Vol. 17(4), pp. 629-641, April, 2021 DOI: 10.5897/AJAR2021.15463 Article Number: CC4BE3B66609 ISSN: 1991-637X Copyright ©2021 African Journal of Agricultural Author(s) retain the copyright of this article http://www.academicjournals.org/AJAR Research

Full Length Research Paper

Nutrients balance approach with emphasis on base cations and ratios concepts as a decisions-support tool in optimizing fertilizers use

Assefa Menna

Debre Zeit Agricultural Research Center, Ethiopian Institute of Agricultural Research (EIAR), P. O. Box - 2003, Addis Ababa, Ethiopia.

Received 21 January, 2021; Accepted 16 March, 2021

Thirty-six samples collected from 24 sites were used to investigate the relationships between cation-ratio concepts and sufficiency level approaches in plant nutrition. Based on threshold values, about 25.0% of the had calcium:magnesium (Ca:Mg)-ratio fallen outside developed favorable range, despite the sufficient levels of individual elements in soils, violating the base cation ratio concept. Similarly, 63.0% of soils had potassium:magnesium (K:Mg)-ratio falling in the unfavorable range for K uptake, though individual element K was found to be above adequate in all sites/soils. In 29.0% of soils, (Mg:K)-ratio is rated unfavorable for nutrients’ uptake, the directly level to sufficiency level concepts. Likewise, all soils had the % K:TEB (total exchangeable bases)-ratio falling within the suggested fav orable range for the most tropical crops, favoring the two concepts. With respect to Ca:TEB ratios, 79.0% of soils were considered unfavorable for Mg and/or K uptake, implying that the lower the base saturation, more favorable the conditions for the aforementioned nutrients uptake and vice-versa. This is also against the base cations’ saturation ratio concept because all soils in those sites had low levels of Ca and Mg. In conclusion, therefore, from such contradictory information, those generated the validity of the base cations’ ratio concept need further detailed investigation.

Key words: Potassium, calcium, magnesium, ratios, fertilizers, rhizosphere.

INTRODUCTION

Sharply rising human population and associated factors (Hurni et al., 2010). Indeed, this is a continuous process have degraded the natural resource base, the soil, thus affecting food and nutrition security in the country. For threatening sustainable agriculture in Ethiopia. In this example, some Vertisols in the central Ethiopian country, soil/land degradation is mainly due to intensive agricultural lands have problems of phosphorus (P) and cropping, overgrazing and unsustainable land-use and related nutrients fixing characteristics. Many were also tenure systems, which further aggravated the loss of soil reported to be poor in essential plant nutrients and quality. Among the soil degradation processes, nutrients organic carbon (OC) (Menna, 2017, 2018, 2019). unavailability or depletion and imbalances; and the In our previous research works, soil-testing combined reduction in total and biomass carbon are the major ones with crop response data primarily have been used as a

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decision-support tool in optimizing nutrients management. pre-soil testing, but on areas approximately 0.5 to 1.5 miles away With regard to soil-testing two general principles were from first season(s) S responsive sites, Do1, Bk1 and BT1, evolved. The major one was the Crop Nutrient respectively. In both seasons, randomized complete block design Requirement/ Sufficient Level of Available Nutrient (RCBD) was used and was replicated three times. All soil samples were taken from 10 spots per block, bulked and further composted (CNR/SLAN) concept, which was built on the concept to make a composite sample per farmer field and/or soil depths. that there are certain levels of plant nutrients in soils that The disturbed samples were then air-dried immediately in dry- 2- can be defined as optimum. Below those defined levels, rooms to avoid SO4 formation from organic matter (OM) in transit, crops will respond to the application of nutrient in ground and sieved to pass through 1-mm sieve. Then, duplicate question. The other was the Base Cation Saturation Ratio analysis was made for different soil variables using wet chemistry (BCSR), which promotes the concept that maximum yield laboratory (Labs) at Sokoine University of Agriculture (SUA), Tanzania and Holeta and Debre Zeit research centers (EIAR), can only be achieved by creating an ideal ratio of calcium Ethiopia as per the methods outlined in Table 1. Finally, the cation (Ca), magnesium (Mg), potassium (K) and sodium (Na) in ratios were calculated using the respective variables. Micro- soils. A more detailed discussion of the two approaches nutrients copper (Cu), manganese (Mn), iron (Fe), zinc (Zn), boron was based on the works by Eckert (1987). In fact, the (B) and molybdenum (Mo) were also considered. base saturation and ratios concept were based on much earlier works provided by Hunter et al. (1943), Bear and Toth (1948), and Hunter (1949). According to Bear et al. RESULTS AND DISCUSSION (1945) for ideal soil it was suggested that, the bulk of exchangeable complex should be occupied by Ca, Mg, K Tables 2 to 4 present the selected physico-chemical and hydrogen (H). However, this was later relaxed by variables of the studied soils. As presented, the studied Graham (1959). About 20 years later, Baker and soils varied in their properties, which could be peculiar to Amacher (1981) defined normal values as 60 to 80% for the specific AEZs. The upcoming discussions focus on Ca, 10 to 20% for Mg and 2 to 5% for K. the percent saturation, ratios concepts and related soil Based on these general descriptions, therefore, the aim properties that are assumed to guarantee high yields and of this research work was (1) to assess the concept of crop quality. BCSRs and (2) to see the relationships between SLAN and BCSR approaches in the studied soils. The study also aimed at looking at the relationship between some Major cations and some basic ideas soil variables and wheat yield at native soil conditions. It 2+ is hypothesized that a strong-positive relationship The cations used in largest amounts by plants are Ca , + 2+ between the SLAN and BCSR concepts would exist. K and Mg , which exist in the soil solution in the form of ions. Cations are absorbed from the soil solution (thin film of water around plant roots, root hairs and soil particles) MATERIALS AND METHODS by actively growing plants. The exchange sites are Site selection negatively charges associated with sized particles, and some of the soil organic matter (SOM). The cations In the present investigation, soil samples collected from 24 sites, in at the exchange site are in equilibrium with those in the three representative locations in central Ethiopian agricultural lands, soil solution. The number of negative charges can be namely Arsi (Ar), East-Shewa (ES) and West-Shewa (WS) zones were considered. The three study areas were selected and geo- measured analytically and is referred to as the cation referenced using Global Positioning System (GPS-GARMIN; model exchange capacity (CEC). It is widely recognized that, number GPS-60) assisted by Google earth (2011), and were the availability of nutrients for plant uptake does not classified by elevation and agro-ecological zones (AEZs) and soil- depend only on their absolute levels, but also on the type when known. The sites, then, were used for conducting 24 relative amounts of individual elements and different base sulfur (S) response and/or S rate determination experiments in wheat or faba bean. The specific locations and salient features of cation ratios in soils. Indeed, percent saturation and the selected sites are presented in Figure 1. . electrical conductivity (EC) of the studied soils were assumed to have direct relationships with the pH.

