Snap Bean Plants' Physio-Biochemical Reactions to Plant Growth-Promoting Rhizobacteria to Mitigate the Negative Effects of Drought Stress

doi:10.21203/rs.3.rs-3401437/v1

Download PDF

Research Article

Snap Bean Plants' Physio-Biochemical Reactions to Plant Growth-Promoting Rhizobacteria to Mitigate the Negative Effects of Drought Stress

https://doi.org/10.21203/rs.3.rs-3401437/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Purpose

Drought is one of the main devastating abiotic stresses on sustainable agriculture and global food security. Enhancement of abiotic and biotic stress tolerance by plant growth–promoting rhizobacteria (PGPR) has been increasingly documented. However, PGPR have not been employed to manage drought stress in snap bean.

Methods

Therefore, the current study was conducted to assess the beneficial effects of Azospirillum brasilense, Bacillus megaterium, Rhizobium leguminosarum bv. phaseoli, and Pseudomonas fluorescens on snap bean plants cv. Valentino grown in sandy soil under three levels of irrigation (100, 80, and 60% of the estimated crop evapotranspiration) during the 2020 and 2021 seasons to alleviate the detrimental impacts of drought stress. The experimental design was a split plot with three replications. The irrigation water levels were randomly distributed in the main plots, while the PGPR and non-inoculation treatments were randomly dispersed in the subplots.

Results

The results showed that drought stress decreased plant growth parameters, leaf elemental content, SPAD readings, relative water content, membrane stability index, yield attributes, and water use efficiency and induced increases in proline content and superoxide dismutase, peroxidase, and catalase activities. PGPR application, particularly Bacillus megaterium, significantly enhanced all growth and yield parameters, improved nutrient content, SPAD readings, and relative water content, lowered membrane damage, and accumulated endogenous proline and antioxidant enzymes, causing drought-tolerance. Yield response factors of all PGPR were lower than those of the check plants, indicating their effectiveness in alleviating the detrimental impacts of drought stress.

Conclusion

In light of these findings, it could be concluded that the PGPR application, especially Bacillus megaterium, could be utilized as a low-cost and an environment-friendly effective strategy to mitigate the negative effects of drought stress on the growth and productivity of snap bean.

Phaseolus vulgaris

Water stress

Azospirillium

Bacillus

Rhizobium

Pseudomonas

Drought tolerance index

Yield response factor

PCA

By 2050, the world's population is projected to exceed 9 billion, necessitating the need for more productive agricultural systems that can provide a sustainable food supply in the face of impending climate change (Chaudhary et al. 2022). Food production has significant challenges worldwide due to rising water constraints, particularly in arid and semiarid regions (Ladeiro 2012), since drought is expected to affect about one-half of the cultivable lands by 2052 (Ramakrishna et al. 2019). Egypt is one of several nations with water shortage issues, which have recently gotten worse as a result of the country's rapid population growth and fixed water allocation from the Nile River (McCarl et al. 2015). Drought stress is a major driver of crop yield volatility and causes morphological, physiological, and biochemical changes in plants (Benaffari et al. 2022), leading to substantial financial losses (Bucheli et al. 2021) in all crops, including snap bean.

Snap bean (Phaseolus vulgaris L.) is a leguminous vegetable belonging to the Fabaceae family and is widely grown all over the world (Karavidas et al. 2022) due to its high contents of protein, carbohydrates, and minerals (Mehrasa et al. 2022). China, Indonesia, and India are the top producers of this crop, with a global annual production of 27 million tonnes and Egypt is ranked the world's seventh-largest producer since the cultivated area was 26028 ha with a total production of 264959 tonnes and an average yield of 10.18 tonnes ha^− 1 in 2020 (FAOSTAT 2022). Nonetheless, drought severely reduces snap bean production because snap bean is a drought-sensitive crop.

