Dual Action of Bacillus and Lactobacillus spp.: Promoting Bean Cultivar Development and Suppressing Xanthomonas axonopodis pv. phaseoli

Abstract

Common bacterial blight (CBB) is a significant disease caused by the seed-borne pathogen Xanthomonas axonopodis pv. phaseoli (Xap), which devastates global bean production. This study evaluated the effects of Bacillus subtilis (Bst26), Lactobacillus plantarum (Lpkb10), their combination (Bst26 + Lpkb10), copper hydroxide (CH), and an untreated control on controlling CBB in three bean cultivars (Göynük, Saltan, and Tezgeldi). Disease incidence (CI), disease severity index (DSI), severity score (SC), area under disease progress curve (AUDPC), and disease control (DC), along with agronomic traits such as plant height, number of primary branches, root length, and fresh root weight, were recorded to assess both infection rates and plant health under each treatment. The findings revealed significant differences in DI, DSI, SC, AUDPC, and DC (p ≤ 0.01) among the bean cultivars for CBB. Among the cultivars, the Bst26 treatment and the combination of Bst26 and Lpkb10 showed the highest control effectiveness, with DI values of 33.11% and 33.46% in Saltan, 35.65% and 44.16% in Göynük, and 37.71% and 42.43% in Tezgeldi, respectively, at 21 days after inoculation (DAI). Bst26 alone and in combination with Lpkb10 effectively controlled CBB, with disease reduction of 56.80% and 46.49% in Göynük, 57.08% and 56.62% in Saltan, and 52.18% and 46.19% in Tezgeldi, respectively. Disease progression was highest in the untreated control, with DI ranging from 77.15% to 82.54% across Göynük, Saltan, and Tezgeldi cultivars. Significant differences (p ≤ 0.01) in plant height, root length, and root weight were observed among treatments and cultivars. Disease parameters were negatively correlated with plant growth traits, and multi-treatment analysis demonstrated that combining bacterial strains effectively reduced disease severity in susceptible cultivars, highlighting their potential for improved CBB management.

1. Introduction

Common bacterial blight (CBB), caused by Xanthomonas axonopodis pv. phaseoli (Xap), is considered the most damaging disease affecting beans globally [1,2]. CBB is widespread in areas where beans (Phaseolus vulgaris L.) are cultivated, including Brazil, the United States, Argentina, India, South Africa, Uganda, and Ethiopia [3,4,5,6,7,8,9]. In 2023, global common bean production was estimated at 28,505,529 metric tons, with Asia producing the largest share (44.1%), followed by Africa (29.2%), the Americas (24.9%), Europe (1.2%), and Oceania (0.6%). As shown in

Table 1. Top 10 common bean (Phaseolus vulgaris L.) producing countries worldwide in 2023 [10].

Ranks	Country	Production (Tons)	World Share (%)
1	India	6,491,362.2	22.77%
2	Brazil	2,899,043.0	10.17%
3	Myanmar	2,683,918.8	9.42%
4	Tanzania	1,484,000.0	5.21%
5	China	1,304,639.86	4.58%
6	USA	1,071,613.0	3.76%
7	Uganda	865,202.84	3.04%
8	Kenya	860,973.0	3.02%
9	Burundi	834,214.01	2.93%
10	Argentina	792,564.0	2.78%

, India is the leading global producer, producing 6,491,362.2 t and accounting for 22.77% of total global production, followed by Brazil, Myanmar, Tanzania, and China.

In Turkey, beans are the third most cultivated legume after lentils and chickpeas, with an annual production of approximately 305,000 tons in 2021 [11,12]. CBB is a major seed-borne disease that can persist in infected seeds, crop residues, and soil, with seeds serving as the primary inoculum source, affecting bean-growing regions across the country [13,14].

Favorable conditions, such as prolonged warmth and high humidity, promote its spread, causing both qualitative and quantitative yield losses through lesions on leaves, pods, stems, and seeds [7,15]. In the field, the disease spreads primarily through contaminated seeds, rain splash, irrigation water, and mechanical transmission. Infection occurs when the pathogen enters plant tissues via natural openings, wounds, or stomata, leading to leaf blight, pod lesions, and reduced plant growth and yield [6]. The disease can affect seed quality at any growth stage, persist in seeds for up to 15 years, and cause yield reductions of 20–70% in susceptible cultivars. Under ideal conditions for the pathogen, total crop failure can occur, resulting in economic losses worth billions of US dollars [16,17,18,19,20].

Some farmers treat bean seeds with chemical pesticides or apply sprays in the field to manage pests and soilborne diseases. While these practices are common, frequent chemical use is often ineffective and can negatively affect beneficial microbes, pollute soil and water, and disrupt both natural and agricultural ecosystems [21,22,23,24]. These concerns highlight the need for alternative, sustainable approaches, such as the use of beneficial bioagents, to manage common bacterial blight (CBB) in beans.

Beneficial bioagents, such as Bacillus, Pseudomonas, and Lactobacillus spp., have gained attention for their potential to manage plant diseases while promoting growth and yield [25,26]. Bacillus spp. are well-studied for producing lipopeptides, enzymes, and antibiotics that suppress a range of plant diseases, including fire blight, common bacterial blight, soft rot, Fusarium wilt, Sclerotinia rot, Rhizoctonia root rot, and nematode infections, in addition to enhancing plant growth [25,27,28,29,30].

Although less studied in legumes, Lactobacillus spp. produce antimicrobial metabolites, such as lactic acid and bacteriocins, and can improve plant resilience [31]. Despite extensive research on individual BCAs, the combined use of Bacillus and Lactobacillus for simultaneous biocontrol and growth promotion in bean cultivars remains unexplored.

In this study, we evaluated the effectiveness of bioagent treatments, Bacillus subtilis (Bst26), Lactobacillus plantarum (Lpkb10), and their combination (Bst26 + Lpkb10), compared to copper hydroxide (CH) on three bean cultivars (Göynük, Saltan, and Tezgeldi), and assessed interactions among these treatments.

