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Biofertilizer and NPSB fertilizer application effects on nodulation and productivity of common bean (Phaseolus vulgaris L.) at Sodo Zuria, Southern Ethiopia

  • Melkamu Dela , Dereje Shanka EMAIL logo and Dawit Dalga
Published/Copyright: January 24, 2023
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Open Life Sciences
From the journal Open Life Sciences Volume 18 Issue 1

Abstract

Common bean is among the vital legumes cultivated for nutrition, foreign currency earnings, and income generation. Common bean production is constrained mainly by nutrient deficiencies. A field experiment was conducted at Sodo Zuria Woreda to assess the effects of blended N–P–S–B fertilizer rates and Rhizobium strain on yield and yield traits of common bean and income of farmers. Treatments were five different rates of blended NPSB fertilizer (0, 50, 100, 150, and 200 kg ha−1) and two types of Rhizobium strains (HB-A15 and HB-429 (Rhizobia etli)) and control (without inoculation). Randomized complete block design in factorial arrangement with three replications were used. Results showed that interaction of blended NPSB rate and Rhizobium strain type had significant effect on the number of effective nodule, grain yield, and above ground dry biomass. Application of 150 kg NPSB ha−1 along with inoculation of Rhizobium etli resulted in the highest grain yield (3017.7 tons ha−1). Similarly, economic analysis indicated that the highest net return of 38298.545 ETB ha−1 was obtained from combined application of 150 kg NPSB ha−1 along with Rhizobium etli. Thus, it could be concluded that using Rhizobium etli strain with 150 kg NPSB ha−1 was found to be appropriate for common bean production in the area.

Keywords: blended fertilizer; inoculation; Rhizobia etli

1 Introduction

Common bean (Phaseolus vulgaris L.) is the most important calorie and protein source for humans [1]. In 2012, 23.9 million tons of dry bean, 20.7 million tons of green bean, and 1.9 million tons of string or common bean were projected to have been produced globally [2]. Common bean is one of Ethiopia’s most important grain legumes, with production centered on small-holder farms where nitrogen (N) fertilizer use is limited and average yields are low, typically less than 1 ton ha−1 [3]. It is one of the fastest-growing legume crops in Ethiopia, providing an important portion of the daily nutrition as well as foreign earnings for most Ethiopians [4]. It is one of the fast expanding legume crops that provide an essential part of the daily diet and foreign exchange earnings for most Ethiopians [4].

However, the present national average yield of common bean (1.48 tons) is significantly less than the yield that most improved varieties can achieve under good management conditions (2.5–3.0 tons ha−1). Poor agronomic techniques, such as insufficient soil fertility management, lack of superior varieties for the different agro-ecological zones, and untimely and inappropriate field operations, could be the major contributing factors for low yield of the crop in the country [5]. In addition to N and P deficiency, a soil fertility mapping effort in Ethiopia has identified K, S, B, and Cu deficiency in key Ethiopian soils [6]. Furthermore, critical soil nutrients such as N, P, K, S, B, and Cu were found to be inadequate in the research areas’ soils. Some of the nutritional deficits were site specific [7]. As a result, the use of a tailored and balanced fertilizer application can help to address the problem.

Furthermore, leguminous crops, such as common bean, require certain Rhizobium strains for optimal nodule development and nitrogen fixation [8]. Nutritional imbalance and poor nodulation are two of the most significant issues in the production of mung bean [9]. As a result, legume crops should be infected with appropriate bacteria to maximize output and enhance soil quality [10].

There have also been notable research findings in Ethiopia and elsewhere in the world that indicate a significant positive effect of single application of blended fertilizers or application along with inoculation with appropriate Rhizobium species on pulse crop growth, nodulation, yield, and yield attributing traits, including common bean [9,11,12]. For instance, Merkebu [9] found a significant (P < 0.05) interaction effect of blended NPSZn fertilizer types with Rhizobium strains on mung bean specific leaf area, leaf area ratio, relative growth rate, above ground biomass, root dry weight, plant height, branch number, tap root length, nodule number, nodule diameter, pod number per plant, and grain yield. Lake and Jemaludin [13] also reported that nodule number and nodule dry mass of common bean were significantly affected by various levels of NPSZnB applications. However, there is hardly any evidence in literature on the effect of blended NPSB and Rhizobia strains on common bean growth and production in Sodo Zuria Woreda. Hence, this study was initiated with the following specific objectives:

  • To evaluate the effect of Rhizobia inoculation and blended NPSB on yield and yield components of common bean.

  • To assess economically appropriate rates of blended NPSB fertilizer and Rhizobium type for production of common bean in Sodo Zuria Woreda

2 Materials and methods

The experiment took place in Sodo Zuria Woreda Offa-sere kebele, Wolaita Zone, Southern Ethiopia, during the 2019 rainy season. The experimental site is 4 km south of Sodo town and at an elevation of 1,812 m above sea level, at 6° 47′ 31.55″ N latitude and 37° 45′ 08.76″ E longitude. The site receives 1,484 mm of yearly rainfall and average annual minimum and maximum temperatures of 16.8 and 21.2°C, respectively. Rainfall for the main growing season begins after June and ends in the last week of September at the experimental location. The experimental field had previously been planted with taro and had never received any fertilizer.

2.1 Soil sampling and analysis

Before planting, composite (0–30 cm) soil depth samples were taken in a zig-zag fashion from several locations within the experimental field. Soil pH was measured potentiometrically in 1:2:5 soil–water suspensions with standard glass electrode pH meter [14]. The Walkley and Black [15] method was used to determine organic matter content of the soil. Total N in the soil was determined by the Kjeldahl method [16]. Available soil Phosphorus was determined using the Olsen extraction method as described by Olsen et al. [17]. Available sulfur was analyzed by turbidimetric method [18]. The Bouyoucos hydrometer method [19] was used to determine the soil texture. Electro-conductivity (EC) was determined by standard glass electrode using EC meter. Soil cation exchange capacity (CEC) was determined by ammonium acetate method [20].