Soil sampling, preparation and analysis

The first 18 surface soil samples (0-20 cm soil depth) were Soil physico-chemical properties collected before planting each of the 18 sulfur (S) response experiments (2013-2014). Similarly, the other 18 soil samples were The studied soils showed important variations in the collected from 0-20 cm, 20-40 cm and 40-60 cm soil depths at each physico-chemical variables and nutrient contents. site in season-II (2015-2016) before planting the test crop(s) Exchangeable-Al was detected in strongly acidic soils (Tables 2 to 4). The three fields, namely GS2, Ke2 and NS2 in season-II, were and this was positively correlated with Ca and Mg selected based on the experimental conditions in seasons-I. deficiency, which may necessitate the application of Ca Whereas, WG/Do2, Bk2 and BT2 were selected randomly without and Mg containing fertilizers or liming in those sites. All

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Figure 1. Locations map showing study site-fields in Arsi, East- and West-Shewa zones of central Ethiopia. 1 = Abosara Alko (AA); 2 = Dosha (Do1); 3 = Gora Silingo (GS1 or 2); 4 = Chefe Misoma (CM); 5 = Boneya Edo (BE); 6 = Boro Lencha (BL); 7 = Chefe Donsa (CD); 8 = Keteba (Ke1); 9 = Ude (Ud); 10 = Bekejo (Bk1); 11 = Insilale (In); 12 = Kilinto (Ki); 13 = Nano Kersa (NK); 14 = Nano Suba (NS1); 15 = Berfeta Tokofa (BT1); 16 = Dawa Lafta (DL); 17 = Wajitu Harbu (WH); 18 = Tulu Harbu (TH: 1st season); 19 = Wonji Gora (WG/Do2); 20 = GS2; 21 = Ke2; 22 = Bk2; 23 = NS2; and 24 = BT2 (2nd season). The numbers (1) and (2) indicate the information which was generated in 1st and 2nd seasons, respectively and soil-type when known.

the soils were salt-free or had no sodicity problems. But, and Ca were found to be limiting depending on the AEZs the exchangeable aluminium (Al3+) was detected in and pH of soils. In similar approach, from the micro- 21.0% of the sites as a manifestation of strongly acidic nutrients: B, Zn, Mo and Fe were found limiting, all in the soil reactions in WS zone. In all soils, the exchangeable decreasing order of importance. This in fact, was in K+ was adequate or above based on the critical levels accordance with the work reported by Menna (2019). (CLs) developed in other locations. Some 21.0% of the Therefore, it is recommended that the deficient amounts soils contained low levels of Ca2+ with values falling of nutrients need to be applied or formulated for the below the suggested thresholds. Still some, 13.0% were specific sites based on the soil-test and plant analysis. marginal, leaving 67.0% of the sites to be safe from Ca- deficiency. Calcium was also found to be dominating soil- colloids, particularly, in the ES zone. Similarly, Mg2+ Total exchangeable bases appeared to be deficient in only strongly acidic soils (29.0% of sites). The excess levels of Ca2+, K+ and even The widely accepted general trend of base cations in Mg2+ were observed in the alkaline soils sampled from typical agricultural soils is that Ca should be higher than ES zone. In fact, sandy and strongly acidic soils tend to Mg; Mg higher than K; and K higher than Na. In the have relative lower levels of Ca2+ and Mg2+. present study, basic cations distribution was closely From the information thus generated, depending on the related to the research outputs reported in other areas. extent of severity in the deficiency of nutrient elements The general sequence was Ca2+ > Mg2+ > K+ > Na+ with and proportions and based on the CLs developed for the exception that, some 34% of soils had the K slightly other areas, nitrogen (N), sulfur (S), phosphorus (P), Mg higher than Mg (Table 3). This could to the deviation

632 Afr. J. Agric. Res.

Table 1. The Analytical Method Used for the studied soils

Variable considered Unit(s) of measurement Extraction/Analytical method by: References pH na Potentiometrically,1:2.5 soil:water solution McLean (1986) + 3+ Total Exchangeable Acidity (H & Al ) cmolc/kg 1.0 M KCl and titration by 0.01 M NaOH (pH:7.0) Pansu and Gautheyrou (2006) Electrical Conductivity (EC) mS/cm 1:5 soil:water suspension Klute (1986) + + Exchangeable Bases (Na & K ) cmolc/kg 1M NH4OAc solution, pH =7.00 Rowell (1994) 2+ 2+ Exchangeable Bases (Ca & Mg ) cmolc/kg 1M NH4OAc solution, pH =7.00 Van Reeuwijk (2002)

Cation Exchangeable Capacity (CEC) cmolc/kg 1M NH4OAc solution, pH =7.00 Van Reeuwijk (2002)

Total exchangeable basis (TEB) cmolc/kg Calculate from all the exchangeable bases Peverill et al. (1999) The percent base saturation (PBS) % Calculation from exch. bases Van Reeuwijk (2002) 3+ + Exchangeable Al cmolc/kg The difference between exch. acidity and H Bertsch and Bloom (1996) Total nitrogen (TN) % Kjeldahl as described in Okalebo et al. (2002) Organic carbon (OC) % Walkley-Black as described in Nelson and Sommers (1996) Available P mg/kg Bray-I (pH<7.00) Bray and Kurtz (1945) Available P mg/kg Olsen (pH>7.00) Olsen et al. (1954)

SO4-S mg/kg Calcium Ortho-Phosphate, Turbidimetric Rowell (1994) na Hydrometer method Bouyoucos (1962)

na = Not applicable

of Mg:K ratios or vice-versa from its normality. In nutrient, if soil-test levels are above a defined The present study tries to address BCSR concept all locations, Ca was dominating the exchange sufficient level. The base cation saturation ratio and attempts to relate its relevance with the SLAN site and largely controlling the percent saturation approach. and pH. This was most common particularly in ES (BCSR) approach promotes the concept that zone, the area with alkaline soil reaction. Its maximum yield can only be achieved by creating extent might affect the availability of some an ideal ratio of Ca, Mg and K in soil system. This Cation balances and ratio approaches nutrients like P and Mg to arable crops due to the approach is not concerned with recommendations precipitation reactions. for N, P, S and micronutrients. Calcium to magnesium ratio Today, most soil-testing laboratories in the country use sufficient level or sufficiency level of The proportions of the basic cations of effective Cation saturation percent and ratios the available nutrients (SLAN) approach. Other CEC are accepted to be more relevant to plant areas might adjust recommendations generated performance than the actual levels (Hazelton and The crop nutrient requirement (CNR) approach is from sufficiency level approach with a Murphy, 2007). For example, according to Abbott a soil-testing technique or procedure built on the consideration for the BCSR. (1989), the K saturation percent (3.2 to 5.4%) of concept that there are certain levels of plant A more detailed discussion of the BCSR soils was reported to be desirable proportion for nutrients in soil that can be defined as optimum. approach was provided by Eckert (1987). Fertilizer many plants (Table 2). Nevertheless, antagonism Below some defined level, crops will respond to recommendations based on this concept are could exist when disproportionate quantities of the application of nutrient in question. Likewise, usually different from those based on the SLAN exchangeable cations and ratios are present in crops will not respond to the application of the concept. soils.

