield and HI were also signifcantly afected in response to lime application (Table 5). A signifcantly higher HI of 27.3% was measured from plots treated with 4.11 t·ha−1. Likewise, a higher HI of 31% was measured from the same treatment in the 2021 cropping period (Table 4). Te observed relatively higher HI in plots treated with 4.11 t·ha−1 lime could be associated with improvement in plant available P compared to other plots (Table 3). Improvements in yields of barley in plots treated with 4.11 and 5.45 t·ha−1 lime could be associated with increasing pH and an increase in available plant nutrients (e.g., available P) and exchangeable cations (Ca+2 and K+) (Ta- bles 2 and 3). Another reason for the improvement in barley yield in plots treated with 4.11 and 5.45 t·ha−1 lime might be the reduction of EA and H+ and Al+3 (Tables 2 and 3) which is in line with the fnding of the authors of [25–27]. It is obvious that the neutralization of aluminum and manganese could create a conducive environment for the growth of plant roots, and this may have led to greater uptake of water and nutrients [12, 28, 29]. Tis is confrmed by the observed positive and strong correlations between barley yield and desirable soil properties (pH), available P, OC, and TN (r= 0.36, 0.49, 0.64, 0.52), respectively (Table 6). Even though liming improved barley yield, barley yield gain measured in this study was lower than reported by other studies [5, 11, 18]. For instance, Desalegn et al. [11] reported barley yield increments of 133% resulting due to integrated use of lime and inorganic fertilizers. Te combined analysis of variance over 2 years showed that the year efect was signifcant (p≤ 0.05) for the number of tillers per plant, spike length (cm), total biomass (kg·ha−1), grain yield (kg·ha−1), and straw yield (kg·ha−1) and (p≤ 0.01) for plant height (cm) and thousand-grain weight (g), but not for the harvest index (HI) of food barley (Table 5). Te highest mean barley grain yield (4138 kg·ha−1) and total biomass (17486 kg·ha−1) were obtained in the 2020 cropping season (Table 5). Tis result is in line with the fnding of the authors of [5, 30] who found a higher barley yield in the third year than the yields obtained in the frst and second years after the application of lime in Ethiopia. Te residual efects of liming are known to last fve to seven years [5, 24]. Likewise, a signifcantly higher thousand-grain weight of 45.8 g was recorded in 2021 than 39.4 g recorded in 2020 (Table 5). Te improvement in barley biological yield in the second year could be associated with high rainfall distri- bution and the decline in Al3+ due to the residual efects of liming (Tables 2 and 3). Generally, the application of lime improved soil prop- erties and nutrient availability and reduced Al+3, Mn+2, and H+ toxicity (Tables 2 and 3). Te combined yield and bio- mass over the 2 years showed that the most optimal rates of lime for barley production in the study area were 4.11 and 5.54 t·ha−1, with respective yield gains of 27 and 30%, re- spectively. Te observed yield gain ranged between 7 and 30% was lower than the yield gain of 52–81% reported by the authors of [11] but within a similar yield gain of 15–68% reported by the authors of [31] and higher than the yield gain of 4–41% reported by the authors of [30] in the highlands of Ethiopia. Te observed lower relative grain yield response to lime application in this study could be due to sole appli- cation of lime, and thus, the recommended lime rate should be integrated with inorganic or organic fertilizer for in- creasing barley yield. Partitioning of the treatments into single degrees of freedom of orthogonal contrasts revealed that grain yield, total biomass, and plant height of barley signifcantly dif- fered due to diferent rates of lime (Table 7). Te frst contrast (control vs. lime treatment (T)) had a highly sig- nifcant (p< 0.05) efect on grain yield, total biomass, and plant height of barley. Te results showed no signifcant efects