2.2 Description of experimental materials

Nasir, a popular common bean variety released in 2003, was used in this study. Nasir is an indeterminate semi-climbing plant that takes 95–110 days to reach physiological maturity and has dark-red seed coat pigmentation. It is generally utilized for domestic consumption and has a seeding rate of 90–100 kg ha−1 [21]. As a source of N, P, S, and B nutrients, a blended NPSB fertilizer containing 18.7, 37.4, 6.9, and 0.25% was received from the Sodo Zuria Agricultural Office. Rhizobia strains HB-A15 and HB-429 were utilized for this research. HB-429 was first isolated by Hawassa University from common bean root nodule around Adilo in Hayia Zone, which is located in Southern Ethiopia, while HB-A15 was isolated by Holeta Agricultural Center. Sequencing was done for HB-429 and it is found to be Rhizobium etli, while HB-A15 was not sequenced. Both species tested and proved to fix atmospheric N by N2 Africa in collaboration with Hawassa University. The Menagesha biotech industry, which is located in Addis Ababa, is commercializing the strains.

2.3 Treatments and experimental design

The experiment included five levels of blended NPSB fertilizer rates (0, 50, 100, 150, and 200 kg NPSB ha−1), two Rhizobia strains (HB-A15 and HB-429 (Rhizobium etli)), and no inoculation. There were a total of 15 treatments replicated 3 times and the total treatment will be (5 × 3 × 3 = 45). The experiment was set up in a factorial layout with a randomized complete block design and was replicated three times. Each plot was 2.40 m × 2.30 m (5.52 m2) and was divided into six rows of three meters each, with the center four rows serving as a net plot. Plots and adjacent replications were separated by 0.5 and 1 m, respectively. The spacing between plants was 10 cm and spacing between rows was 40 cm. The inoculation of Rhizobia strains was done before sowing and blended NPSB fertilizer was applied according to the treatments at the time of sowing.

2.4 Agronomic practices

The experimental field was cleansed of undesired items and plant remnants, and was leveled. The experimental field was then plowed three times by oxen before being planted in early May. A sachet of bio-fertilizer containing 125 g was administered according to the advice, which was 10 g kg−1 seeds for inoculation. Before inoculation, seeds were soaked in water for 30 min. Then, excess water was removed from the seeds by placing in a sack. There after sugar was applied as adhesive material to stick the inoculums in to the seeds. Finally, the inoculums were applied to the seeds and dressed until the seeds showed a black color in a shade to avoid direct sun light so as to maintain the viability of the inoculums.

Flat sowing of two seeds per hill to a depth of 5 cm was done, and following establishment, the plots were thinned to one plant per hill. At the time of sowing, a blended NPSB fertilizer was applied in a band. Weeding was done by hand following the fourth and fifth weeks of sowing. To prevent Rhizobia cell death due to desiccation, the seeds were promptly covered with moist soil after sowing. From field preparation to harvesting, all relevant agronomic managements were carried out equally. On August 20, 2019, harvesting was completed when the pods turned a brownish red color.

2.5 Data collected

Data on total number of nodules and effective nodules were collected from five randomly selected plants grown in rows left for destructive sampling during flowering stage. The total and effective nodules were studied after washing the root samples carefully in plastic containers to remove the soils attached to the roots. The separated root nodules were counted, the total was recorded, and then the nodules were dissected using forceps and knives to determine the nodule effectiveness based on the nodules internal color. Hence, the nodules with pink or dark red internal color were recorded as effective and those nodules with white color were recorded as non-effective. Data on yield and yield component parameters were taken in each plot from five randomly selected plants at physiological maturity and at harvest time, respectively. Hundred seeds weight was determined from 100 randomly taken seeds from plants grown in the net plot area at harvest and the seeds weight was determined using a sensitive balance. Number of pods per plant, and number of seeds per pod were collected from five randomly selected plants in the net plot area at harvest. Aboveground dry biomass yield was measured from five plants left for destructive sampling at physiological maturity and converted into hectare basis. Grain yield was measured from the net plot area at harvest and adjusted to 10% moisture content. Harvest index (HI) was calculated as the ratio of grain yield to total aboveground biomass multiplied by hundred.

2.6 Statistical data analysis

The data were subjected to analysis of variance (ANOVA) using SAS version 9.1’s Generalized Linear Model, and interpretations were derived using procedures described on Gomez and Gomez [22]. The least significant difference (LSD) test was used to separate the means at a 5% level of significance.

2.7 Economic analysis

CIMMYT’s (1988) partial budget procedure was used to conduct an economic study. The variable costs included the blended NPSB fertilizer cost (14 ETB kg−1) and the cost of each Rhizobia strain type HB-A15 and Rhizobia etli (200 and 240 ETB ha−1, respectively), at the time of planting and their application, while the price of the current common bean was considered as gross benefit, according to the partial budget procedure described by CIMMYT [23]. The labor costs associated with inoculating common bean seeds with Rhizobia strains and applying NPSB fertilizer were documented and employed in this research as well. The average open market price (ETB kg−1) was used to appraise the common bean grain price.

3 Results and discussion

3.1 Physico-chemical properties of soil of experimental site

The soil physico-chemical parameters of the study site are indicated in Table 1. According to the soil analysis data, the soil texture class of the experimental location is clay loam (Table 1). The pH of the experimental site’s soil is in the moderately acidic range [24]. Similarly, according to Landon [24], the experimental site’s CEC is medium.

Table 1

Physico-chemical properties of soil

Soil physico-chemical property Values
Texture Clay loam
Sand (%) 59
Silt (%) 19
Clay (%) 22
Textural class Clay loam
pH 5.8
Total N (%) 0.172
Available P (ppm) 1.54
CEC (cmol(+)/kg soil) 22.4
O.C (%) 2
Available S (ppm) 18.2
Available B (ppm) 0.42

3.2 Total and effective number of nodules

3.2.1 Total number of nodules

Application of NPSB fertilizer and inoculation of Rhizobia strain had significant (P > 0.05) effect on the total number of nodules (Table 2). The Rhizobia strain type Rhizobium etli produced the highest number of total nodules (86.6), whereas the treatment without Rhizobia inoculation produced the lowest number of total nodules (44) (Table 3). When compared to HB-A15 Rhizobia strain type and control treatment, inoculation with Rhizobium etli resulted in a higher number of nodules per plant, which could be due to the fact that Rhizobium etli had better nodulation inducing capacity than HB-A15 and naturally pre-existing soil Rhizobium species. The presence of Rhizobia strain type specificity could potentially explain the result. Many researchers agreed that inoculating common beans with the right Rhizobium strain increases the number of nodules per plant compared to uninoculated beans [25,26,27,28]. Recent finding by Genetu et al. [11] and Ketema and Tefera [28] indicated significant increase in the number of nodule per plant for faba bean in different parts of Ethiopia due to Rhizobia inoculation. In addition, several researchers showed that inoculating common bean with efficient Rhizobia strains resulted in much higher nodulation and N2 fixation rates than the native Rhizobia population [29].