2. Materials and Methods

2.1. Plant Material and Growth Conditions

This experiment was conducted in 2024 under controlled conditions at the Molecular Plant Bacteriology Laboratory (BASTAS Lab), Department of Plant Protection, Faculty of Agriculture, Selcuk University, Konya, Türkiye, using three bean cultivars commonly grown in Türkiye: Göynük, Saltan, and Tezgeldi. These cultivars were selected because they represent popular local varieties. Seeds of each cultivar were surface-sterilized in a 1% sodium hypochlorite solution for 5 min to eliminate potential surface microbes, followed by thorough rinsing with sterile distilled water. Sterilized seeds were placed in sterile Petri dishes to soften and promote rapid germination prior to sowing in pots. After four days, germinated seeds were soaked in the beneficial bacterial suspension as described below and subsequently transplanted into sterile pots (20 cm diameter × 21 cm depth). The soil used in this study was collected from an agricultural area in the Çumra district (37.51° N, 32.47° E), Konya Province, Türkiye, a major agricultural zone covering approximately 172,000 ha and around 1013 m above sea level [32]. The soil was medium clay and originated from a field previously cultivated with leguminous crops. Before use, the soil was air-dried, sieved through a 2 mm mesh to remove debris and large aggregates, and autoclaved at 121 °C for 1 h to eliminate potential contaminants. The sterilized field soil was then mixed with sterilized peat and perlite (1:1:1, v/v/v) obtained from Agrikal Agriculture and Industrial Minerals Ltd., Co., forming the growth substrate. The chemical composition of the substrate was as follows: nitrogen (N), 149.7 mg kg⁻¹; phosphorus (P), 91.02 mg kg⁻¹; potassium (K), 56.44 mg kg⁻¹; calcium (Ca), 12.81 me 100 g⁻¹; and magnesium (Mg), 2.69 me 100 g⁻¹, showing sufficient nutrient levels to support healthy plant growth. Each pot contained 4 kg of soil substrate, with five plants per pot, maintained under controlled environmental conditions (8 h light/16 h dark photoperiod, 25 ± 2 °C, 65% relative humidity) and irrigated every 3 days with distilled water to maintain adequate soil moisture until the end of the experiment.

2.2. Bacterial Growth and Pathogen Inoculation

A highly virulent Xanthomonas axonopodis pv. phaseoli strain (Xap-kkb-15), causing approximately 85% disease severity in preliminary virulence assays, was used as the challenge pathogen in this study. The Xap-kkb-15 strain was originally isolated from seed samples of six common bean cultivars (Dermason, Cali, Sira, Battal, Bombay, and Seker) gathered across 12 provinces in the Central Anatolia Region, Türkiye (Ankara, Aksaray, Çorum, Eskişehir, Kayseri, Kırşehir, Kırıkkale, Konya, Nevşehir, Niğde, Sivas, and Yozgat). In total, 198 seed samples, each weighing approximately 2500 g (≈5000 seeds), were collected from local bean producers in accordance with International Seed Testing Association standards [33]. This strain was previously characterized biochemically, including Gram reaction (negative), levan production (negative), fluorescence on King’s B medium under UV light (negative), oxidase test (negative), nitrate reduction (negative), urease and indole production (negative), catalase activity (positive), pectolytic activity (negative), arginine-dihydrolase (negative), hypersensitive reaction on tobacco (positive), H₂S production from cysteine (positive), hydrolysis of gelatin (negative), aesculin (positive), starch (positive), and casein (positive), as well as acid production from sucrose (positive), maltose (positive), sorbitol (negative), mannitol (negative), and insitol (negative). The molecular characterization of the strain was conducted in the earlier work of Bastas et al. [13], and the strain has been preserved in the Bastas Laboratory Collection, Selcuk University, Molecular Plant Bacteriology Laboratory. To maintain the strain’s pathogenicity, it was cultured on Tryptic Soy Agar (TSA) at 28 °C for 48 h, inoculated onto bean plants, re-isolated from the infected tissues, and subsequently used in the experiments.

Bacillus subtilis (Bst26) and Lactobacillus plantarum (Lpkb10) were originally isolated from intensively cultivated agricultural areas of the Çumra district, Konya Province, Türkiye. Specifically, Bst26 was obtained from the rhizosphere of healthy bean plants, while Lpkb10 was isolated from the rhizosphere of tomato plants. Each soil sample was collected from a depth of 0–20 cm. For bacterial isolation, 10 g of soil was suspended in 90 mL of sterile distilled water and shaken at 150 rpm for 30 min. Subsequently, 1 mL of the suspension was transferred into 9 mL sterile Nutrient Broth (NB) to prepare a five-step serial dilution. A dilution of 10⁻² was selected for routine isolation due to its ability to produce well-separated and uniformly distributed colonies. From this dilution, 100 µL aliquots were plated in triplicate onto Nutrient Agar and incubated at 25 °C for 24–48 h. Emerging colonies were purified and subjected to biochemical tests and molecular characterization in the Bastas Molecular Plant Bacteriology Laboratory, Selcuk University (unpublished). Both strains were selected for further evaluation against Xap-kkb-15 based on their strong antagonistic activity and plant growth-promoting potential observed in preliminary assays.

In this study, Bacillus subtilis (Bst26), Lactobacillus plantarum (Lpkb10), and their combination (Bst26 + Lpkb10) were used as bioagent treatments. The bacterial strains were grown on TSA at 28 °C for 48 h and subsequently used for three applications. After growth, colonies were suspended in sterile water and adjusted to 10⁸ CFU mL⁻¹ (OD₆₀₀ = 0.15). The first bioagent application was performed at seed germination, prior to transplanting, by soaking germinated seeds in the bacterial suspension (10⁸ CFU mL⁻¹, OD₆₀₀ = 0.15) for 30 min. Copper hydroxide (1.7 g L⁻¹) and sterile distilled water (SDW) were applied as controls. The seedlings were then transplanted into sterile pots. Seven days later, a second bioagent application was performed by spraying the same bacterial suspension onto the leaves.