between T2 vs. T3–T6 and T3 vs. T4–T6 on grain yield (Table 7). Tis clearly indicates that there are no signifcant Table 6: Correlation coefcients among plant parameters and soil nutrient concentrations as afected by diferent rate of liming on Nitisols in southern Ethiopia. Parameters Height Tillers Yield Biomass pH Av. P CEC OC TN Tillers 0.76∗∗ Yield 0.41∗ 0.46∗∗ Biomass 0.57∗∗ 0.43∗∗ 0.84∗∗∗ pH 0.38∗ 0.12ns 0.36∗ 0.35∗ Av. P 0.56∗∗ 0.77∗∗ 0.49∗∗ 0.51∗∗ −0.57∗∗ CEC 0.26ns 0.27ns 0.11ns 0.06ns 0.11ns 0.03ns OC 0.64∗∗ 0.82∗∗∗ 0.54∗∗ 0.49∗∗ 0.15ns 0.79∗∗ 0.14ns TN 0.52∗∗ 0.39∗ 0.49∗∗ 0.46∗∗ 0.04ns 0.22ns 0.02ns 0.36∗ EA −0.51∗∗ −0.24ns −0.39∗ −0.32∗ −0.67∗∗ −0.01ns −0.16ns −0.06ns −0.09ns ∗p≤ 0.05, ∗∗p≤ 0.01, and ∗∗∗p≤ 0.001; ns: not signifcant. 10 International Journal of Agronomy diferences among the four treatments, i.e., between T2, T3, T5, and T6 on barley grain yield as evidenced in the yield data in Table 4. A study by the authors of [5] also reported similar results on yields of barley, wheat, and tef due to the application of integrated soil fertility management practices. 3.3. Correlations among Soil Properties, Barley Yield, and Yield Components. Pearson correlation analysis indicated that plant height was positively correlated with soil pH (r� 0.38∗), soil available P (r� 0.58∗∗), soil OC (r� 0.64∗∗), and total N (r� 0.52∗∗). Similarly, grain yield and total biomass had positive and strong correlations with soil pH (r� 0.36∗ and 0.35∗), soil available P (r� 0.49∗∗ and 0.51∗∗), soil OC (r� 0.54∗∗ and 0.49∗∗), and TN (r� 0.49∗∗ and 0.46∗∗). Conversely, EA was negatively correlated with plant height (r� −0.51∗∗), grain yield (r� −0.39∗), and total biomass (r� −0.32∗), indicating an inverse relationship where yield and growth parameters increased as EA de- creased (Table 6). Grain yield was positively and strongly correlated (r� 0.84∗∗∗) with total biomass (Table 6). Te grain yield was also positively correlated with the number of Table 7: Variance ratios and probabilities of single degrees of freedom of orthogonal contrasts for the efects of diferent rates of liming on crop growth and yield on Nitisols in southern Ethiopia. Parameters Control vs. (T2–T6) T2 vs. T3–T6 T3 vs. T4–T6 T4 vs. T5-T6 Plant height Variance ratio 425.6 262.5 0.18 26.3 F-probability 0.0067 0.0282 0.9510 0.4644 Number of tillers Variance ratio 2.86 0.15 5.23 2.88 F-probability 0.3200 0.8198 0.1831 0.3183 Spike length Variance ratio 1.79 0.34 0.80 0.11 F-probability 0.0976 0.4618 0.2601 0.6704 Grain yield Variance ratio 1.67E+ 06 863773 42583 1.19E+ 06 F-probability 0.0151 0.0710 0.6776 0.0363 Total biomass Variance ratio 5.37E+ 07 8.89E+ 06 2.56E+ 07 3.35E+ 07 F-probability 0.0391 0.3818 0.1444 0.0972 Straw yield Variance ratio 3.65E+ 07 4.22E+ 06 2.77E+ 07 2.21E+ 07 F-probability 0.0514 0.4911 0.0864 0.1235 Harvest index Variance ratio 9.34 1.63 112.50 4.00 F-probability 0.3551 0.6966 0.0034 0.5428 1000 grain weight Variance ratio 40.898 1.80 10.20 10.13 F-probability 0.3371 0.8387 0.6289 0.6300 Table 8: Marginal and partial budget analyses of diferent rates of lime application combined over 2 years on Nitisols in southern Ethiopia. Lime rate (t·ha−1) Control 2.74 4.11 5.54 6.85 8.22 Average grain yield (kg·ha−1) 3330 3560 4060 4330 3760 3800 Adjusted grain yield (kg·ha−1) 2990 3210 3650 3890 3390 3420 Average straw yield (kg·ha−1) 9800 21700 21130 27600 22350 25360 Adjusted straw yield (kg·ha−1) 8820 19530 190200 24840 20120 22820 Gross beneft from grain 89,791.5 96,219.9 109,644.3 116,847 101,552.1 102,650.2 Gross beneft from straw 36,240.8 80,282.4 78,173.2 102,094 82,676.0 93,803.3 Total gross beneft (ha−1) 126,032.2 176,502.3 187,817.5 218,942.1 184,228.1 196,453.5 Field cost of lime (ha−1) — 11,234.0 16,851.0 22,468.0 28,085.0 33,702.0 Field cost of labor (ha) — 1,808.4 2,712.6 3,616.8 4,521.0 5,425.2 Total variable cost (birr/ha) — 13,042.4 19,563.6 26,084.8 32,606.0 39,127.2 Net beneft (birr/ha) 126,032.2 163,459.9 168,253.9 192,857.3 151,622.1 157,326.3 