Table 2

Mean squares of ANOVA for yield and yield components of common bean as affected by Rhizobium inoculation and NPSB rate

Source of variation Mean squares
Df BM GY HI NP NS HW NTN NEN
Block 2 38,260 130,853 319.26 3.096 0.17422 116.8 37.94 44.5
Bio-fertilizer 2 23,297ns 285,168** 1.99 157.818** 2.0009** 83.80** 722.04** 306.59*
NPSB rate 4 5,541,910** 2,647,396** 104.79** 27.879* 0.293ns 78.52** 7077.77** 3243.54**
BF xFR 8 314,495** 47,564* 1.812ns 3.48ns 0.1153ns 9.05ns 39.5ns 301.68*
Error 28 47,417 19,641 14.208 7.781 0.139 7.31 82.3 117.99
CV 4.01 5.67 8.68 12.14 8.83 9.43 13.41 20.49

Where, Df = Degree of freedom; ** = highly significant (P = 0.01); * = significant (P = 0.05); ns = non-significant; CV (%) = coefficient of variation; BM = above ground biomass; GY = grain yield; HI = harvest index; NP = number of pods; NS = number of seeds and HW = hundred seeds weight; NTN = number of total nodules; NEN = number of effective nodules.

Table 3

Mean number of total nodules, Number of total nodules per plant, Number of pods per plant, Number of seeds per plant, and Hundred seeds weight (g), HI of common bean as affected by main effect of blended NPSB fertilizer and Rhizobia strain type at Offa-sere kebele during 2019 main crop season

Rhizobia strain Number of total nodules per plant Number of pods per plant Number of seeds per pod HW (g) HI
HB-A15 72.40b 24.57a 4.29b 28.24b 46.97a
Rhizobium etli 86.61a 25.13a 4.55a 31.23a 46.22a
Withoutinoculation 43.95c 19.25b 3.83b 26.56c 42.36b
LSD (0.05) 6.7856 2.10 0.28 2.02 2.25
CV (%) 13.41 12.14 8.83 9.43 6.65
Blended NPSB rate (kg ha−1)
0 56.24d 20.38b — 24.22d 38.31c
50 62.01cd 22.11ab — 27.62c 41.71c
100 68.8bc 23.42a — 28.98bc 52.36a
150 79.54a 24.42a — 30.88ab 46.73b
200 71.69ab 24.59a — 31.68a 46.82b
LSD (0.05) 8.76 2.69 — 2.61 2.90
CV (%) 13.41 12.14 — 9.43 6.65

Mean values in the table followed by the same letter(s) are not significantly different from each other at 5% level of significance, LSD (0.05) = Least significant difference at 5% level of significance; and CV (%) = coefficient of variation.

In the case of blended NPSB fertilizer, the number of total nodules increased as the blended NPSB fertilizer was increased only up to 150 kg NPSB ha−1. This probably indicates that applying NPSB fertilizer beyond 150 kg ha−1 may cause elemental N from blended NPS fertilizer to have an antagonistic effect on the crop root zone. Further, the increase in total nodule number with the increase in NPSB level even up to the indicated level might be attributed to better supply of P and S nutrients, which are important for nodulation. This finding is consistent with Chala et al. [30], who reported significant effect of NPS fertilizer application on total number of nodule per plant. Dereje et al. [31] also reported the significant effect of P application on total nodule number of common bean at Areka. On the contrary, Chen et al. [32] and Starling et al. [33] reported that a high nitrogen rate (56.58 kg N ha−1) reduced nodule quantity and weight in soya bean.

3.2.2 Number of effective nodules

The number of effective nodules was significantly affected (P < 0.05) by the interaction of blended NPSB fertilizer and Rhizobia strain types (Table 2). The plot that received a combined application of 150 kg ha−1 of NPSB fertilizer with inoculation of Rhizobium etli had the largest number of effective nodules (75.13), whereas the control plot had the lowest (30) (Table 4). The probable reason for increase in the number of effective nodules could be due to the improved availability of nutrients such as P and S following application of NPSB, which are crucial for effective nodulation and the suitability of the Rhizobium strain for effective nodulation.

Table 4

Mean number of effective nodules of common bean as affected by interaction effect of blended NPSB fertilizer and Rhizobia strain at Offa-Sere kebele during 2019 main cropping season

Blended NPSB rate (kg ha−1)
Rhizobia strain 0 50 100 150 200
Effective nodules
HB-A15 48.07cde 50.60cd 53.07bcd 64.83abc 57.07abc
Rhizobium etli 59.33abc 62.67abc 70.73ab 75.13a 70.70ab
Wi 29.93ef 31.47ef 27.93f 57.73abc 35.93def
LSD (0.05) 18.17
CV (%) 20.49
Grain yield (kg ha −1 )
HB-A15 1,879e 2241.7d 2748.7bc 2923.7ab 2,922ab
Rhizobium etli 1747.7e 2291.7d 2887.3ab 3017.7 a 2,867ab
Wi 1496.3f 1759.3e 2,622c 2770.3bc 2,924ab
LSD (0.05) 245.3
CV (%) 5.67
Aboveground dry biomass yield (kg ha −1 )
HB-A15 4,607h 5,194ef 5183.7ef 6,326b 6096.7bc
Rhizobium etli 4566.7h 5060.3fg 5545.3de 6014.7bc 5,847cd
Wi 4,171i 4,776gh 5043.7fg 6,367b 6383.7b
LSD (0.05) 364.2
CV (%) 4.01

Mean values in the table followed by the same letter(s) are not significantly different from each other at 5% level of significance, LSD (0.05) = Least significant difference at 5%; and CV (%) = coefficient of variation; Wi = without inoculation.

This study is consistent with Genetu et al. [11], who observed highly significant (P < 0.001) greater nodulation by the interaction effect of the inoculant and blended fertilizer. This may be attributed to the positive effect of sulfur in nodulation as it plays a vital role in biosynthesis of nitrogenase, which is employed in nitrogen fixation, in common beans Becana et al. [34]. Chala et al. [30] also reported significant (P < 0.01) effect of Rhizobia inoculation and NPS on the number of effective nodules per plant. Tsai et al. [35] found that applying N at a rate of 22–33 kg ha−1 increased both the nodulation and seed output in French bean (P. vulgaris).