Fresh colonies of Xap-kkb-15 were suspended in sterile distilled water and adjusted to 10⁷ CFU mL⁻¹ (OD₆₀₀ = 0.15) using a spectrophotometer. The pathogen was inoculated onto bean plants 7 days after the second bioagent application, corresponding to 14 days after transplanting germinated seeds into pots. Inoculation was carried out by gently syringe-infiltrating the bacterial suspension into leaf tissues without causing visible mechanical damage, followed by spraying the suspension onto leaf surfaces using a handheld atomizer. After inoculation, pots were covered with polyethylene bags for 72 h to maintain high humidity and promote disease development, after which the bags were removed [30]. Disease symptoms were monitored daily, and initial symptoms appeared three days after inoculation (17 days after transplanting). On the same day, the third bioagent and control treatments were applied using the same procedure as the previous applications.

2.3. Experimental Design and Disease Assessment

The experiment was arranged in a completely randomized design (CRD) with three cultivars and five treatments. Each cultivar × treatment combination included three biological replicates, with five plants per pot, giving a total of 225 plants. The experiment was conducted once under controlled environmental conditions. Disease evaluation was carried out for 20 days following Xap inoculation. To monitor disease progression, disease incidence (DI) was assessed at 8, 15, and 21 days after inoculation (DAI). Disease severity index (DSI) and severity score (SC) were determined at 21 DAI, while the area under the disease progress curve (AUDPC) was calculated using the DI values from 8, 15, and 21 DAI, according to the formulas shown below.

$$\mathrm{D}\mathrm{I}(\mathrm{\%})={\displaystyle \frac{\mathrm{Number} \mathrm{of} \mathrm{infected} \mathrm{leaves}}{\mathrm{Total} \mathrm{number} \mathrm{of} \mathrm{leaves} \mathrm{observed}}} \times 100$$

(1)

$$\mathrm{D}\mathrm{S}\mathrm{I}(\mathrm{\%})={\displaystyle \frac{\mathrm{Total} \mathrm{sum} \mathrm{of} \mathrm{ratings}}{\mathrm{Total} \mathrm{number} \mathrm{of} \mathrm{plants} \mathrm{assessed} \times \mathrm{Maximum} \mathrm{rating} (\mathrm{score}) \mathrm{on} \mathrm{scale}}} \times 100$$

(2)

$$\mathrm{D}\mathrm{C}(\mathrm{\%})={\displaystyle \frac{\mathrm{Disease} \mathrm{incidence} \mathrm{in} \mathrm{control} \mathrm{group} - \mathrm{Disease} \mathrm{incidence} \mathrm{in} \mathrm{treated} \mathrm{group} }{\mathrm{Disease} \mathrm{incidence} \mathrm{in} \mathrm{control} \mathrm{group}}}\times 100$$

(3)

$$\mathrm{A}\mathrm{U}\mathrm{D}\mathrm{P}\mathrm{C}=\sum _{\mathrm{i}=1}^{\mathrm{n}-1}{\displaystyle \frac{\left(\mathrm{Y}\mathrm{i}+\mathrm{Y}\mathrm{i}+1\right)}{2}}\times \left(\mathrm{t}\mathrm{i}+1-\mathrm{t}\mathrm{i}\right)$$

(4)

where Yi is the percent severity index expressed as a proportion at the ith observation, ti is the time (days after inoculation) at the ith observation, and n is the total number of observations.

The severity of CBB was assessed using a modified CIAT 0–9 visual scale [34,35], where 0 = no symptoms, 1 = 1% leaf area affected, 2 = 2–5%, 3 = 6–10%, 4 = 11–15%, 5 = 16–30%, 6 = 31–50%, 7 = 51–75%, 8 = 76–85%, and 9 = >85% of the leaf area showing lesions.

Additionally, to assess bean growth and evaluate temporal differences, plant height was measured from the above-soil portion at 5 and 7 weeks of age using a centimeter scale. At 7 weeks, the number of leaves and the number of primary branches (main lateral stems that originate directly from the primary stem) were also recorded. During the 8th week, representing the final stage of the experiment, all plants in each pot were carefully removed from the soil, and the roots were gently washed. Roots of individual plants were separated and measured for root length (cm) and fresh root weight (g) using a centimeter scale and a digital balance, respectively.

2.4. Statistical Analysis

Data were subjected to analysis of variance (ANOVA) using OriginPro 2025 (OriginLab Corporation, Northampton, MA, USA). Mean comparisons were performed using Tukey’s HSD test to determine significant differences among treatments and cultivars. Pearson’s correlation coefficients were calculated to evaluate relationships between disease parameters and growth traits. Principal Component Analysis (PCA) was conducted to assess multivariate patterns among variables. Figures were generated using OriginPro 2025, draw.io, and R (version 4.5.1), with the ggplot2, tidyr, and dplyr packages employed to create box plots.

3. Results

Beans, as a major legume used for human and animal feed, are increasingly threatened by climate change, and the use of chemical treatments to manage Xap poses risks to both the environment and human health. Therefore, this study focused on applying different bioagent treatments as a sustainable alternative. The results showed that common bacterial blight (CBB) in bean cultivars caused highly significant differences (p ≤ 0.01) in disease incidence, disease severity index, and severity score. Significant variations were also observed in the area under the disease progress curve (AUDPC) and disease control rates compared with the untreated control group (

Table 2. Impact of Treatments on CBB Disease Progression Parameters Across Bean Cultivars.