MRR 1.74 3.87 4.77 D∗ D∗ MRR (%) 174% 387% 477% ∗Dominated; ∗1USD� 47 Ethiopian birr at the time of the study. Price of barley grain� 30 birr kg−1; price of barley straw� 4.11 birr kg−1. Temarket price of lime� 4.5 birr kg−1; labor cost for spreading lime� 50 ETB per person-day. International Journal of Agronomy 11 tillers per plant and plant height (r� 0.46∗∗ and 0.41∗), respectively (Table 6). Total biomass had a positive and strong correlation with plant height and the number of tillers per plant (r� 0.57∗∗ and 0.43∗∗, respectively). A systematic review by Agegnehu et al. [5] reported related patterns of correlations between the barley grain yield and soil pH level and wheat grain yield and soil pH [32], implying the sen- sitivity of barley to soil acidity. 3.4. Economic Viability of Liming. Te application of 5.54 t·ha−1 lime provided the highest net beneft of ETB 192,857.3 ha−1 (Table 8). Te net beneft from the control treatment was ETB 126,032.2 ha−1 (Table 6). It is apparent that changing lime rates from 4.11 t·ha−1 to 5.48 t·ha−1 gave a positive and highest MRR of 477%. As a rule of thumb, an MRR of below 100% is considered low and unacceptable to ofset management and transaction costs [17]. Te eco- nomic return from using 5.48 t·ha−1 of lime was fourfold greater than the minimummarginal rate of return required to justify the acceptance of lime application, implying a return of 4.77 birr on every birr spent in liming appli- cation. Tis could be attractive enough to motivate farmers to adopt liming. 4. Conclusions Te results from this study showed signifcant improve- ments in soil chemical properties, nutrient availability, and crop yield and better economic return from liming of acidic soils. Considering the amendment efect of soil acidity, crop yield, and economic benefts, we recommend 5.45 t·ha−1 of lime as the optimum rate for barley production on acidic Nitisols in southern highlands of Ethiopia followed by the second best rate of 4.11 t·ha−1. Applications of 4.11 and 5.54 t·ha−1 of lime increased grain yield by 22 and 30% over the control, respectively. Te slight rise in EA and a corre- sponding decline in soil pH in the second year compared to the frst year may be an indication of a weaker residual efect of liming. A longer term study than considered in this study may provide a better picture of the residual efects of liming in the area. In economic terms, return from acid soil amendment with liming far outweighs investment. For example, the application of 5.48 t·ha−1 of lime provided an MRR of 477%, implying a return of 4.77 birr on every birr spent in liming application. Further experiments on in- tegrated acid soil amendments involving diferent rates of lime and organic and inorganic fertilizers are suggested to see improvements in the overall physicochemical and bi- ological properties of soils and crop yield. Data Availability Data will be made available from the corresponding author upon request. Conflicts of Interest Te authors declare that they have no conficts of interest. Authors’ Contributions Getahun Haile designed the feld experiment, collected soil and agronomic data, analyzed the data, and wrote the manuscripts. Habtamu Berihun and Helina Abera con- tributed to feld data collection. Getachew Agegnehu con- tributed to analyzing the agronomic and soil data and reviewing the manuscript and quality assuring the overall work. Mulugeta Lemenih contributed to reviewing the manuscript and quality assuring the overall work. Acknowledgments Te authors’ special thanks go to the administrators and development agents of Bule District, Gedeo Zone, for their assistance in the execution of the feld experiment. Tey also thank local farmers for allowing their farm felds to conduct the trials for two consecutive years. Tey received research grant from Dilla University.Tey would like to acknowledge Dilla University for funding this study. References [1] L. V. Kochian, O. A. 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