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Table 2. Saturation percent, ratios and much related soil physico-chemical variables before planting.

Zo- Soil pH(1:2.5) EC CEC BS/SP Ex.Acidity Ex.Al3+ OC TN C:N Base Cation Ratios Ref. code PV/A Ne type (soil:H2O) (dS/m) cmolc/kg (%) cmolc/kg cmolc/kg (%) (%) (Ratio) Ca:Mg Mg:K K:Mg % K:TEB Ca:TEB Season(s)-I 1-a Ar AA CV 5.95 0.10 23.80 63.20 na na 1.11 0.13 8.85 3.98 1.73 0.58 10.36 0.71 2-a Ar Do1 RNi 5.30 0.10 24.30 42.48 1.47 1.14 2.04 0.25 8.09 5.23 1.32 0.76 10.63 0.73 3-a Ar GS1 CV 6.12 0.11 25.30 68.24 na na 1.17 0.14 8.39 3.86 2.55 0.39 7.37 0.73 4-a Ar CM Ni 6.94 0.18 31.60 71.83 na na 2.75 0.13 20.70 2.44 1.87 0.53 13.28 0.61 5-a Ar BE CV 6.19 0.13 27.80 64.03 na na 2.77 0.20 13.66 2.85 1.92 0.52 11.75 0.64 6-a Ar BL Ni 6.98 0.17 29.80 69.19 na na 1.07 0.11 10.24 3.01 2.59 0.39 8.66 0.68 7-a ES CD PV 7.91 0.19 45.01 96.64 na na 0.90 0.06 14.23 4.62 3.88 0.26 4.34 0.78 8-a ES Ke1 PV 8.14 0.25 45.80 96.47 na na 1.06 0.06 18.84 3.38 1.60 0.63 12.42 0.67 9-a ES Ud PV 7.14 0.16 39.40 90.80 na na 1.23 0.10 12.59 4.31 1.82 0.55 9.29 0.73 10-a ES Bk1 PV 7.33 0.18 34.40 93.39 na na 1.31 0.07 18.76 4.54 2.20 0.45 7.47 0.75 11-a ES In CV 7.15 0.18 31.40 92.65 na na 1.35 0.10 13.80 3.79 2.67 0.37 7.19 0.73 12-a ES Ki PV 8.02 0.24 47.80 95.23 na na 1.39 0.06 24.86 3.81 2.04 0.49 9.19 0.71 13-a OL NK CV 6.71 0.17 26.40 66.98 na na 1.41 0.07 20.17 2.98 1.84 0.54 11.83 0.65 14-a OL NS1 RNI 5.65 0.07 15.00 53.73 na na 1.47 0.13 11.68 2.87 0.61 1.64 29.01 0.51 15-a OL BT1 RNi 5.07 0.06 16.40 41.60 1.56 1.15 1.69 0.12 14.20 2.75 0.79 1.26 24.65 0.54 16-a OL DL RNi 5.86 0.05 18.60 55.91 na na 1.71 0.14 12.21 3.64 0.63 1.58 24.55 0.57 17-a OL WH RNi 5.52 0.08 15.00 51.63 1.01 0.75 2.99 0.15 19.42 3.33 0.50 2.00 30.86 0.51 18-a OL TH RNi 5.62 0.08 22.20 52.25 na na 1.31 0.14 9.38 2.39 0.72 1.38 28.43 0.49

Season(s)-II 19-a Ar WG/Do2 PV 5.36 0.08 32.60 42.22 1.77 1.35 2.71 0.21 12.92 1.95 1.20 0.84 21.12 0.49 19-b Ar WG/Do2 PV 6.26 0.15 32.91 55.02 1.45 1.24 2.41 0.11 21.91 1.85 1.23 0.81 21.12 0.48 19-c Ar WG/Do2 PV 6.76 0.18 31.94 62.22 1.37 1.14 2.06 0.11 18.73 1.09 2.01 0.50 18.32 0.40 20-a Ar GS2 Ni 6.24 0.11 26.80 55.24 na na 2.18 0.17 12.96 1.91 2.80 0.36 10.58 0.57 20-b Ar GS2 Ni 6.63 0.16 27.28 61.24 na na 1.97 0.11 17.62 1.84 1.50 0.66 18.31 0.51 20-c Ar GS2 Ni 6.75 0.19 26.94 65.24 na na 1.67 0.11 14.87 1.61 1.01 0.99 26.82 0.44 21-a ES Ke2 PV 8.00 0.20 45.80 83.31 na na 1.15 0.05 23.56 3.66 2.20 0.45 8.82 0.71 21-b ES Ke2 PV 8.10 0.26 44.99 90.23 na na 0.80 0.03 25.08 3.72 1.88 0.53 10.03 0.70 21-c ES Ke2 PV 8.40 0.45 45.73 93.31 na na 0.81 0.03 26.21 3.81 1.85 0.54 10.01 0.71 22-a ES Bk2 PV 7.15 0.10 33.40 71.26 na na 1.17 0.08 15.25 3.77 2.09 0.48 9.01 0.71 22-b ES Bk2 PV 7.53 0.29 33.74 74.27 na na 0.88 0.05 16.30 4.33 2.11 0.47 8.05 0.74 22-c ES Bk2 PV 7.64 0.44 33.46 83.19 na na 0.79 0.05 14.48 4.35 2.16 0.46 7.84 0.74 23-a OL NS2 RNi 5.85 0.07 13.80 53.16 na na 0.96 0.14 6.83 3.16 0.61 1.65 27.51 0.53 23-b OL NS2 RNi 5.93 0.21 13.87 55.23 na na 0.64 0.07 9.16 3.10 0.62 1.60 27.12 0.52

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Table 2. Contd.

23-c OL NS2 RNi 5.89 0.25 14.56 58.17 na na 0.61 0.06 10.18 2.43 0.75 1.34 27.02 0.49 24-a OL BT2 PV 4.85 0.11 36.20 37.45 2.84 2.17 2.03 0.15 13.16 2.33 0.76 1.31 27.12 0.48 24-b OL BT2 PV 4.94 0.24 35.42 38.54 2.51 2.03 1.70 0.88 1.95 2.33 0.78 1.29 26.45 0.48 24-c OL BT2 PV 4.91 0.26 36.43 39.27 2.40 1.75 1.63 0.58 2.82 1.60 1.16 0.86 23.84 0.44

PV/A = Farmer village or association (1 = Abosara Alko (AA); 2 = Dosha (Do1); 3 = Gora Silingo (GS1 or 2); 4 = Chefe Misoma (CM); 5 = Boneya Edo (BE); 6 = Boro Lencha (BL); 7 = Chefe Donsa (CD); 8 = Keteba (Ke1); 9 = Ude (Ud); 10 = Bekejo (Bk1); 11 = Insilale (In); 12 = Kilinto (Ki); 13 = Nano Kersa (NK); 14 = Nano Suba (NS1); 15 = Berfeta Tokofa (BT1); 16 = Dawa Lafta (DL); 17 = Wajitu Harbu (WH); 18 = Tulu Harbu (TH) (1st season). 19 = Wonji Gora (WG/Do2); 20 = GS2; 21 = Ke2; 22 = Bk2; 23 = NS2; and 24 = BT2 (2nd season). The numbers (1) and (2) indicate the information which was generated in 1st and 2nd seasons respectively; soil variables (EC = electrical conductivity; CEC = cation exchange capacity; PS/SP = saturation percent; OC = organic carbon; TN = total nitrogen; TEB = total exchangeable bases); Soil depth (a = 0–20 cm; b = 20-40 cm; and c = 40–60 cm). na = not applicable. Soil types (CV = Chromic Vertisol, RNi = Red Nitisol, PV = Pellic Vertisol); and Av.P for soils with pH >7.0 (analyzed by Olsen); and for soil with pH < 7.0 (Bray-1 method). Study areas [(Ar = Arsi, ES = East-Shewa = E/Shewa, WS/OL = West-Shewa or OL = Oromia Liyu = O/Liyu)].