3.3 Yield and yield components

3.3.1 Number of pods per plant

The Rhizobia strain and the application of blended NPSB fertilizer had significant effect on the quantity of pods per plant (Table 2). The maximum number of pods per plant was observed after inoculation with Rhizobium etli, which is statistically equal to HB-A15, and the lowest number of pods per plant was observed after no inoculation (Table 3).

As a result, the increase in pods per plant could be attributed to improved vegetative growth [28] following effective nodulation with the new Rhizobia strains (Rhizobium etli and HB-A15). Inoculation with Rhizobium etli also increased the number of pods per plant, which could be attributable to the novel strain’s efficacy in nodulation and N-fixation over native Rhizobia in the experimental soils. This conclusion is supported by studies from Ethiopian and international scholars [36,37,38]. According to Yoseph and Shanko [36], inoculation with Rhizobium strain HB-429, for example, enhanced the number of pods per plant of common bean substantially over the control.

Improved number of pods per plant in legumes was also ascribed to appropriate supply of important plant nutrients such as N [36], P [39], and/or NPS [36,40]. For example, Deresa et al. [40] suggested that the increased number of pods per plant for common bean with increased NPS rates could be due to adequate N, P, and S availability, which could have facilitated the production of primary branches and plant height, resulting in the production of a higher number of total pods.

Confirming these finding different researchers found a considerable increase in the number of pods per plant of common bean in the study area or elsewhere in the country following application of NPS/NPSB blended fertilizer [41, 42 43]. The increase in number of pods per plant due to NPSB fertilizer application might be attributed to better supply of other nutrients such as S, P, and B from blended NPSB fertilizer, which leads to improved dry matter accumulation, growth, and yield component formation [36]. For example, Shumi [42] found that at a rate of 250 kg NPS ha−1, the largest number of pods per plant was recorded, whereas the unfertilized plot had the lowest number of total pods.

3.3.2 Hundred seed weight

The results also demonstrated that the Rhizobia strain and blended NPSB fertilizer application had a substantial impact on HW (Table 2). The plot that was inoculated with the HB-429 type of Rhizobia strain had the highest HW, while the plot without inoculation had the lowest HW (Table 3). Increased nodulation and N bio-availability for absorption and assimilation, resulting in improved vegetative growth and re-translocation of photo-assimilates for grain filling, could explain the increase in HW. This also suggests that the Rhizobia strain HB-429 is more efficient than the native Rhizobia strain, which has a paramount importance improving nodulation and growth. Improved growth and N-fixation can lead to higher grain filling by allowing assimilates to be translocated later in the growth cycle, resulting in a positive contribution to seed weight. Corroborating the current finding, different authors have found considerable increases in HW of common bean [44], chickpea [37], and faba bean [28] after inoculation with Rhizobium bacteria. Girma et al. [44] also found that Rhizobium inoculation of haricot bean influenced thousand seed weight strongly and significantly (P < 0.001) with the highest thousand seed weight (162.95 g) obtained at Rhizobium inoculation treatment.

Furthermore, due to the use of blended NPS fertilizer, the HSW varied greatly. As a result, the greatest NPS fertilizer rate yielded the highest HW, while the lowest yielded the smallest (Table 3). The increase in HWs might be due to the direct supply of N, P, S, and B from inorganic mixed NPSB, which are critical for plant growth and development, boosting photosynthetic efficiency and dry-matter accumulation, and resulting in greater grain filling. Different researchers observed a substantial influence of blended NPS [40] or NPKSB fertilizer [43] on HW of common bean, which is consistent with the current findings. For example, Abebe and Mekonnen [43] found that increasing the rate of blended NPKSB fertilizer application had a substantial impact on common bean HW.

3.3.3 Number of seeds per pod

The number of seeds per pod was considerably affected by Rhizobia inoculation (Table 2). The plot with Rhizobia etli produced the maximum number of seeds per pod, while the plot with no inoculation produced the lowest number of seeds per pod (Table 3). This can be explained by the fact that Rhizobia strain inoculation can improve symbiotic N fixation and N nutrition, which in turn enhance assimilate production, thereby promoting growth, which can be re-translocated for the formation of yield containers such as seeds, thus increasing the number of seeds per pod. Corroborating the results, different authors reported significant effect of Rhizobium inoculation on number of seeds per pod for different legumes common bean [36] and faba bean [28,45,46]. Yoseph and Shanko [36] showed a remarkable 115% increase in the number of seeds per pod of common bean inoculated with Rhizobium bacteria as compared to the control. Recent study by Ketema and Tefera [28] also reported highly significant (P < 0.001) effect of Rhizobium rate on the number of seeds per pod of faba bean in Southern Ethiopia. Furthermore, Samuel et al. [45] reported that Rhizobia inoculation resulted in considerable increases in the number of seeds per plant for faba bean.

3.3.4 Grain yield

The interaction effect of Rhizobia strain and blended NPSB fertilizer on grain yield was significant (P < 0.05) (Table 2). Inoculation of Rhizobium etli with application of 150 kg ha−1 blended NPSB produced the highest grain yield, whereas the control produced the lowest grain yield (Table 4). This means that both new Rhizobia strain inoculation and inorganic NPSB application can alleviate the soil fertility problem (Table 1), which is a direct cause of poor production in the study location. In other words, enhanced grain production with increased blended NPSB fertilizer rate and Rhizobia inoculation could be attributed to increased availability of nutrients like P, S, and B because of either blended NPSB fertilizer application or improved N-fixation by Rhizobia strain. Regardless of this, increasing the level of N along with the rate of NPSB might interfere with the atmospheric N-fixation. Higher availability of these nutrients is important for growth, development, and assimilates production [47], which leads to increased grain production via photo-assimilates being re-translocated from the vegetative to the yield components. The results of this study are supported by the findings of different authors [27,41,48].

For instance, Endrias [41] found the maximum grain yield (2,257 kg ha−1) from the interaction of Rhizobium inoculation with 100 kg ha−1 NPS fertilizer treatment, and the lowest grain yield (665 kg ha−1) from the plot that got no blended NPS fertilizer application. Abera and Abebe, [27] reported significantly higher mean seed yield for field as a result of interaction of 125 kg NP ha−1 and Rhizobium inoculation at Gedo, Oromia region, Ethiopia. Abera and Tadele [48] also found that combining Rhizobia strains with nitrogen had a substantial impact on grain yield of common bean in the Areka district, which is close to the study location.