Under drought stress conditions, reduced plant growth and productivity are caused by altered plant water relations, decreased nutrient uptake (Chandra et al. 2021), and decreased CO₂ assimilation, resulting in an imbalance between electron excitation and utilization through photosynthesis, which results in the production of reactive oxygen species (ROS) that damage cell membranes, proteins, nucleic acids, and other important cellular components causing cellular oxidative stress (Bano et al. 2021; Sachdev et al. 2021). Plants exhibit osmotic adjustment by synthesizing and accumulating some osmolytes such as proline, soluble sugars, spermine, and glycine betaine to maintain the cell turgor pressure (Molinari et al. 2007; Seki et al. 2007; Pashang et al. 2021; Wahab et al. 2022). In addition, the plants possess enzymatic and non-enzymatic mechanisms to scavenge ROS and reduce cellular oxidative stress (Abid et al. 2016). To mitigate such harmful effects of drought and improve plant growth and productivity, many innovative, efficient, and smart farming technologies, including eco-friendly plant growth-promoting rhizobacteria (PGPR) may be exploited (Bargaz et al. 2018).

Plant growth-promoting rhizobacteria (PGPR) are the rhizospheric bacteria that influence positively plant growth and provide stress resistance by altering root morphology/architecture which promote water absorption and transport (Bouremani et al. 2023), favouring the absorption of nutrients via nitrogen fixation, phosphorus solubilizing and uptake of other micro and macronutrients such as potassium, iron, and zinc (Anli et al. 2020; de Andrade et al. 2023), regulating the stress responsive-genes (Ahmad et al. 2022), protecting the photosynthetic system and maintaining plant photosynthetic efficiency (Liu et al. 2019), producing phytohormones (Vasseur-Coronado et al. 2021), stimulating the oxygen radical scavenging by osmolytes (Ghosh et al. 2019) and antioxidant enzymes accumulation (Singh et al. 2020; Batool et al. 2020; Ashry et al. 2022), producing extracellular polymeric substance (EPS) (Ghosh et al. 2019), volatile organic compounds (VOCs) (Almeida et al. 2023), and siderophores (Ferreira et al. 2019; Qessaoui et al. 2019), and improving the 1-aminocyclopropane-1-carboxylate deaminase (ACC) activities (Danish et al. 2020a; b), quorum sensing (QS) signal interference induced systemic resistance (ISR) (Hartmann et al. 2021), and beneficial plant-microbe symbioses. By employing these mechanisms, PGPR make changes in the morphological, physiological, biochemical, and molecular levels in the plants and thus exerts its drought stress resistance attributes to maintain plant survival under these extreme conditions. It has been widely confirmed that inoculating plants with PGPR can improve drought resistance in various vegetable crops, such as pea (Saikia et al. 2018), tomato (Liu et al. 2023), potato (Batool et al. 2020), okra (Puthiyottil and Akkara 2021), spinach (Petrillo et al. 2022), and lettuce (Ouhaddou et al. 2023).

Thus, the current study was based on the hypothesis that the inoculation of snap bean plants with different rhizobacteria would enhance drought stress tolerance with different efficiencies. Based on the literature and to our knowledge, PGPR have not been employed to manage drought stress in snap bean. Therefore, this study was designed to investigate, for the first time, the beneficial effects of Azospirillum brasilense, Bacillus megaterium, Rhizobium leguminosarum bv. phaseoli, and Pseudomonas fluorescens and which one of them is the most effective in ameliorating the adverse effects of drought on the growth, yield, and quality of snap bean plants.

2.1 Experimental site and plant material

The experiment was conducted in the two seasons of 2020 and 2021 at the Experimental Farm of the Horticulture Department (30°06ʹ46ʺN, 31°14ʹ37ʺE), Faculty of Agriculture, Ain Shams University, Shoubra El Kheima, Qalyubiyah Governorate, Egypt. Seeds of snap bean (Phaseolus vulgaris L.) cv. Valentino (a bush bean of the fine-type group) were obtained from Sakata Company, imported via the Agriculture Research Center (ARC), Giza, Egypt. Seeds were sown on the 1st of September in both seasons in cement basins of 2 m². They were filled with washed sand soil. The physical properties of the soil were 89.4% sand, 6.9% silt, and 3.7% clay with a pH of 7.8, and an EC of 1.68 dS/m (averaged over 2 years). The experimental site has a prevailing arid climate with cool winters and hot dry summers. Seeds were sown in rows spaced 60 cm apart with the seed spaced 10 cm apart in the row.

All agricultural practices for snap bean production, fertilization, diseases, and pest control were followed according to the recommendations of the Egyptian Ministry of Agriculture. The meteorological parameters and ET_o of the experimental site are shown in Table 1.