Cultivar	Treatment	8 DAI	DI (%) 15 DAI	21 DAI	DSI (%)	SC	AUDPC	DC (%)
Göynük	Bst26	23.77 ± 1.4 c	30.26 ± 1.9 c	35.65 ± 1.7 c	39.15 ± 5.0 defg	5.57 ± 0.5 cde	651.26 ± 39.0 f	56.80
	Lpkb10	31.84 ± 3.7 bc	39.77 ± 4.6 bc	46.62 ± 4.6 bc	44.23 ± 1.9 de	6.40 ± 0.5 bcd	910.25 ± 9.8 d	43.51
	Mixed (Bst26 + Lpkb10)	29.38 ± 6.0 c	37.26 ± 6.6 c	44.16 ± 6.6 c	44.41 ± 5.0 de	5.94 ± 0.3 bcd	730.10 ± 38.31 ef	46.49
	CH	31.43 ± 9.5 bc	38.47 ± 9.6 bc	45.14 ± 9.4 bc	42.14 ± 1.0 def	6.17 ± 0.16 bcd	748.63 ± 28.9 e	43.31
	Control (SDW)	57.70 ± 2.3 a	70.85 ± 1.0 a	82.54 ± 2.7 a	80.44 ± 1.3 a	8.35 ± 0.5 a	2023.64 ± 8.0 a	0.00
Saltan	Bst26	22.69 ± 2.9 c	28.51 ± 3.2 c	33.11 ± 3.5 c	28.23 ± 1.6 gh	5.22 ± 0.1 de	516.86 ± 12.6 g	57.08
	Lpkb10	27.11 ± 3.7 c	32.83 ± 3.8 c	37.17 ± 3.4 c	35.34 ± 2.8 efg	5.71 ± 0.5 cde	714.00 ± 12.8 ef	51.82
	Mixed (Bst26 + Lpkb10)	23.55 ± 5.3 c	29.59 ± 5.0 c	33.46 ± 5.1 c	14.73 ± 1.0 i	4.26 ± 0.6 e	307.63 ± 5.0 i	56.62
	CH	28.30 ± 3.2 c	33.90 ± 3.1 c	38.60 ± 2.4 c	23.23 ± 2.5 hi	5.08 ± 0.9 de	425.36 ± 15.2 h	49.96
	Control (SDW)	56.79 ± 2.1 a	67.15 ± 1.5 a	77.15 ± 2.6 a	59.83 ± 1.0 bc	6.98 ± 0.1 abc	1235.89 ± 32.2 b	0.00
Tezgeldi	Bst26	26.67 ± 1.8 c	33.27 ± 1.8 c	37.71 ± 2.6 c	32.90 ± 2.0 fgh	5.34 ± 0.7 de	731.49 ± 6.7 ef	52.18
	Lpkb10	42.53 ± 4.2 b	51.18 ± 5.0 b	58.96 ± 5.0 b	49.70 ± 6.7 cd	6.84 ± 0.2 bc	1228.61 ± 34.6 b	25.23
	Mixed (Bst26 + Lpkb10)	29.00 ± 4.5 c	35.92 ± 5.2 c	42.43 ± 6.4 c	38.82 ± 7.0 defg	6.05 ± 0.5 bcd	905.37 ± 51.9 d	46.19
	CH	30.09 ± 4.5 bc	37.19 ± 4.7 bc	43.76 ± 4.5 c	34.48 ± 5.0 efg	5.08 ± 0.1 de	928.79 ± 50.0 d	44.50
	Control (SDW)	59.65 ± 1.0 a	69.16 ± 1.0 a	78.86 ± 1.7 a	67.56 ± 1.5 b	7.40 ± 0.3 ab	1131.81 ± 25.3 c	0.00
CV (%)		14.76	13.54	13.36	16.41	12.35	29.12	-

Bst26, Bacillus subtilis; Lpkb10, Lactobacillus plantarum; DI, disease incidence; DSI, disease severity index; SC, severity score; AUDPC, area under the disease progress curve; DC, disease control; DAI, days after inoculation; SDW, sterile distilled water; ±, standard deviation of the mean; CH, copper hydroxide; CV, coefficient of variation. Different lowercase letters within a column indicate significant differences among treatments and varieties, according to Tukey’s HSD test (p ≤ 0.01).

). Similarly, plant growth traits, including plant height, root length, and fresh root weight, differed significantly among treatments (p ≤ 0.01). Disease suppression was associated with improved plant performance, as reflected by increases in plant height, number of leaves, and number of primary branches per plant relative to the control group (Table 2 and

Table 3. Impact of Treatments on some agronomic parameters in different Bean Cultivars.

Cultivar	Treatment	PH5 (cm)	PH7 (cm)	NPBPP (co)	NL (co)	RL (cm)	RW (g)
Göynük	Bst26	52.25 ± 5.5 a	68.76 ± 0.5 bc	3.36 ± 0.7 a	17.66 ± 1.5 ab	24.06 ± 1.7 ab	3.85 ± 0.1 cd
	Lpkb10	52.50 ± 6.5 a	74.47 ± 2.1 a	3.09 ± 0.5 a	13.99 ± 1.5 bcde	20.66 ± 2.0 b	2.79 ± 0.3 cd
	Mixed (Bst26 + Lpkb10)	52.33 ± 2.5 a	74.00 ± 1.0 ab	2.51 ± 1.1 ab	16.58 ± 2.5 abc	19.78 ± 6.0 b	3.31 ± 0.8 cd
	CH	48.55 ± 0.9 ab	68.11 ± 0.5 cd	2.75 ± 0.5 ab	16.25 ± 1.0 abc	19.77 ± 0.8 b	4.39 ± 0.5 bcd
	Control (SDW)	35.77 ± 2.2 d	56.10 ± 2.2 hi	1.31 ± 0.6 b	11.00 ± 1.0 def	18.88 ±1.0 b	1.85 ± 0.4 d
Saltan	Bst26	49.46 ± 6.5 ab	67.07 ± 2.0 cd	2.98 ± 0.5 ab	15.46 ± 1.5 abc	20.55 ± 1.3 b	7.47 ± 1.0 ab
	Lpkb10	40.37 ± 1.0 bcd	58.78 ± 2.1 fghi	2.77 ± 0.5 ab	14.41 ± 0.6 bcd	21.21 ± 0.7 b	3.26 ± 1.5 cd
	Mixed (Bst26 + Lpkb10)	44.24 ± 4.4 abcd	60.85 ± 1.5 efgh	2.64 ± 0.3 ab	15.66 ± 1.0 abc	23.66 ± 1.0 ab	4.66 ± 0.4 bcd
	CH	40.19 ± 1.0 bcd	58.08 ± 1.7 ghi	2.64 ± 0.2 ab	15.83 ± 1.5 abc	18.99 ± 1.5 b	4.10 ± 0.1 bcd
	Control (SDW)	37.39 ± 2.0 cd	55.15 ± 1.0 i	1.84 ± 0.1 ab	11.25 ± 1.0 def	19.11 ± 0.5 b	3.85 ± 1.5 cd
Tezgeldi	Bst26	40.74 ± 2.1 bcd	61.32 ± 2.4 efgh	2.51 ± 0.6 ab	18.66 ± 1.0 a	29.62 ± 0.6 a	10.29 ± 1.7 a
	Lpkb10	43.12 ± 2.5 abcd	62.97 ± 0.5 defg	2.10 ± 0.6 ab	8.50 ± 1.0 f	17.73 ± 3.6 b	5.98 ± 2.0 bc
	Mixed (Bst26 + Lpkb10)	46.93 ± 5.2 abc	63.40 ± 1.8 def	3.07 ± 0.5 a	13.60 ± 2.3 bcde	21.66 ± 2.9 b	7.51 ± 1.5 ab
	CH	47.31 ± 2.1 abc	64.08 ± 3.0 cde	2.54 ± 0.4 ab	13.08 ± 1.0 cde	21.33 ± 1.2 b	5.85 ± 1.1 bc
	Control (SDW)	43.14 ± 2.5 abcd	58.73 ± 1.1 fghi	1.34 ± 0.2 b	10.24 ± 0.6 ef	19.50 ± 5.4 b	4.49 ± 1.1 bcd
CV (%)		14.47	10.02	23.68	18.40	20.98	10.02