3.3.5 Aboveground dry biomass

The aboveground dry biomass yield of common bean was significantly affected (P < 0.05) by the interaction effect of blended NPSB fertilizer and Rhizobia strain types (Table 2). The maximum aboveground dry biomass (6383.7 kg ha−1) was found in plots that received a blended NPSB rate of 200 kg ha−1 without inoculation, which is also statistically at par with plots that receive 150 kg NPSB ha−1 along with inoculation of HB-A15 Rhizobia strain, while the lowest (4,171 kg ha−1) was found in plots applied with nil rate of NPSB along with no inoculation (Table 4). The improved availability of N and other nutrients P, S, and B directly from the applied inorganic fertilizer might have significantly increased the vegetative growth of the crop, which in turn could be attributed to the increase in biomass yield of common bean. This also indicates that the native Rhizobia strain is more effective than the new Rhizobia strain in enhancing vegetative growth. Endrias [41], also reported highest (5,006 kg ha−1) aboveground dry biomass from Rhizobium inoculation along with NPS rate at 100 kg ha−1. Veeresh [49] also found total dry matter production per plant increased significantly from 12.0 to 16.03 g as a result of increasing the rate of N from 40 to 120 kg ha−1 on French bean (Phaseolus vulgaris). The findings of this study are also backed up by Yoseph and Shanko [36], who found a considerable favorable effect of N fertilizer and Rhizobium application on shoot dry weight.

3.3.6 HI

The results showed that the rate of blended NPSB fertilizer and the Rhizobia strains had a significant (P < 0.05) impact on the HI (Table 2). The plot with the highest fertilizer rate of 100 kg ha−1 had the highest HI, whereas the plot with the lowest fertilizer rate had the lowest HI (Table 3). According to this research, the favorable effect of NPSB fertilizer on nutrient and photo-assimilate re-translocation from the vegetative to grain parts of the crop may explain the improvement in HI with increase in the blended NPSB fertilizer rate. Birhan [50] also recorded a considerable rise in HI with the application of P on common bean, which is consistent with this finding. Further, Chala et al. [30] reported significant effects of NPS on HI of soybean. The increase in HI with fertilizer rates is also consistent with Dhanjal et al. [51], who found that raising N levels from zero to 60 and 120 kg N ha−1 improved HI values by 31.60, 31.99, and 33.86%, respectively. In contrast, Chala et al. [30] reported non-significant effect of blended fertilizer application on HI of faba bean.

Furthermore, when a crop was inoculated with a new Rhizobia strain, the HI increased. The reason for this could be because inoculation increased N bioavailability, absorption, and assimilation through biological N-fixation, which boosted crop growth and partitioning of dry matter to grain. Inoculation of Rhizobium etli and without inoculation had the highest (46.97%) and lowest (42.36%) percent of HI, respectively. Corroborating the findings, both Anteneh and Bulti [52] on common bean and Chala et al. [30] on Soybean observed significant effect of seed inoculation on HI of both crops.

3.4 Economic analysis

According to the economic analysis, the NPSB fertilizer rate of 100 kg ha−1 combined with inoculation of Rhizobia strain, Rhizobium etli gave economically optimum net return (37238.955 ETB ha−1) with the maximum marginal rate of return of 4579.77% followed by 38298.5 ETB with 3,702% marginal rate of return attained at 100 kg NPSB ha−1 along with inoculation of the same Rhizobium strain (Table 5). This finding suggests that applying 150 kg ha−1 of NPSB with the Rhizobium etli yields a good economic return in the research area and other places with similar agro-ecological parameters (Table 5). In agreement, Kiros and Atsede [53] reported that Rhizobium inoculation along with 125 kg NPSB ha−1 gave the highest net benefit with acceptable marginal rate of return.

Table 5

Partial budget analysis of the responses of common bean to Rhizobia inoculation and NPSB fertilizer application rates

Rhizobium inoculation NPSB kg ha−1 UGY kg ha−1 AGY (kg ha−1) GFB (ETB ha−1) TVC (ETB ha−1) NB (ETB ha−1) MRR (%)
HB-A15 0 1,879 1691.1 25366.5 200 25166.5
Rhizobium etli 0 1747.67 1572.903 23593.55 240 23353.545 D
Wi 0 14946.33 13451.697 201775.45 0 201775.455 D
HB-A15 50 2241.67 2017.503 30262.55 1,000 29262.545 D
Rhizobium etli 50 2291.67 2062.503 30937.55 1,040 29897.545 1587.5
Wi 50 1759.33 1583.397 23750.95 800 22950.955 2894.41
HB-A15 100 2748.67 2473.803 37107.05 1,700 35407.045 1384.01
Rhizobium etli 100 2887.33 2598.597 38978.95 1,740 37238.955 4579.77
Wi 100 2,622 2359.8 35,397 1,500 33,897 1392.46
HB-A15 150 2923.67 2631.303 39469.55 2,400 37069.545 352.51
Rhizobium etli 150 3017.67 2715.903 40738.55 2,440 38298.545 3072.5
Wi 150 2770.33 2493.297 37399.455 2,200 35199.455 1291.29
HB-A15 200 2,922 2629.8 39,447 3,100 36347 127.51
Rhizobium etli 200 2,867 2580.3 38704.5 3,140 35564.5 D
Wi 200 2,924 2631.6 39,474 2,900 36,574 420.63

Where, UGY = unadjusted grain yield; AGY = adjusted grain yield; GFB = gross field benefit; TVC = total variable costs; NB = net benefit; MRR = marginal rate of return; ETB/ha = Ethiopian Birr per hectare; D = dominated treatments.

4 Conclusion

The results of the present study showed that common bean production in the study site is constrained by nutrient deficiency. Hence, single application of either blended NPSB fertilizer or inoculation of Rhizobia strain or application of both together can correct soil fertility problems and increase yield and yield attributing traits of common bean. Accordingly, common bean grain yield was increased with increased rate of blended NPSB fertilizer and Rhizobia strain inoculation. Based on the results of this study, it could be tentatively concluded that inoculation of Rhizobium etli strain along with application of NPSB at the rate of 100 kg ha−1 was found to be the appropriate treatment combination from agronomic and economic point of view for common bean production in the area and other areas with similar agro-ecologies.