In the present investigations, Ca:Mg ratio in the was higher in top-soils than in sub-soils. Whilst Liebhardt (1981), the Ca:Mg ratio of 2.2:1 to surface soils ranged from 1.91 to 5.23. From this, this trend was reversed in alkaline soils sampled 14.3:1 (wider ratios) did not exert a significant the bulk of soils had the ratio in an optimum range from ES zone. Increase of the exchangeable effect on yield and nutritional requirements of According to Landon (1991), the optimum Ca:Mg Ca:Mg ratio with depth might be attributable to the crops. ratio favorable for most crops ranges from 2 to 4. presence of increased levels of CaCO3 in sub- From the results obtained in this study and the As per this criterion, only 25.0% of the soils fall soils or its concentration which is also expected to discussions so far, therefore, Ca:Mg ratio alone outside this optimum. The sites in such category increase with depth due to leaching. In general, can be misleading, as the ratios can be affected include Do, GS, CD, Ude and Bk. However, the Ca:Mg ratio falling outside the suggested by soil and plant factors; the presence or absence except Do1, the rest of the soils (86.0%) had optimum in sub-soils of Do, GS, Bk, and BT may of other nutrients and others. Amézketa (1999) sufficient levels of Ca and Mg (individual need further investigation at pedons level. In observed that basic cation saturation ratios are elements), which contradicts to the BCSR concept. general, the high Ca:Mg ratio observed in some also influenced by soil structure, in particular Landon (1991) reported that, the availability of locations may have detrimental effects on the surface crusting, compaction and hydraulic con- Mg and P to plants becomes less when Ca:Mg uptake of Mg and/or P by crops and may need ductivity. Therefore, our forthcoming research ratio exceeds 5:1. Based on this, however, only appropriate management practices. works should focus on relating Ca:Mg ratios with CD site was found to be beyond this optimum. In In accordance, some authors disprove the specific crop response, tissue analysis and the this site, the availability of Mg and/or P may be usefulness of the overall BCSR concept (John, individual basic cations data including the analysis impaired due to this reason. It might, therefore, be 2005; Kopittke and Menzies, 2007). Similarly, at pedons level. important to apply Mg and P containing fertilizers Ologunde and Sorensen (1982) reported that, in to keep an appropriate balance. soils with an optimal supply of base cations, the A clear trend of change of Ca:Mg ratio with ratios generally did not influence plant yield. Magnesium to potassium ratio depth was observed. Though not significant in the Numerous other studies revealed that in soils with context of shallow rooted crops, sub-soils of Do balanced pH, the Ca:Mg ratio had a limited The Mg:K ratios for the studied surface soils and GS (Arsi), Bk (ES) and BT (WS) zones fallen influence on yield and mineral composition of ranged from 0.50 to 3.88. The Mg:K ratio for outside of the optimum range. In the acid soils like plants (Fox and Piekielek, 1984; Kelling et al., optimum nutrients uptake by plants was reported that of Arsi and WS, the Ca:Mg ratio tends to 1996; Schönbeck, 2001; Zalewska et al., 2017). In to be between 1 and 4 (Landon, 1991). Based on decrease with depth, showing that, the Ca content studies by McLean and Carbonell (1972) and this, 29.0% of the soils had Mg:K ratio below this

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Table 3. Bases cations and related soil variables before planting.

Soil pH(1:2.5) EC CEC BS/SP Ex.Acidity Ex.Al3+ OC TN C:N Exchangeable Bases (cmolc/kg) TEB Ref. code Zo-Ne PA/FA type (soil:H2O) (dS/m) cmolc/kg (%) cmolc/kg cmolc/kg (%) (%) (Ratio) Ca2+ Mg2+ K+ Na+ (cmolc/kg) Season(s)-I 1-a Ar AA CV 5.95 0.10 23.80 63.20 na na 1.11 0.13 8.85 10.74 2.70 1.56 0.04 15.04 2-a Ar Do1 RNi 5.30 0.10 24.30 42.48 1.47 1.14 2.04 0.25 8.09 7.55 1.44 1.10 0.23 10.32 3-a Ar GS1 CV 6.12 0.11 25.30 68.24 na na 1.17 0.14 8.39 12.52 3.25 1.27 0.23 17.26 4-a Ar CM Ni 6.94 0.18 31.60 71.83 na na 2.75 0.13 20.70 13.76 5.64 3.02 0.28 22.70 5-a Ar BE CV 6.19 0.13 27.80 64.03 na na 2.77 0.20 13.66 11.45 4.03 2.09 0.23 17.80 6-a Ar BL Ni 6.98 0.17 29.80 69.19 na na 1.07 0.11 10.24 13.94 4.62 1.78 0.27 20.62 7-a ES CD PV 7.91 0.19 45.01 96.64 na na 0.90 0.06 14.23 33.90 7.33 1.89 0.38 43.50 8-a ES Ke1 PV 8.14 0.25 45.80 96.47 na na 1.06 0.06 18.84 29.65 8.77 5.49 0.28 44.18 9-a ES Ud PV 7.14 0.16 39.40 90.80 na na 1.23 0.10 12.59 26.10 6.06 3.32 0.29 35.77 10-a ES Bk1 PV 7.33 0.18 34.40 93.39 na na 1.31 0.07 18.76 23.97 5.28 2.40 0.47 32.13 11-a ES In CV 7.15 0.18 31.40 92.65 na na 1.35 0.10 13.80 21.13 5.58 2.09 0.28 29.09 12-a ES Ki PV 8.02 0.24 47.80 95.23 na na 1.39 0.06 24.86 32.48 8.53 4.18 0.32 45.52 13-a OL NK CV 6.71 0.17 26.40 66.98 na na 1.41 0.07 20.17 11.45 3.85 2.09 0.29 17.68 14-a OL NS1 RNI 5.65 0.07 15.00 53.73 na na 1.47 0.13 11.68 3.48 1.21 1.99 0.19 6.86 15-a OL BT1 RNi 5.07 0.06 16.40 41.60 1.56 1.15 1.69 0.12 14.20 3.65 1.33 1.68 0.16 6.82 16-a OL DL RNi 5.86 0.05 18.60 55.91 na na 1.71 0.14 12.21 5.06 1.39 2.19 0.30 8.94 17-a OL WH RNi 5.52 0.08 15.00 51.63 1.01 0.75 2.99 0.15 19.42 3.83 1.15 2.30 0.17 7.44 18-a OL TH RNi 5.62 0.08 22.20 52.25 na na 1.31 0.14 9.38 5.05 2.11 2.91 0.18 10.24