Bst26, Bacillus subtilis; Lpkb10, Lactobacillus plantarum; CH, copper hydroxide; PH5, plant height at 5-week ages; PH7, plant height at 7-week ages; NPBPP, number of primary branches per plant; NL, number of leaves; RL, root length; RW, fresh root weight; SDW, sterile distilled water; ±, standard deviation of the mean; CV, coefficient of variation; cm, centimeter; co, count; g, gram. Different lowercase letters within a column indicate significant differences among treatments and varieties, according to Tukey’s HSD test (p ≤ 0.01).

).

3.1. Disease Evaluation

In the Göynük cultivar, the Bst26 treatment was the most effective, resulting in disease incidence (DI) values of 23.77%, 30.26%, and 35.65% at 8, 15, and 21 DAI, respectively, and an area under the disease progress curve (AUDPC) of 651.26 (Table 2). The disease severity index (DSI), severity score, and disease control (DC) percentage were 39.15%, 5.57, and 56.80%, respectively. The Bst26 + Lpkb10 treatment ranked second in effectiveness, with DI values ranging from 29.38% to 44.16%, a DSI of 44.41%, a severity score of 5.94, and a DC of 46.49%. In contrast, the untreated control (SDW) group displayed the highest DI and DSI values, reaching 82.54% at 21 DAI and 80.44%, respectively (Figure 1).

In the Saltan variety, both the Bst26 treatment alone and the combination of Bst26 + Lpkb10 yielded the highest control effectiveness. Bst26 treatment resulted in disease incidence (DI) values of 22.69%, 28.51%, and 33.11% at 8, 15, and 21 DAI, respectively, with a disease severity index (DSI) of 28.23%. The combined treatment showed similar DI values (23.55%, 29.59%, and 33.46% at 8, 15, and 21 DAI, respectively) but achieved a lower DSI of 14.73%. The severity scores were 5.22 for Bst26 alone and 4.26 for the combined treatment. The area under the disease progress curve (AUDPC) values confirmed this trend, with 516.86 for Bst26 and 307.63 for the combined treatment, indicating that the combination reduced disease progression more effectively (Figure 2). However, the disease control (DC) percentage was slightly higher with Bst26 alone (57.08%) compared to the combined treatment (56.62%). These were followed by the Lpkb10 treatment, which reduced DI to 27.11–37.17%, with a DSI of 35.34%, a severity score of 5.71, and an AUDPC value of 714.00. The DC observed in plants treated with Lpkb10 reached 51.82%.

In the Tezgeldi variety, as in the other cultivars, the Bst26 treatment alone was the most effective. This treatment reduced DI values to 26.67%, 33.27%, and 37.71% at 8, 15, and 21 DAI, respectively, with a DSI of 32.90% and a severity score of 5.34, resulting in an AUDPC value of 731.49 and a disease control rate of 52.18%.

The combination of Bst26 + Lpkb10 and the CH treatment were the next most effective, with DI values ranging from 29.00% to 42.43% and 30.09% to 43.76%, DSI values of 38.82% and 34.48%, and disease control rates of 46.19% and 44.50%, respectively. Conversely, the untreated control groups reflected the highest disease incidence and severity index values, reaching 78.86% and 67.56% in Tezgeldi, 77.15% and 59.83% in Saltan, and 82.54% and 80.44% in Göynük (Table 2, Figure 1).

As shown in Table 2 and Figure 3, disease incidence progression varied significantly (p ≤ 0.01) among treatments and bean cultivars for Xap inoculation. In all three cultivars, the lowest disease incidence across all evaluation periods (8, 15, and 21 DAI) was consistently observed in plants treated with Bacillus subtilis 26, while the highest values occurred in the untreated control (SDW). Across all cultivars, copper hydroxide (CH) and Lpkb10 treatments resulted in lower disease incidence and severity compared to the control. Although the mixed treatment (Bst26 + Lpkb10) depicted some reduction in disease incidence, it did not consistently outperform the B. subtilis strain (Bst26) treatment alone (Figure 3).

3.2. Plant Growth Parameters

According to Table 3, the greatest plant heights in the Göynük cultivar were recorded with Lpkb10 treatment, measuring 52.50 cm and 74.47 cm at 5 and 7 weeks of age, respectively. This cultivar also noted a high number of primary branches per plant at 4 weeks. In the Saltan cultivar, Bst26 significantly enhanced plant height across multiple growth stages, while the highest number of primary branches per plant (2.64) was registered with both the mixed treatment and copper hydroxide (CH), presenting similar effects. For the Tezgeldi cultivar, copper hydroxide treatment yielded the greatest plant heights at 4 and 7 weeks (47.31 cm and 64.08 cm, respectively), whereas the combined Bst26 and Lpkb10 treatment produced the highest number of primary branches per plant (3.07), as illustrated in Figure 4.

Across all three bean cultivars, plants in the untreated control group manifested reduced growth and stunting compared to those receiving treatments. Plant heights measured at 5 and 7 weeks of age were 35.77 cm and 56.10 cm in Göynük, 37.39 cm and 55.15 cm in Saltan, and 43.14 cm and 58.73 cm in Tezgeldi.