  1. Funding information: Authors state no funding involved.

  2. Conflict of interest: Authors state no conflict of interest.

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

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Received: 2021-12-03
Revised: 2022-10-01
Accepted: 2022-11-13
Published Online: 2023-01-24

© 2023 the author(s), published by De Gruyter

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

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  160. Small breast epithelial mucin as a useful prognostic marker for breast cancer patients
  161. Continuous non-adherent culture promotes transdifferentiation of human adipose-derived stem cells into retinal lineage
  162. Nrf3 alleviates oxidative stress and promotes the survival of colon cancer cells by activating AKT/BCL-2 signal pathway
  163. Favorable response to surufatinib in a patient with necrolytic migratory erythema: A case report
  164. Case report of atypical undernutrition of hypoproteinemia type
  165. Down-regulation of COL1A1 inhibits tumor-associated fibroblast activation and mediates matrix remodeling in the tumor microenvironment of breast cancer
  166. Sarcoma protein kinase inhibition alleviates liver fibrosis by promoting hepatic stellate cells ferroptosis
  167. Research progress of serum eosinophil in chronic obstructive pulmonary disease and asthma
  168. Clinicopathological characteristics of co-existing or mixed colorectal cancer and neuroendocrine tumor: Report of five cases
  169. Role of menopausal hormone therapy in the prevention of postmenopausal osteoporosis
  170. Precisional detection of lymph node metastasis using tFCM in colorectal cancer
  171. Advances in diagnosis and treatment of perimenopausal syndrome
  172. A study of forensic genetics: ITO index distribution and kinship judgment between two individuals
  173. Acute lupus pneumonitis resembling miliary tuberculosis: A case-based review
  174. Plasma levels of CD36 and glutathione as biomarkers for ruptured intracranial aneurysm
  175. Fractalkine modulates pulmonary angiogenesis and tube formation by modulating CX3CR1 and growth factors in PVECs
  176. Novel risk prediction models for deep vein thrombosis after thoracotomy and thoracoscopic lung cancer resections, involving coagulation and immune function
  177. Exploring the diagnostic markers of essential tremor: A study based on machine learning algorithms
  178. Evaluation of effects of small-incision approach treatment on proximal tibia fracture by deep learning algorithm-based magnetic resonance imaging
  179. An online diagnosis method for cancer lesions based on intelligent imaging analysis
  180. Medical imaging in rheumatoid arthritis: A review on deep learning approach
  181. Predictive analytics in smart healthcare for child mortality prediction using a machine learning approach
  182. Utility of neutrophil–lymphocyte ratio and platelet–lymphocyte ratio in predicting acute-on-chronic liver failure survival
  183. A biomedical decision support system for meta-analysis of bilateral upper-limb training in stroke patients with hemiplegia
  184. TNF-α and IL-8 levels are positively correlated with hypobaric hypoxic pulmonary hypertension and pulmonary vascular remodeling in rats
  185. Stochastic gradient descent optimisation for convolutional neural network for medical image segmentation
  186. Comparison of the prognostic value of four different critical illness scores in patients with sepsis-induced coagulopathy
  187. Application and teaching of computer molecular simulation embedded technology and artificial intelligence in drug research and development
  188. Hepatobiliary surgery based on intelligent image segmentation technology
  189. Value of brain injury-related indicators based on neural network in the diagnosis of neonatal hypoxic-ischemic encephalopathy
  190. Analysis of early diagnosis methods for asymmetric dementia in brain MR images based on genetic medical technology
  191. Early diagnosis for the onset of peri-implantitis based on artificial neural network
  192. Clinical significance of the detection of serum IgG4 and IgG4/IgG ratio in patients with thyroid-associated ophthalmopathy
  193. Forecast of pain degree of lumbar disc herniation based on back propagation neural network
  194. SPA-UNet: A liver tumor segmentation network based on fused multi-scale features
  195. Systematic evaluation of clinical efficacy of CYP1B1 gene polymorphism in EGFR mutant non-small cell lung cancer observed by medical image
  196. Rehabilitation effect of intelligent rehabilitation training system on hemiplegic limb spasms after stroke
  197. A novel approach for minimising anti-aliasing effects in EEG data acquisition
  198. ErbB4 promotes M2 activation of macrophages in idiopathic pulmonary fibrosis
  199. Clinical role of CYP1B1 gene polymorphism in prediction of postoperative chemotherapy efficacy in NSCLC based on individualized health model
  200. Lung nodule segmentation via semi-residual multi-resolution neural networks
  201. Evaluation of brain nerve function in ICU patients with Delirium by deep learning algorithm-based resting state MRI
  202. A data mining technique for detecting malignant mesothelioma cancer using multiple regression analysis
  203. Markov model combined with MR diffusion tensor imaging for predicting the onset of Alzheimer’s disease
  204. Effectiveness of the treatment of depression associated with cancer and neuroimaging changes in depression-related brain regions in patients treated with the mediator-deuterium acupuncture method
  205. Molecular mechanism of colorectal cancer and screening of molecular markers based on bioinformatics analysis
  206. Monitoring and evaluation of anesthesia depth status data based on neuroscience
  207. Exploring the conformational dynamics and thermodynamics of EGFR S768I and G719X + S768I mutations in non-small cell lung cancer: An in silico approaches
  208. Optimised feature selection-driven convolutional neural network using gray level co-occurrence matrix for detection of cervical cancer
  209. Incidence of different pressure patterns of spinal cerebellar ataxia and analysis of imaging and genetic diagnosis
  210. Pathogenic bacteria and treatment resistance in older cardiovascular disease patients with lung infection and risk prediction model
  211. Adoption value of support vector machine algorithm-based computed tomography imaging in the diagnosis of secondary pulmonary fungal infections in patients with malignant hematological disorders