Season(s)-II 19-a Ar WG/Do2 PV 5.36 0.08 32.60 42.22 1.77 1.35 2.71 0.21 12.92 5.11 2.62 2.19 0.47 10.39 19-b Ar WG/Do2 PV 6.26 0.15 32.91 55.02 1.45 1.24 2.41 0.11 21.91 5.21 2.82 2.29 0.54 10.86 19-c Ar WG/Do2 PV 6.76 0.18 31.94 62.22 1.37 1.14 2.06 0.11 18.73 5.35 4.92 2.45 0.67 13.39 20-a Ar GS2 Ni 6.24 0.11 26.80 55.24 na na 2.18 0.17 12.96 6.11 3.20 1.14 0.34 10.80 20-b Ar GS2 Ni 6.63 0.16 27.28 61.24 na na 1.97 0.11 17.62 6.35 3.45 2.29 0.42 12.50 20-c Ar GS2 Ni 6.75 0.19 26.94 65.24 na na 1.67 0.11 14.87 6.75 4.20 4.14 0.34 15.44 21-a ES Ke2 PV 8.00 0.20 45.80 83.31 na na 1.15 0.05 23.56 30.35 8.29 3.77 0.32 42.73 21-b ES Ke2 PV 8.10 0.26 44.99 90.23 na na 0.80 0.03 25.08 31.08 8.35 4.44 0.36 44.22 21-c ES Ke2 PV 8.40 0.45 45.73 93.31 na na 0.81 0.03 26.21 32.35 8.49 4.59 0.42 45.85 22-a ES Bk2 PV 7.15 0.10 33.40 71.26 na na 1.17 0.08 15.25 19.72 5.22 2.50 0.34 27.78 22-b ES Bk2 PV 7.53 0.29 33.74 74.27 na na 0.88 0.05 16.30 23.72 5.48 2.59 0.41 32.20 22-c ES Bk2 PV 7.64 0.44 33.46 83.19 na na 0.79 0.05 14.48 24.77 5.69 2.63 0.45 33.55 23-a OL NS2 RNi 5.85 0.07 13.80 53.16 na na 0.96 0.14 6.83 4.01 1.27 2.09 0.24 7.61 23-b OL NS2 RNi 5.93 0.21 13.87 55.23 na na 0.64 0.07 9.16 4.24 1.37 2.19 0.28 8.08

636 Afr. J. Agric. Res.

Table 3. Contd.

23-c OL NS2 RNi 5.89 0.25 14.56 58.17 na na 0.61 0.06 10.18 4.02 1.65 2.21 0.30 8.18 24-a OL BT2 PV 4.85 0.11 36.20 37.45 2.84 2.17 2.03 0.15 13.16 4.01 1.72 2.26 0.34 8.32 24-b OL BT2 PV 4.94 0.24 35.42 38.54 2.51 2.03 1.70 0.88 1.95 4.24 1.82 2.34 0.45 8.86 24-c OL BT2 PV 4.91 0.26 36.43 39.27 2.40 1.75 1.63 0.58 2.82 4.61 2.89 2.50 0.48 10.49

PV/A = Farmer village or association (1 = Abosara Alko (AA); 2 = Dosha (Do1); 3 = Gora Silingo (GS1 or 2); 4 = Chefe Misoma (CM); 5 = Boneya Edo (BE); 6 = Boro Lencha (BL); 7 = Chefe Donsa (CD); 8 = Keteba (Ke1); 9 = Ude (Ud); 10 = Bekejo (Bk1); 11 = Insilale (In); 12 = Kilinto (Ki); 13 = Nano Kersa (NK); 14 = Nano Suba (NS1); 15 = Berfeta Tokofa (BT1); 16 = Dawa Lafta (DL); 17 = Wajitu Harbu (WH); 18 = Tulu Harbu (TH) (1st season). 19 = Wonji Gora (WG/Do2); 20 = GS2; 21 = Ke2; 22 = Bk2; 23 = NS2; and 24 = BT2 (2nd season). The numbers (1) and (2) indicate the information which was generated in 1st and 2nd seasons respectively; soil variables (EC = electrical conductivity; CEC = cation exchange capacity; PS/SP = saturation percent; OC = organic carbon; TN = total nitrogen; TEB = total exchangeable bases); Soil depth (a = 0–20 cm; b = 20–40 cm; and c = 40–60 cm). na = not applicable. Soil types (CV = Chromic Vertisol, RNi = Red Nitisol, PV = Pellic Vertisol); and Av.P for soils with pH >7.0 (analyzed by Olsen); and for soil with pH < 7.0 (Bray-1 method). Study areas [(Ar = Arsi, ES = East-Shewa = E/Shewa, WS/OL = West-Shewa or OL = Oromia Liyu = O/Liyu)].

range and rated as unfavorable for Mg and/or P directly related to shallow rooted crops growth, the Theoretically, this can be corrected by applying K uptake. The soils in this category came from the sub-soils of NS and BT sites had also Mg:K ratio to bring the K:Mg ratio closer to 0.7:1 (or 1:1). WS zone: NS, BT, DL, WH and TH sites (strongly below this range. It should be noted that the sub- Unfortunately, this was also found to be another acidic soils). Looking at the individual elements in soils in Arsi (slightly acidic) and WS (strongly mismatch between the SLAN and BCSR this area, as directly related, all the soils had low acidic soils) had the problem of Mg deficiency, philosophies as K was above adequate in all sites. levels of Mg, except TH; whilst all the sites had which could be the reason for the observed The low K:Mg ratio in those sites can result in K either adequate or high levels of exchangeable K. nutritional imbalances. Hence, our forthcoming adsorption to the cation exchange sites, which Fortunately, at this part of the data the research agendas should focus on relating the could reduce the K activity. Some 29.0% of the sufficiency level approach matched directly with Mg:K ratio or vice versa with specific crop soils had the ratio wider than 1:1 again suspected the BCSR concept. In general, most researchers response including the investigations at the to be triggering the K-induced, Mg deficiency in are in agreement that, the Mg:K ratio for the pedons level. some soils. Such areas include NS, BT, DL, WH surface soils should be maintained at minimum and TH sites, the sites with strongly acidic soils in 2:1 to achieve balanced composition and, hence WS zone. In these more acidic soils, the K:Mg high yields of crops (McLean and Carbonell, 1972; Potassium to magnesium ratio ratios were close to or over 2:1, which could lead Lombin and Fayemi, 1976; Farina et al., 1992; to reduced uptake of Mg in some plants. Manson, 1995; Zalewska, 2008). Other workers In reverse scenario, the K:Mg ratio is also It is widely recognized that the contents of Mg in reported that, when the Mg:K ratio decreases assumed to have an impact in crops productivity. plants are about less than half of that of K. Third below 2, deterioration in fodder quality due to The K:Mg ratio of the studied soils varied from in significance is Mg, which is present in plants excessive accumulation of K and decreased Mg 0.26:1 to 2.0:1 (Table 2). In the present study, in about less than half of the Ca, but in soils it is concentration was observed (Zalewska et al., the bulk of soils, K:Mg was below the suggested frequently found in deficit for plant nutrition. From 2017). Hence, for balancing the mineral adequate or agreeable ratio for most arable and the results, therefore, K:Mg ratio seemingly found composition, supplemental Mg needs to be vegetable crops (Loide, 2004; Dobermann et al., to be another nutrient imbalance. This can be applied in the deficient areas; whereas K was 1996). Hence, taking 0.7:1 as threshold value, corrected by applying Mg containing fertilizer, sufficient in all areas in the present study. 58.0% of the soils had K:Mg ratio below this though it seems unlikely to balance the ratio, as No clear trend of change with depth was criterion. Taking 1:1 as a threshold, however, the contents of K was adequate or above in all observed, except that an equivocal increase or 63.0% of the soils were below this optimum. And, soils. Generally, the optimum percent saturation decrease with depth was recorded. Though not this might trigger Mg induced K deficiency. of exchange sites with a given cation is not