Table 1

Means monthly of climatic parameters and reference evapotranspiration (ET_o) during snap been growth and development at Shoubra El Kheima region, Qalyubiyah Governorate, Egypt in 2020 and 20201 seasons.
Month	Air temperature (°C)				Relative humidity (%)		Wind speed (kmh^− 1)		ET_o (mm day^–1)
Month	Minimum		Maximum		Relative humidity (%)		Wind speed (kmh^− 1)		ET_o (mm day^–1)
	2020	2021	2020	2021	2020	2021	2020	2021	2020	2021
September	27.66	27	46.1	45	58.86	58.7	14.51	14.5	2.2	2.2
October	24.59	23.5	43.03	41	58.54	58.8	13.32	13.01	1.6	1.8
November	20.49	21	28.69	27	61.13	60.2	11.75	11.7	1.2	1.2
December	17.42	18	27.66	28	57.35	59.03	11.07	11.2	0.9	1.1
Data obtained from the nearest Metrological Station in Bahtim, Shoubra El Kheima, Qalyubiyah Governorate, Egypt.

2.2 Experimental layout

The experimental design was a split plot with three replications. The treatments included three irrigation water levels (100, 80, and 60% of the estimated crop evapotranspiration, ET_c), representing well–watered, moderately water–stressed, and severely water-stressed conditions, which were randomly distributed in the main plots. The amounts of irrigation water were calculated according to the following equation:

ET _c = ET_o× KC

Where, ET_c= crop evapotranspiration.

ET _o = reference evapotranspiration (mm/day).

KC = crop coefficient.

The FAO Penman-Monteith method was used to estimate reference evapotranspiration (ET_o). The reference evapotranspiration values were calculated by a class evaporation pan obtained from the nearest metrological station in Bahtim, Shoubra El Kheima, Qalyubiyah Governorate, Egypt. Crop coefficient is varying according to growth stage and also affected by the growth stage length and was calculated according to FAO56 approach (Allen et al. 1998).

Four microbial inoculants were obtained from the Unit of Bio-fertilizers, Faculty of Agriculture, Ain Shams University: Azospirillum brasilense, Bacillus megaterium, Rhizobium leguminosarum bv. phaseoli, and Pseudomonas fluorescens. The active strains of PGPB (108 CFU/ml) as well as the non-inoculation treatments were dispersed at random in the subplots, 5 ml of each microbial was injected around seedlings that were 7 days old and was repeated three times at 15-day intervals.

2.3 Data Recorded

2.3.1 Vegetative Growth Parameters

A random sample of three plants/replicate was collected 52 days after sowing to assess vegetative growth parameters, namely plant length, number of leaves per plant, leaf area, and fresh and dry weights of shoot and root systems. Shoot and root dry weights were estimated after oven drying at 70°C for 48 h. The fourth fully expanded mature leaf from the plant top of five plants was used to calculate the average leaf area. Leaf area was calculated as the relation between unit area and leaf dry weight using the following equation (Koller 1972):

Leaf area (cm ² )= \(\frac{\mathbf{D}\mathbf{i}\mathbf{s}\mathbf{k} \mathbf{a}\mathbf{r}\mathbf{e}\mathbf{a} \times \mathbf{N}\mathbf{o}. \mathbf{D}\mathbf{i}\mathbf{s}\mathbf{k} \mathbf{L}\mathbf{e}\mathbf{a}\mathbf{f} \mathbf{D}\mathbf{W}}{\mathbf{D}\mathbf{i}\mathbf{s}\mathbf{k} \mathbf{D}\mathbf{W}}\)

2.3.2 Determination of Leaf Mineral Content

Nitrogen, phosphorus, potassium, calcium, and magnesium were determined in the dry leaves. Total nitrogen in the plant was determined by the Kjeldahl method using 5% boric acid and 40% NaOH as described by Chapman and Pratt (1982). Phosphorus content was determined using a spectrophotometer according to Watanabe and Olsen (1965). Potassium, calcium, and magnesium contents were determined as described by Chapman and Pratt (1982).

2.3.3 PhysioBiochemical Parameters

All samples of leaves were taken from mature, fully expanded leaves on the fourth leaf from the plant apex and were collected 52 days after sowing to measure all physio-biochemical parameters.

SPAD Readings

A portable chlorophyll meter (SPAD-502; Konica Minolta Sensing, Inc., Japan) was used to measure the plants' leaf greenness. Each plant's measurements were obtained four times, twice on either side of the midrib on all fully developed leaves. The average of these measurements was then calculated (Khan et al. 2003).