  212. From slides to insights: Harnessing deep learning for prognostic survival prediction in human colorectal cancer histology
  213. Ecology and Environmental Science
  214. Monitoring of hourly carbon dioxide concentration under different land use types in arid ecosystem
  215. Comparing the differences of prokaryotic microbial community between pit walls and bottom from Chinese liquor revealed by 16S rRNA gene sequencing
  216. Effects of cadmium stress on fruits germination and growth of two herbage species
  217. Bamboo charcoal affects soil properties and bacterial community in tea plantations
  218. Optimization of biogas potential using kinetic models, response surface methodology, and instrumental evidence for biodegradation of tannery fleshings during anaerobic digestion
  219. Understory vegetation diversity patterns of Platycladus orientalis and Pinus elliottii communities in Central and Southern China
  220. Studies on macrofungi diversity and discovery of new species of Abortiporus from Baotianman World Biosphere Reserve
  221. Food Science
  222. Effect of berrycactus fruit (Myrtillocactus geometrizans) on glutamate, glutamine, and GABA levels in the frontal cortex of rats fed with a high-fat diet
  223. Guesstimate of thymoquinone diversity in Nigella sativa L. genotypes and elite varieties collected from Indian states using HPTLC technique
  224. Analysis of bacterial community structure of Fuzhuan tea with different processing techniques
  225. Untargeted metabolomics reveals sour jujube kernel benefiting the nutritional value and flavor of Morchella esculenta
  226. Mycobiota in Slovak wine grapes: A case study from the small Carpathians wine region
  227. Elemental analysis of Fadogia ancylantha leaves used as a nutraceutical in Mashonaland West Province, Zimbabwe
  228. Microbiological transglutaminase: Biotechnological application in the food industry
  229. Influence of solvent-free extraction of fish oil from catfish (Clarias magur) heads using a Taguchi orthogonal array design: A qualitative and quantitative approach
  230. Chromatographic analysis of the chemical composition and anticancer activities of Curcuma longa extract cultivated in Palestine
  231. The potential for the use of leghemoglobin and plant ferritin as sources of iron
  232. Investigating the association between dietary patterns and glycemic control among children and adolescents with T1DM
  233. Bioengineering and Biotechnology
  234. Biocompatibility and osteointegration capability of β-TCP manufactured by stereolithography 3D printing: In vitro study
  235. Clinical characteristics and the prognosis of diabetic foot in Tibet: A single center, retrospective study
  236. Agriculture
  237. Biofertilizer and NPSB fertilizer application effects on nodulation and productivity of common bean (Phaseolus vulgaris L.) at Sodo Zuria, Southern Ethiopia
  238. On correlation between canopy vegetation and growth indexes of maize varieties with different nitrogen efficiencies
  239. Exopolysaccharides from Pseudomonas tolaasii inhibit the growth of Pleurotus ostreatus mycelia
  240. A transcriptomic evaluation of the mechanism of programmed cell death of the replaceable bud in Chinese chestnut
  241. Melatonin enhances salt tolerance in sorghum by modulating photosynthetic performance, osmoregulation, antioxidant defense, and ion homeostasis
  242. Effects of plant density on alfalfa (Medicago sativa L.) seed yield in western Heilongjiang areas
  243. Identification of rice leaf diseases and deficiency disorders using a novel DeepBatch technique
  244. Artificial intelligence and internet of things oriented sustainable precision farming: Towards modern agriculture
  245. Animal Sciences
  246. Effect of ketogenic diet on exercise tolerance and transcriptome of gastrocnemius in mice
  247. Combined analysis of mRNA–miRNA from testis tissue in Tibetan sheep with different FecB genotypes
  248. Isolation, identification, and drug resistance of a partially isolated bacterium from the gill of Siniperca chuatsi
  249. Tracking behavioral changes of confined sows from the first mating to the third parity
  250. The sequencing of the key genes and end products in the TLR4 signaling pathway from the kidney of Rana dybowskii exposed to Aeromonas hydrophila
  251. Development of a new candidate vaccine against piglet diarrhea caused by Escherichia coli
  252. Plant Sciences
  253. Crown and diameter structure of pure Pinus massoniana Lamb. forest in Hunan province, China
  254. Genetic evaluation and germplasm identification analysis on ITS2, trnL-F, and psbA-trnH of alfalfa varieties germplasm resources
  255. Tissue culture and rapid propagation technology for Gentiana rhodantha
  256. Effects of cadmium on the synthesis of active ingredients in Salvia miltiorrhiza
  257. Cloning and expression analysis of VrNAC13 gene in mung bean
  258. Chlorate-induced molecular floral transition revealed by transcriptomes
  259. Effects of warming and drought on growth and development of soybean in Hailun region
  260. Effects of different light conditions on transient expression and biomass in Nicotiana benthamiana leaves
  261. Comparative analysis of the rhizosphere microbiome and medicinally active ingredients of Atractylodes lancea from different geographical origins
  262. Distinguish Dianthus species or varieties based on chloroplast genomes
  263. Comparative transcriptomes reveal molecular mechanisms of apple blossoms of different tolerance genotypes to chilling injury
  264. Study on fresh processing key technology and quality influence of Cut Ophiopogonis Radix based on multi-index evaluation
  265. An advanced approach for fig leaf disease detection and classification: Leveraging image processing and enhanced support vector machine methodology
  266. Erratum
  267. Erratum to “Protein Z modulates the metastasis of lung adenocarcinoma cells”
  268. Erratum to “BRCA1 subcellular localization regulated by PI3K signaling pathway in triple-negative breast cancer MDA-MB-231 cells and hormone-sensitive T47D cells”
  269. Retraction
  270. Retraction to “Protocatechuic acid attenuates cerebral aneurysm formation and progression by inhibiting TNF-alpha/Nrf-2/NF-kB-mediated inflammatory mechanisms in experimental rats”
https://doi.org/10.1515/biol-2022-0537
Keywords for this article
blended fertilizer; inoculation; Rhizobia etli
Creative Commons
BY 4.0