Menna 637

Table 4. Macro- and micro nutrient elements and related properties of soils before planting.

Soil Nodules Treat. applied Av.P (SO4-S) Micronutrients (mg/kg) Soil Ref. code Zo-Ne PA/FA Alt. (m) Av.P (By) type (CaCO3) (NPS, kg/ha) (mg/kg) (mg/kg) Cu Mn Fe Zn B Mo texture Season(s)-I 1-a Ar AA 2297.02 CV no Na Bray-I 5.12 6.94 2.38 41.67 4.80 0.91 0.31 0.05 SCL 2-a Ar Do1 2418.32 RNi no Na Bray-I 1.84 10.44 1.38 59.67 6.40 1.01 0.44 0.04 C 3-a Ar GS1 2151.10 CV no Na Bray-I 3.73 7.77 1.65 43.33 3.50 0.63 0.43 0.03 SC 4-a Ar CM 1768.98 Ni no Na Bray-I 1.11 22.13 0.75 38.33 3.40 0.82 1.22 0.06 C 5-a Ar BE 2359.95 CV no Na Bray-I 1.95 21.50 2.38 43.33 5.00 0.76 0.99 0.06 C 6-a Ar BL 2186.37 Ni no Na Bray-I 3.29 4.32 1.47 36.67 3.10 0.52 0.38 0.04 SC 7-a ES CD 2426.53 PV yes Na Olsen 7.67 15.37 1.29 5.00 1.60 0.34 0.24 0.59 C 8-a ES Ke1 2224.37 PV yes Na Olsen 7.55 5.78 1.47 6.70 1.80 0.33 0.23 1.08 C 9-a ES Ud 1873.86 PV yes Na Olsen 9.53 12.37 2.38 5.67 2.00 0.32 0.42 0.11 C 10-a ES Bk1 1874.16 PV yes na Olsen 10.82 1.30 2.11 5.00 1.90 0.26 0.35 0.04 SC 11-a ES In 2211.30 CV yes na Olsen 10.99 6.62 1.47 10.00 1.70 0.26 0.24 0.10 C 12-a ES Ki 2204.00 PV yes na Olsen 8.17 8.27 1.56 6.70 1.90 0.19 0.41 1.12 C 13-a OL NK 2123.74 CV no na Bray-I 0.22 11.89 1.93 46.67 5.10 0.58 0.48 0.05 C 14-a OL NS1 2229.54 RNI no na Bray-I 0.39 5.64 2.29 50.00 7.10 0.91 0.41 0.07 C 15-a OL BT1 2252.64 RNi no na Bray-I 1.89 3.82 1.75 60.00 8.20 1.25 0.25 0.06 CL 16-a OL DL 2173.6 RNi no na Bray-I 0.28 10.83 3.11 63.33 7.60 0.88 0.44 0.05 CL 17-a OL WH 2335.63 RNi no na Bray-I 1.34 23.02 3.47 50.00 9.10 1.12 1.57 0.06 C 18-a OL TH 2349.62 RNi no na Bray-I 1.45 24.18 4.11 53.33 5.10 1.17 0.43 0.07 C

Season(s)-II 19-a Ar WG/Do2 2418.32 PV no na Bray-I 2.01 31.98 2.56 61.67 4.10 0.87 1.60 0.06 C 19-b Ar WG/Do2 2418.32 PV no na Bray-I 1.51 24.98 2.32 61.60 4.00 0.87 1.99 0.07 C 19-c Ar WG/Do2 2418.32 PV no na Bray-I 1.15 23.13 2.45 61.52 4.12 0.80 2.11 0.06 C 20-a Ar GS2 2151.10 Ni no na Bray-I 3.01 12.11 2.47 41.67 4.60 0.93 0.38 0.05 CL 20-b Ar GS2 2151.10 Ni no na Bray-I 2.04 7.10 2.37 41.55 4.60 0.91 0.60 0.49 CL 20-c Ar GS2 2151.10 Ni no na Bray-I 1.51 6.01 2.40 41.39 4.60 0.92 1.11 0.50 CL 21-a ES Ke2 2224.37 PV yes na Olsen 9.02 6.77 1.47 6.70 2.10 0.36 0.34 1.06 C 21-b ES Ke2 2224.37 PV yes na Olsen 7.07 4.14 1.42 6.13 2.12 0.33 0.66 1.00 C 21-c ES Ke2 2224.37 PV yes na Olsen 4.06 3.10 1.41 6.44 2.22 0.31 1.21 1.11 C 22-a ES Bk2 1874.16 PV yes na Olsen 12.01 4.03 3.20 5.50 2.20 0.49 0.21 0.05 SC 22-b ES Bk2 1874.16 PV yes na Olsen 8.06 2.03 3.11 5.31 2.23 0.42 0.33 0.07 SC 22-c ES Bk2 1874.16 PV yes na Olsen 5.07 2.01 3.26 5.42 2.24 0.45 0.76 0.08 SC 23-a OL NS2 2229.54 RNi no na Bray-I 0.89 4.58 2.38 55.00 6.90 0.98 0.44 0.05 C 23-b OL NS2 2229.54 RNi no na Bray-I 0.51 2.13 2.33 55.00 6.87 0.89 0.63 0.05 C

638 Afr. J. Agric. Res.

Table 4. Contd.