The treatments, particularly Bacillus subtilis and Lactobacillus plantarum, also positively influenced root development, enhancing both root elongation and biomass across the bean cultivars, as shown in Table 3 and Figure 4e,f.

When Bst26 was applied, the greatest root length (29.62 cm) and fresh root weight (10.29 g), along with the highest number of leaves (18.66), were recorded in the Tezgeldi cultivar. In the Göynük cultivar, this treatment also resulted in notable root length (24.06 cm), fresh root weight (3.85 g), and number of leaves (17.66) compared with other treatments.

Furthermore, in the Saltan cultivar, Bst26 improved fresh root weight (7.47 g), while the combination of Bst26 and Lpkb10 yielded the greatest root length (23.66 cm), as illustrated in Figure 4 and Table 3.

The treatments not only mitigated disease progression but also significantly enhanced bean growth traits, including plant height, leaf number, primary branching, root length, and root biomass (Table 2 and Table 3).

These morphological improvements directly contribute to yield optimization and provide valuable secondary benefits, such as increased biomass for animal fodder and biofuel production. Therefore, the combined effects of disease suppression and growth promotion position these treatments as promising components of climate-resilient and sustainable cropping systems.

3.3. Principal Component Analysis of Disease Parameters and Growth Traits

Principal Component Analysis (PCA) was employed to interpret the multivariate relationships among disease parameters and growth traits across three bean cultivars (Göynük, Saltan, and Tezgeldi) inoculated with Xap. Figure 5a,c,e illustrate the PCA biplots for disease parameters in the Göynük, Saltan, and Tezgeldi cultivars, respectively, while Figure 5b,d,f correspond to growth traits in each cultivar.

For the Göynük cultivar, particularly the disease parameters (Figure 5a), the first two principal components accounted for 99.7% of the total variance, with PC1 and PC2 explaining 99.2% and 0.5%, respectively. These results prove that disease severity, area under the disease progress curve, disease incidence, and severity score are strongly positively correlated and form a tight clustering. Disease control percentage (DC) is negatively correlated with these parameters, signifying that higher disease severity is associated with lower disease control. Treatments such as Bst26 and CH depict differentiation along PC1 and PC2. Based on the growth traits (Figure 5b) in this cultivar, the total variance captured by the principal components is 88.2%, with PC1 and PC2 contributing 75.3% and 12.9%, respectively. Loadings for root length, fresh root weight, number of leaves, and NPBP4 align positively, highlighting that these growth parameters co-vary and may be functionally interconnected.

For the Saltan cultivar, the PCA results for disease parameters (Figure 5c) illustrate that the first two principal components explain 99.7% of the total variance, with PC1 and PC2 representing 95.2% and 4.5%, respectively. Similarly to the Göynük cultivar, disease parameters, namely DSI, AUDPC, SC, and DI, cluster together, reflecting a unified disease response. In contrast, disease control aligns negatively and is positioned oppositely in the biplot space. Regarding growth traits (Figure 5d), the total explained variance amounts 87.2%, distributed across PC1 (69.2%) and PC2 (18.0%). Traits such as root length, number of leaves, NPBP, and fresh root weight reveal positive loadings and group closely, indicating co-variation among vegetative performance indicators. Treatments Bst26 and Mixed display distinct growth responses, while the control condition is positioned near the origin, reflecting minimal influence on principal component separation.

The Tezgeldi cultivar expressed a more nuanced separation in the PCA results (Figure 5e,f), which may reflect genotype-specific variation in disease expression and growth response. For disease parameters (Figure 5e), the first two principal components captured 97.6% of the total variance, with PC1 explaining 91.3% and PC2 contributing 6.3%. Although modest, PC2’s influence may uncover subtle variation in disease patterns across treatments. Regarding growth traits (Figure 5f), PC1 and PC2 accounted for 54.8% and 37.4% of the variance, respectively, manifesting broader dispersion in trait loadings and suggesting greater heterogeneity in morphological responses and growth resilience within the Tezgeldi genotype.

Across all three bean cultivars, PCA clearly distinguishes disease parameters from growth traits, highlighting the inverse relationship between disease severity and disease control. Growth traits cluster distinctly, and treatment effects are evident as separations along the principal components. While Göynük and Saltan present tightly clustered disease and growth profiles, displaying less variability in their responses, Tezgeldi demonstrates a broader dispersion in growth traits and a more adaptive disease–growth relationship. This pattern suggests that Tezgeldi possesses greater morphological resilience and treatment adaptability, making it a promising candidate for breeding programs aimed at enhancing both disease resistance and growth vigor. These observations align with the treatment-specific performance patterns summarized in Table 2 and Table 3.

3.4. Disease-Growth Correlations in Bean Cultivars

To clarify the interrelationships between disease and growth traits under different treatments across bean cultivars inoculated with the Xap pathogen, Pearson’s correlation coefficients were calculated. The correlation matrix demonstrated strong and significant relationships (p < 0.01) between disease parameters and growth traits. Figure 6 presents the correlation matrices for the three bean cultivars.

In the Göynük cultivar, disease incidence (DI) was almost perfectly correlated with the disease severity index (DSI, r = 0.99), severity score (SC, r = 0.99), and the area under the disease progress curve (AUDPC, r = 0.99). DI was perfectly and negatively correlated with disease control percentage (DC, r = −1.00), suggesting that treatments which reduced DI consistently achieved higher disease control.

All disease parameters expressed strong and significant negative correlations with plant height at 5 weeks (PH5), plant height at 7 weeks (PH7), number of leaves (NL), number of primary branches per plant (NPBP), root length (RL), and fresh root weight (RW). Growth traits were positively correlated with one another, particularly PH5 with PH7 (r = 0.96) and NPBP (r = 0.92).

Additionally, the Saltan cultivar displayed similarly strong relationships among disease parameters. DI was strongly correlated with DSI (r = 0.91), SC (r = 0.88), and AUDPC (r = 0.92). DI and DC were perfectly and inversely correlated (r = −1.00), confirming the effectiveness of control treatments. As shown in Figure 6b, all disease parameters were negatively associated with NL and NPBP, with moderate to strong negative correlations with PH5, PH7, and RL. RW was weakly correlated with disease parameters, pointing to that root biomass was less sensitive to disease severity in this cultivar. Growth traits were highly interrelated, with PH5 and PH7 exhibiting an almost perfect correlation (r = 0.99) and strong positive associations with NPBP and RW.