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  148. Hemorrhagic meningioma with pulmonary metastasis: Case report and literature review
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  160. Small breast epithelial mucin as a useful prognostic marker for breast cancer patients
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  170. Precisional detection of lymph node metastasis using tFCM in colorectal cancer
  171. Advances in diagnosis and treatment of perimenopausal syndrome
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  175. Fractalkine modulates pulmonary angiogenesis and tube formation by modulating CX3CR1 and growth factors in PVECs
  176. Novel risk prediction models for deep vein thrombosis after thoracotomy and thoracoscopic lung cancer resections, involving coagulation and immune function
  177. Exploring the diagnostic markers of essential tremor: A study based on machine learning algorithms
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  183. A biomedical decision support system for meta-analysis of bilateral upper-limb training in stroke patients with hemiplegia
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  185. Stochastic gradient descent optimisation for convolutional neural network for medical image segmentation
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  190. Analysis of early diagnosis methods for asymmetric dementia in brain MR images based on genetic medical technology
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  192. Clinical significance of the detection of serum IgG4 and IgG4/IgG ratio in patients with thyroid-associated ophthalmopathy
  193. Forecast of pain degree of lumbar disc herniation based on back propagation neural network
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  209. Incidence of different pressure patterns of spinal cerebellar ataxia and analysis of imaging and genetic diagnosis
  210. Pathogenic bacteria and treatment resistance in older cardiovascular disease patients with lung infection and risk prediction model
  211. Adoption value of support vector machine algorithm-based computed tomography imaging in the diagnosis of secondary pulmonary fungal infections in patients with malignant hematological disorders
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  214. Monitoring of hourly carbon dioxide concentration under different land use types in arid ecosystem
  215. Comparing the differences of prokaryotic microbial community between pit walls and bottom from Chinese liquor revealed by 16S rRNA gene sequencing
  216. Effects of cadmium stress on fruits germination and growth of two herbage species
  217. Bamboo charcoal affects soil properties and bacterial community in tea plantations
  218. Optimization of biogas potential using kinetic models, response surface methodology, and instrumental evidence for biodegradation of tannery fleshings during anaerobic digestion
  219. Understory vegetation diversity patterns of Platycladus orientalis and Pinus elliottii communities in Central and Southern China
  220. Studies on macrofungi diversity and discovery of new species of Abortiporus from Baotianman World Biosphere Reserve
  221. Food Science
  222. Effect of berrycactus fruit (Myrtillocactus geometrizans) on glutamate, glutamine, and GABA levels in the frontal cortex of rats fed with a high-fat diet
  223. Guesstimate of thymoquinone diversity in Nigella sativa L. genotypes and elite varieties collected from Indian states using HPTLC technique
  224. Analysis of bacterial community structure of Fuzhuan tea with different processing techniques
  225. Untargeted metabolomics reveals sour jujube kernel benefiting the nutritional value and flavor of Morchella esculenta
  226. Mycobiota in Slovak wine grapes: A case study from the small Carpathians wine region
  227. Elemental analysis of Fadogia ancylantha leaves used as a nutraceutical in Mashonaland West Province, Zimbabwe
  228. Microbiological transglutaminase: Biotechnological application in the food industry
  229. Influence of solvent-free extraction of fish oil from catfish (Clarias magur) heads using a Taguchi orthogonal array design: A qualitative and quantitative approach
  230. Chromatographic analysis of the chemical composition and anticancer activities of Curcuma longa extract cultivated in Palestine
  231. The potential for the use of leghemoglobin and plant ferritin as sources of iron
  232. Investigating the association between dietary patterns and glycemic control among children and adolescents with T1DM
  233. Bioengineering and Biotechnology
  234. Biocompatibility and osteointegration capability of β-TCP manufactured by stereolithography 3D printing: In vitro study
  235. Clinical characteristics and the prognosis of diabetic foot in Tibet: A single center, retrospective study
  236. Agriculture
  237. Biofertilizer and NPSB fertilizer application effects on nodulation and productivity of common bean (Phaseolus vulgaris L.) at Sodo Zuria, Southern Ethiopia
  238. On correlation between canopy vegetation and growth indexes of maize varieties with different nitrogen efficiencies
  239. Exopolysaccharides from Pseudomonas tolaasii inhibit the growth of Pleurotus ostreatus mycelia
  240. A transcriptomic evaluation of the mechanism of programmed cell death of the replaceable bud in Chinese chestnut
  241. Melatonin enhances salt tolerance in sorghum by modulating photosynthetic performance, osmoregulation, antioxidant defense, and ion homeostasis
  242. Effects of plant density on alfalfa (Medicago sativa L.) seed yield in western Heilongjiang areas
  243. Identification of rice leaf diseases and deficiency disorders using a novel DeepBatch technique
  244. Artificial intelligence and internet of things oriented sustainable precision farming: Towards modern agriculture
  245. Animal Sciences
  246. Effect of ketogenic diet on exercise tolerance and transcriptome of gastrocnemius in mice
  247. Combined analysis of mRNA–miRNA from testis tissue in Tibetan sheep with different FecB genotypes
  248. Isolation, identification, and drug resistance of a partially isolated bacterium from the gill of Siniperca chuatsi
  249. Tracking behavioral changes of confined sows from the first mating to the third parity
  250. The sequencing of the key genes and end products in the TLR4 signaling pathway from the kidney of Rana dybowskii exposed to Aeromonas hydrophila
  251. Development of a new candidate vaccine against piglet diarrhea caused by Escherichia coli
  252. Plant Sciences
  253. Crown and diameter structure of pure Pinus massoniana Lamb. forest in Hunan province, China
  254. Genetic evaluation and germplasm identification analysis on ITS2, trnL-F, and psbA-trnH of alfalfa varieties germplasm resources
  255. Tissue culture and rapid propagation technology for Gentiana rhodantha
  256. Effects of cadmium on the synthesis of active ingredients in Salvia miltiorrhiza
  257. Cloning and expression analysis of VrNAC13 gene in mung bean
  258. Chlorate-induced molecular floral transition revealed by transcriptomes
  259. Effects of warming and drought on growth and development of soybean in Hailun region
  260. Effects of different light conditions on transient expression and biomass in Nicotiana benthamiana leaves
  261. Comparative analysis of the rhizosphere microbiome and medicinally active ingredients of Atractylodes lancea from different geographical origins
  262. Distinguish Dianthus species or varieties based on chloroplast genomes
  263. Comparative transcriptomes reveal molecular mechanisms of apple blossoms of different tolerance genotypes to chilling injury
  264. Study on fresh processing key technology and quality influence of Cut Ophiopogonis Radix based on multi-index evaluation
  265. An advanced approach for fig leaf disease detection and classification: Leveraging image processing and enhanced support vector machine methodology
  266. Erratum
  267. Erratum to “Protein Z modulates the metastasis of lung adenocarcinoma cells”
  268. Erratum to “BRCA1 subcellular localization regulated by PI3K signaling pathway in triple-negative breast cancer MDA-MB-231 cells and hormone-sensitive T47D cells”
  269. Retraction
  270. Retraction to “Protocatechuic acid attenuates cerebral aneurysm formation and progression by inhibiting TNF-alpha/Nrf-2/NF-kB-mediated inflammatory mechanisms in experimental rats”
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