23-c OL NS2 2229.54 RNi no na Bray-I 0.53 1.53 2.29 55.00 6.99 0.99 0.71 0.06 C 24-a OL BT2 2252.64 PV no na Bray-I 0.50 35.83 3.11 65.00 8.20 1.21 0.41 0.04 C 24-b OL BT2 2252.64 PV no na Bray-I 0.30 25.13 3.10 65.10 8.00 1.20 0.52 0.06 C 24-c OL BT2 2252.64 PV no na Bray-I 0.20 20.12 3.19 65.01 8.12 1.23 0.74 0.05 C

PV/A = Farmer village or association (1 = Abosara Alko (AA); 2 = Dosha (Do1); 3 = Gora Silingo (GS1 or 2); 4 = Chefe Misoma (CM); 5 = Boneya Edo (BE); 6 = Boro Lencha (BL); 7 = Chefe Donsa (CD); 8 = Keteba (Ke1); 9 = Ude (Ud); 10 = Bekejo (Bk1); 11 = Insilale (In); 12 = Kilinto (Ki); 13 = Nano Kersa (NK); 14 = Nano Suba (NS1); 15 = Berfeta Tokofa (BT1); 16 = Dawa Lafta (DL); 17 = Wajitu Harbu (WH); 18 = Tulu Harbu (TH) (1st season). 19 = Wonji Gora (WG/Do2); 20 = GS2; 21 = Ke2; 22 = Bk2; 23 = NS2; and 24 = BT2 (2nd season). The numbers (1) and (2) indicate the information which was generated in 1st and 2nd seasons respectively; soil variables (EC = electrical conductivity; CEC = cation exchange capacity; PS/SP = saturation percent; OC = organic carbon; TN = total nitrogen; TEB = total exchangeable bases); Soil depth (a = 0-20 cm; b = 20–40 cm; and c = 40–60 cm). na = not applicable. Soil types (CV = Chromic Vertisol, RNi = Red Nitisol, PV = Pellic Vertisol); and Soil Texture [(SCL = Sandy clay , C = Clay, SC = Sandy Clay, and CL = Clay loam)]; and Av.P for soils with pH >7.0 (analyzed by Olsen); and for soil with pH < 7.0 (Bray-1 method). Study areas [(Ar = Arsi, ES = East-Shewa = E/Shewa, WS/OL = West-Shewa or OL = Oromia Liyu = O/Liyu)]; Districts [(Ti =Tiyo, Hi = Hitosa, Ad = Ada'a, and We = Welmera)].

Table 5. Pearson correlation coefficients (r), some soil variables, base cation ratios, and wheat yield (native soil condition) (N =24).

Correlation pH EC CN TN AvP SO4S Ca:Mg Mg:K K:Mg pK:TEB Ca:TEB ExCa ExMg ExK ExNa TEB TAGB GY 0.3036 0.1126 0.5789 0.7427 0.6952 0.2896 0.0188 0.0559 0.0198 0.0058 0.0019 0.2189 0.3022 0.6415 0.1599 0.2755 0.0359 0.4137

1.00000 0.88113 0.58957 -0.77983 0.74751 -0.43331 0.38636 0.68244 -0.65916 -0.71477 0.71338 0.93769 0.95376 0.61331 0.37089 0.94780 -0.36839 -0.43472 pH - <0.0001 0.0024 <0.0001 <0.0001 0.0344 0.0622 0.0002 0.0005 <0.0001 <0.0001 <0.0001 <0.0001 0.0014 0.0744 <0.0001 0.0765 0.0338

0.88113 1.00000 0.64443 -0.64506 0.58389 -0.20753 0.27958 0.61733 -0.67625 -0.68098 0.63214 0.86820 0.92653 0.63916 0.35122 0.89098 -0.13349 -0.19922 EC <0.0001 - 0.0007 0.0007 0.0027 0.3305 0.1858 0.0013 0.0003 0.0002 0.0009 <0.0001 <0.0001 0.0008 0.0924 <0.0001 0.5340 0.3507

0.58957 0.64443 1.00000 -0.58062 0.33601 -0.00154 -0.01062 0.17395 -0.22271 -0.21660 0.17790 0.54594 0.63489 0.62726 0.34725 0.58766 -0.31160 -0.21130 CN 0.0024 0.0007 - 0.0029 0.1084 0.9943 0.9607 0.4163 0.2955 0.3093 0.4056 0.0058 0.0009 0.0010 0.0964 0.0025 0.1383 0.3216

-0.77983 -0.64506 -0.58062 1.00000 -0.61739 0.46852 -0.24713 -0.39016 0.31413 0.35756 -0.44231 -0.73214 -0.70559 -0.55966 -0.19639 -0.73808 0.55257 0.54897 TN <.0001 0.0007 0.0029 - 0.0013 0.0209 0.2443 0.0595 0.1349 0.0863 0.0304 <0.0001 0.0001 0.0045 0.3577 <0.0001 0.0051 0.0055

0.74751 0.58389 0.33601 -0.61739 1.00000 -0.45693 0.54691 0.58346 -0.59977 -0.67261 0.73270 0.82451 0.73820 0.39066 0.35200 0.80389 -0.37713 -0.49040 Av.P <0.0001 0.0027 0.1084 0.0013 - 0.0248 0.0057 0.0028 0.0019 0.0003 <0.0001 <0.0001 <0.0001 0.0591 0.0916 <0.0001 0.0693 0.0150

-0.43331 -0.20753 -0.00154 0.46852 -0.45693 1.00000 -0.50363 -0.26636 0.25603 0.40075 -0.54564 -0.34564 -0.25612 -0.02671 0.15901 -0.31481 0.34643 0.48363 SO4S 0.0344 0.3305 0.9943 0.0209 0.0248 - 0.0121 0.2084 0.2272 0.0523 0.0058 0.0981 0.2270 0.9014 0.4580 0.1340 0.0972 0.0166

0.38636 0.27958 -0.01062 -0.24713 0.54691 -0.50363 1.00000 0.32183 -0.28247 -0.51229 0.79082 0.53530 0.30125 0.01196 -0.00725 0.46913 0.07735 -0.22973 CaMg 0.0622 0.1858 0.9607 0.2443 0.0057 0.0121 - 0.1251 0.1811 0.0105 <0.0001 0.0070 0.1526 0.9558 0.9732 0.0207 0.7194 0.2802

0.68244 0.61733 0.17395 -0.39016 0.58346 -0.26636 0.32183 1.00000 -0.88774 -0.89326 0.76193 0.67389 0.66122 -0.05958 0.36690 0.64015 -0.13411 -0.19276 MgK 0.0002 0.0013 0.4163 0.0595 0.0028 0.2084 0.1251 - <0.0001 <0.0001 <0.0001 0.0003 0.0004 0.7821 0.0778 0.0008 0.5321 0.3668

Menna 639

Table 5. Contd.