Furthermore, in the Tezgeldi cultivar, DI was almost perfectly correlated with DSI (r = 0.99) and strongly correlated with SC (r = 0.90) and AUDPC (r = 0.79). DI was perfectly and negatively correlated with DC (r = −1.00). Higher disease levels were strongly associated with reductions in PH7, NL, NPBP, RL, and RW (Figure 6c). DC was strongly and positively correlated with NPBP, RL, and RW, which signified that effective disease control was associated with better plant vigor and root development. Growth parameters were generally positively correlated with each other, with particularly strong relationships between RL and RW (r = 0.90) and between NL and RW (r = 0.98).

All correlation data pointed out that increases in disease incidence and severity index were consistently associated with reductions in vegetative and root growth traits of bean varieties, and vice versa. This establishes a strong relationship between disease severity and plant growth performance. The perfect negative correlation between DC and disease parameters across all cultivars underscores the importance of effective disease management in sustaining plant vigor and yield potential.

4. Discussion

X. a. pv. phaseoli not only reduces production but also affects seed quality and quantity and can spread across countries through seed-borne transmission [36,37]. To reduce the impacts of climate change, chemical use, and associated risks to human health and the environment, the application of biological control agents has gained increasing global attention for sustainable crop production. These eco-friendly agents, effective against fungi, viruses, and bacteria, reduce disease severity and infection rates and are increasingly adopted worldwide, including in Turkey, as part of sustainable plant protection practices [28,29,38,39,40,41,42].

Many researchers have reported that Bacillus amyloliquefaciens, Bacillus subtilis, Bacillus pumilus, and other strains can reduce the incidence and severity of plant pathogens, including common bacterial blight, by interacting with host plants, compared to the control group [25,29,43,44,45,46]. These Bacillus species are known to produce numerous antibiotics, bacteriocins, siderophores, and hydrolytic enzymes, which help plants resist a wide range of pathogens [25,47].

In a study, tomato plants treated with Bacillus subtilis strain QST 713 had a considerably lower incidence and severity of bacterial speck disease than the control, with about 60% of the treated plants showing no symptoms [48]. In 2024, Sunyar et al. [49] investigated the biological control of common bacterial blight in beans and identified ten strains with antibacterial activity, forming inhibition zones of 1.60–2.66 cm against Xanthomonas citri subsp. fuscans. Among them, Bacillus subtilis strain BSU-37 achieved the highest disease control efficacy (83.43%), followed by B. velezensis BSU-26 (75%), B. amyloliquefaciens BSU-14 (59%), and B. pumilus BSU-22 (58.46%). Another work highlighted that str. QST 713 reduced disease severity by up to 60% of yellow rust induced by Puccinia striiformis f. sp. Tritici in winter wheat field trials [50]. Similarly, the present study aligns with previous reports, showing that Bst26 reduced disease incidence from 37.71% to 22.69% at 8, 15, and 21 days after inoculation (DAI) in bean cultivars, achieving disease control levels of 52.18-57.08%.

Lactobacillus plantarum, which is a common lactic acid bacterium (LAB) used in food preservation and probiotics, has shown strong potential against various plant pathogens [51,52,53,54]. LAB, including Lactobacillus plantarum, suppress plant diseases by producing organic acids, hydrogen peroxide, and reactive oxygen species (ROS), which lower pH, enhance antimicrobial activity, and inhibit pathogen growth [55,56,57]. Beyond their antagonistic effects, LAB enhance plant health by producing growth-promoting substances such as IAA and siderophores and by solubilizing phosphate, thereby strengthening host plants and improving resistance [56,57,58]. Various LAB strains have shown strong antagonistic activity against major bacterial pathogens, including Ralstonia solanacearum, Pseudomonas savastanoi, Xanthomonas campestris, Pseudomonas syringae, and Pectobacterium carotovorum, which significantly affect staple and cash crops [59,60,61].

A study by Shrestha et al. [60] reported that LAB strains KLF01, KLC02, and KPD03 suppressed R. solanacearum and P. carotovorum and also reduced bacterial spot (X. campestris pv. vesicatoria) on pepper, while some strains promoted plant growth through the production of indole-3-acetic acid (IAA), siderophores, and phosphate solubilization. Trias, R. et al. [61] evaluated LAB isolated from fruits and vegetables as biocontrol agents against Xanthomonas campestris, Erwinia carotovora, Monilinia laxa, and Botrytis cinerea, finding that several strains effectively inhibited pathogen growth and reduced postharvest rot in apples, mainly through the production of organic acids and, in some cases, hydrogen peroxide. Among 100 LAB strains tested in vitro against ten phytopathogens, Lactiplantibacillus plantarum KB2 LAB 03 showed the highest antimicrobial activity, with HPLC analysis revealing lactic acid, acetic acid, propionic acid, and ethanol as major metabolites. In situ tests on seed potatoes demonstrated a 40–90% reduction in infestation by eight pathogens, indicating that L. plantarum KB2 LAB 03 is a promising biocontrol agent for potato protection [57].

A study in 2019 reported that Lactobacillus plantarum strains CC100, PM411, and TC92 effectively controlled bacterial pathogens, including Xanthomonas arboricola pv. pruni in Prunus, X. fragariae in strawberry, and Pseudomonas syringae pv. actinidiae in kiwifruit, primarily via pH reduction and lactic acid production [62]. Furthermore, Lactobacillus plantarum has shown antifungal activity in laboratory and field experiments, reducing stem smut in rye and common bunt in wheat with disease control efficacy of 34.5–94.7% and 24.8–99.6%, respectively, while seed treatments also improved cereal yields without causing phytotoxicity [63]. Additionally, Lactiplantibacillus plantarum has been shown to suppress diseases caused by phytopathogens such as Pectobacterium carotovorum and Rhizoctonia solani, but was ineffective against Fusarium oxysporum and F. sambucinum in vivo [57]. Citrus green rot and Botrytis cinerea were also effectively suppressed when Lactiplantibacillus plantarum was applied as a biocontrol agent [64]. In another study, several lactic acid bacteria strains, including Lactobacillus plantarum LMG9211, were able to inhibit the growth of Erwinia amylovora and other bacterial pathogens, with strains TC54 and TC92 showing consistent disease suppression in leaf trials [65]. Consistent with these findings, our results demonstrate that Lactobacillus plantarum (Lpkb10) suppressed common bacterial blight in bean cultivars, reducing disease incidence from 58.96% to 27.11% at 8, 15, and 21 DAI and achieving disease control levels of 25.23–51.82% across Saltan, Göynük, and Tezgeldi varieties, highlighting its potential as a biocontrol agent.

Additionally, bio-organic fertilizers, PGPR, LAB, and inoculants have been used to enhance plant growth, improve soil quality, and increase resistance to pathogens, with a global adoption growth rate of about 10%, offering a safer alternative to chemical fertilizers and pesticides [66,67,68,69,70,71,72,73].

Several studies have evaluated the compatibility of bioagents with copper for bacterial disease management. Abbasi and Weselowski (2015) [74] reported reduced bacterial spot in tomato, while a 2021 study observed significant decreases in disease severity, incidence, and infection rate of common bacterial blight by 53% and 51.21%, respectively [30]. Similarly, this combination achieved about 87% control of citrus bacterial canker [75].

As suggested by previous studies, combining Bacillus strains with other chemicals or microbes can improve disease control and reduce both incidence and severity. Although the compatibility of BCAs with copper hydroxide has been proven, prolonged copper use poses environmental and ecological risks. Alternatively, integrating BCAs with other beneficial microbes can supply essential nutrients, promote plant growth, and offer a more sustainable and eco-friendly approach to disease management.

The combination of Bacillus and Pseudomonas strains is frequently cited in the literature; for instance, mixing B. subtilis QST713 and B. amyloliquefaciens MBI600 reduced fire blight severity to 33.97%, achieving 66.03% disease control [29]. Similarly, Gur A. et al. [28] assessed bioagents against soft rot in tomato caused by Pectobacterium carotovorum subsp. carotovorum, reporting disease control rates of 25.12%, 42.93%, and 72.60% with Pseudomonas fluorescens (Pf), B. subtilis (Bs), and B. amyloliquefaciens (Ba), respectively, while the combined application of Pf + Bs + Ba improved plant growth parameters such as height, root length, and dry root weight, with Pf alone producing the tallest plants (23.66 cm), followed by Ba (22.33 cm).

It is believed that mixing B. subtilis 26 with Lactobacillus plantarum Lpkb10 could have a synergistic effect, similar to observations that Pseudomonas fluorescens and B. subtilis act synergistically as biocontrol agents by producing siderophores and antibiotics, including 2,4-diacetylphloroglucinol and pyoluteorin from P. fluorescens, and surfactin, iturin, and fengycin from B. subtilis [25,28,76]. These works highlight that using multiple biological control agents in combination can enhance efficacy against serious plant diseases.

Our findings signify that the application of Bst26 consistently reduced disease incidence and severity across all bean cultivars. To our knowledge, this study represents the first evaluation in Turkey of the combined use of Bst26 and Lpkb10 against common bacterial blight in three bean cultivars. Both the Bst26 + Lpkb10 combination and Bst26 alone were significantly more effective than the other treatments, with DI values of 23.6–33.5% and 22.7–33.1% and AUDPC values of 307.63 and 516.85, respectively, in the Saltan variety. Their combination also provided moderate disease control in the Göynük and Tezgeldi cultivars, demonstrating the broad-spectrum potential of these biocontrol agents.

Based on the correlation patterns, there were consistent and strong interrelationships between disease parameters and growth traits across all bean varieties inoculated with Xanthomonas axonopodis pv. phaseoli. In each genotype, disease incidence, severity index, severity score, and AUDPC were strongly and positively correlated (r = 0.88–0.99), while all were perfectly and inversely related to disease control percentage (r = −1.00), confirming that effective treatments directly translated into higher control levels. Growth traits, including plant height, number of leaves, number of primary branches, root length, and fresh root weight, were generally positively associated with one another (r = 0.90–0.99) but negatively correlated with disease parameters (r = −0.79 to −0.99). This inverse relationship reveals that increased disease severity and incidence were consistently associated with reduced vegetative and root growth performance across varieties.

The PCA findings show a clear separation between disease parameters and growth traits across the three bean varieties inoculated with Xanthomonas axonopodis pv. phaseoli. In Göynük, disease parameters clustered tightly, with PC1 and PC2 explaining 99.2% and 0.5% of the variance, respectively, while growth traits grouped distinctly (PC1 = 75.3%, PC2 = 12.9%), suggesting consistent vegetative performance patterns. In Saltan, disease clustering was similarly strong (PC1 = 95.2%, PC2 = 4.5%), with growth traits also showing strong co-variation (PC1 = 69.2%, PC2 = 18.0%). In contrast, Tezgeldi demonstrated broader dispersion in growth traits (PC1 = 54.8%, PC2 = 37.4%) and a more variable disease–growth relationship, highlighting greater adaptability and morphological resilience under different treatments. These results prove that while Göynük and Saltan displayed more uniform responses, Tezgeldi may offer enhanced potential for breeding programs targeting both disease resistance and growth vigor.

Collectively, our findings underscore the significance of effective integrated disease management strategies combining biological control agents and sustainable practices to enhance common bacterial blight resistance and promote vigorous growth in bean varieties.

5. Conclusions

This study successfully demonstrated that Bacillus subtilis, particularly when applied alone or in combination with Lpkb10, effectively reduces the incidence and severity of common bacterial blight while enhancing key growth parameters in common beans. Among the tested cultivars, Bacillus subtilis (Bst26) alone provided the highest disease control, achieving 57.08% efficacy, whereas the Saltan variety responded best to the combined treatment with 56.62% control. Göynük and Tezgeldi showed greater improvement with Bst26 alone. The integration of different biological control agents presents a promising, eco-friendly approach for managing CBB, enhancing plant health, and promoting sustainable bean production. Further research should evaluate this integrated approach under field conditions, develop suitable formulations, and use molecular tools to better understand CBB dynamics, ultimately optimizing practical applications for sustainable and healthier bean production.