-0.65916 -0.67625 -0.22271 0.31413 -0.59977 0.25603 -0.28247 -0.88774 1.00000 0.95975 -0.78761 -0.66598 -0.70538 -0.07618 -0.35933 -0.65233 0.03108 0.01635 KMg 0.0005 0.0003 0.2955 0.1349 0.0019 0.2272 0.1811 <.0001 - <0.0001 <0.0001 0.0004 0.0001 0.7235 0.0846 0.0006 0.8854 0.9396

-0.71477 -0.68098 -0.21660 0.35756 -0.67261 0.40075 -0.51229 -0.89326 0.95975 1.00000 -0.91827 -0.73132 -0.71155 -0.06211 -0.29982 -0.70235 0.06984 0.13951 pKTEB <0.0001 0.0002 0.3093 0.0863 0.0003 0.0523 0.0105 <0.0001 <0.0001 - <0.0001 <0.0001 <0.0001 0.7731 0.1546 0.0001 0.7457 0.5156

0.71338 0.63214 0.17790 -0.44231 0.73270 -0.54564 0.79082 0.76193 -0.78761 -0.91827 1.00000 0.77828 0.66642 0.10154 0.15224 0.73198 -0.06441 -0.25448 CaTEB <0.0001 0.0009 0.4056 0.0304 <0.0001 0.0058 <0.0001 <0.0001 <0.0001 <0.0001 - <0.0001 0.0004 0.6368 0.4776 <0.0001 0.7649 0.2301

0.93769 0.86820 0.54594 -0.73214 0.82451 -0.34564 0.53530 0.67389 -0.66598 -0.73132 0.77828 1.00000 0.95426 0.60070 0.38378 0.99500 -0.27347 -0.40798 ExCa <0.0001 <0.0001 0.0058 <0.0001 <0.0001 0.0981 0.0070 0.0003 0.0004 <0.0001 <0.0001 - <0.0001 0.0019 0.0641 <0.0001 0.1960 0.0478

0.95376 0.92653 0.63489 -0.70559 0.73820 -0.25612 0.30125 0.66122 -0.70538 -0.71155 0.66642 0.95426 1.00000 0.69181 0.39905 0.97516 -0.29116 -0.33884 ExMg <.0001 <.0001 0.0009 0.0001 <0.0001 0.2270 0.1526 0.0004 0.0001 <0.0001 0.0004 <0.0001 - 0.0002 0.0534 <.0001 0.1675 0.1053

0.61331 0.63916 0.62726 -0.55966 0.39066 -0.02671 0.01196 -0.05958 -0.07618 -0.06211 0.10154 0.60070 0.69181 1.00000 0.18150 0.66688 -0.23786 -0.22699 ExK 0.0014 0.0008 0.0010 0.0045 0.0591 0.9014 0.9558 0.7821 0.7235 0.7731 0.6368 0.0019 0.0002 - 0.3960 0.0004 0.2630 0.2861

0.37089 0.35122 0.34725 -0.19639 0.35200 0.15901 -0.00725 0.36690 -0.35933 -0.29982 0.15224 0.38378 0.39905 0.18150 1.00000 0.39045 -0.18233 -0.01807 ExNa 0.0744 0.0924 0.0964 0.3577 0.0916 0.4580 0.9732 0.0778 0.0846 0.1546 0.4776 0.0641 0.0534 0.3960 - 0.0592 0.3938 0.9332

0.94780 0.89098 0.58766 -0.73808 0.80389 -0.31481 0.46913 0.64015 -0.65233 -0.70235 0.73198 0.99500 0.97516 0.66688 0.39045 1.00000 -0.28383 -0.39434 TEB <0.0001 <0.0001 0.0025 <0.0001 <0.0001 0.1340 0.0207 0.0008 0.0006 0.0001 <0.0001 <0.0001 <0.0001 0.0004 0.0592 - 0.1789 0.0565

-0.36839 -0.13349 -0.31160 0.55257 -0.37713 0.34643 0.07735 -0.13411 0.03108 0.06984 -0.06441 -0.27347 -0.29116 -0.23786 -0.18233 -0.28383 1.00000 0.84781 TAGB 0.0765 0.5340 0.1383 0.0051 0.0693 0.0972 0.7194 0.5321 0.8854 0.7457 0.7649 0.1960 0.1675 0.2630 0.3938 0.1789 - <0.0001

-0.43472 -0.19922 -0.21130 0.54897 -0.49040 0.48363 -0.22973 -0.19276 0.01635 0.13951 -0.25448 -0.40798 -0.33884 -0.22699 -0.01807 -0.39434 0.84781 1.00000 GY 0.0338 0.3507 0.3216 0.0055 0.0150 0.0166 0.2802 0.3668 0.9396 0.5156 0.2301 0.0478 0.1053 0.2861 0.9332 0.0565 <0.0001 -

Correlation coefficient |r| = 0.00-0.10: negligible correlation; 0.10-0.39: weak correlation; 0.40-0.69: moderate correlation; 0.70-0.89: strong correlation; and 0.90-1.00: very strong correlation.

constant, but assumed to depend on the CEC, and productivity. In this regard, the K:TEB ratio is increases or decreases with depth in some sites. mineralogy and the soil texture. It is also important assumed to be another factor limiting K or related In direct conformity, as per the suggested to consider the plant factors and the presence or elements availability to plants. According to thresholds, all the soils had adequate or excess absence of other nutrients, etc., in deciding the Landon (1991), percent (K:TEB) ratios above levels of exchangeable K. In this part of data, adequacy of the K:Mg ratios. 2.0% are favorable for most tropical crops. In the there was a perfect match between the BCSR and present study, percent K:TEB ratios for the SLAN approaches. studied soils ranged from 4.34 to 30.86% (Table Percentage potassium to total exchangeable 2). From this, all the ratios were above 2.0%, bases ratio which are considered favorable for most tropical Calcium to total exchangeable bases ratio crops. The soil’s percent saturation levels of all major In addition, no clear trend of change with depth Amézketa (1999) observed that the basic cations cations levels are important indicator of soil fertility in the ratio was recorded, except that an equivocal saturation ratios influence and are influenced by

640 Afr. J. Agric. Res.

soil structure, in particular surface crusting, compaction solely depending on the cation ratios. Although soil-tests and . The high exchangeable Ca provide information about soil’s ability to supply plant content, 65.0%, of a balanced soil is suggested to be available nutrients, it is an indirect measurement. Hence, beneficial in maintaining and improving soil structure and our follow-up research should focus on correlating the aggregate stability. A lower Ca saturation level relative to data from both approaches with crop yields under BCSR and in relation to total exchangeable base (TEB) externally applied fertilizer conditions. The other major can lead to deterioration in soil structure, because areas of research could also be establishing critical aggregates more saturated with Ca are less susceptible thresholds for the major cations and pH of soils using to dispersion (Rengasamy, 1983; Zhang and Norton, more reliable research conditions. As there were no clear 2002). trends of change of the ratios with depth seen, it is From this, the Ca:TEB ratio is another factor widely important to make further investigations at different accepted to be affecting the availability of the major base pedons level. cations. In the present study, the Ca:TEB ratio of soils ranged from 0.40 to 0.78 (Table 2). According to Landon (1991), Ca:TEB ratios of above 0.5 may affect the uptake CONFLICT OF INTERESTS of other bases, particularly Mg and/or K as Ca induced deficiency of Mg and/or K may become visible. Thus, Ca The authors have not declared any conflict of interests. may influence the uptake and induce deficiency of K in those sites which are having the ratios greater than 0.5. Based on this, 79.0% of the studied soils had, Ca:TEB REFERENCES ratio fairly above this threshold, and are considered unfavorable. Abbott TS (1989). Biological and Chemical Research Institute soil testing methods and interpretation. 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