Leaf Relative Water Content (LRWC)

To measure the relative water content (RWC) of the leaves, 10 leaf discs (2 cm in diameter) were weighed to obtain the fresh weight (FW). Leaves were immersed in distilled water for 24 hours inside a covered petri dish to determine the turgid weight (TW). The samples were subsequently oven dried (70°C for 48 h 72 h) to record their dry weight (DW). According to Kaya et al. (2003), the values were utilized to calculate RWC using the following equation:

RWC (%) = \(\frac{\mathbf{F}\mathbf{W}–\mathbf{D}\mathbf{W}}{\mathbf{T}\mathbf{W}–\mathbf{D}\mathbf{W}} \times 100\)

Leaf Membrane Stability Index (LMSI)

It was appraised following the methodology of Shi et al. (2006). Ten leaf discs (2 cm in diameter) were placed in 30 ml of distilled water and allowed to stand in the dark for 24 h at room temperature. The electrical conductivity of the bathing solution was determined at the end of the incubation period (EC1) using a digital EC meter (Spectrum Technologies Inc., USA). Vials were heated in a temperature-controlled water bath at 95°C for 20 min and then cooled to room temperature and the electrical conductivity was again measured (EC2). Leaf membrane stability index was calculated using the following equation:

Membrane Stability Index (MSI%) = \(\frac{\mathbf{E}\mathbf{C}1}{\mathbf{E}\mathbf{C}2} \times 100\)

Determination of Proline Content

Total free proline content was estimated using a modified method described by Khare et al. (2012). Fresh leaf samples (0.1 g) were homogenized in 0.5 ml of 3% (w/v) sulphosalicylic acid using a mortar and pestle. About 0.2 ml of each homogenate was mixed with 0.2 ml of glacial acetic acid to which 0.2 ml of ninhydrin was added. The reaction mixture was boiled in a water bath at 100°C for 30 min and immediately cooled in an ice bath. After cooling, 0.4 ml of toluene was added to the reaction mixture. After thorough mixing, the chromophore containing toluene was separated, and the absorbance of the red color developed was read at 520 nm against toluene blank on a UV–visible spectrophotometer (ChemitoSpectrascan, UV 2600). The concentration of proline was calculated from the formula:

Proline content (mg g ^− 1 FW) = \(\frac{\mathbf{C}\times 4\times \mathbf{v}\mathbf{o}\mathbf{l}. \mathbf{o}\mathbf{f} \mathbf{t}\mathbf{o}\mathbf{t}\mathbf{a}\mathbf{l} \mathbf{e}\mathbf{x}\mathbf{t}\mathbf{r}\mathbf{a}\mathbf{c}\mathbf{t}}{\mathbf{s}\mathbf{a}\mathbf{m}\mathbf{p}\mathbf{l}\mathbf{e} \mathbf{W}\mathbf{t}.\times \mathbf{v}\mathbf{o}\mathbf{l}. \mathbf{o}\mathbf{f} \mathbf{s}\mathbf{a}\mathbf{m}\mathbf{p}\mathbf{l}\mathbf{e}\times 1000}\)

Where: C=(absorbance-intercept)/slope (from a standard curve of L-proline).

Determination of Antioxidant Enzyme Activity

Superoxide Dismutase Activity (SOD)

The activity of superoxide dismutase (EC 1.15.1.1) was assayed according to the method of Beauchamp and Fridovich (1971) by estimating the ability of the enzyme to inhibit the photochemical reduction of nitro blue tetrazolium (NBT). A reaction mixture (3 ml) containing 50 mM potassium phosphate buffer (pH 7.8), 13 mM methionine, 75 µM NBT, 2 µM riboflavin, 0.1 mM EDTA and 100 µl of crude enzyme extract was shaken and placed 30 cm below a 15 W fluorescent lamp as a light source. At 560 nm, the absorbance was measured. One unit of SOD activity is the amount of protein required to inhibit 50% of the initial reduction of NBT under light. SOD activity was expressed as unit min^− 1 mg^− 1 protein.

Peroxidase Activity (POD)

The activity of peroxidase (EC 1.11.1.7) was assayed by the method of Hammerschmidt et al. (1982). The reaction mixture (2.9 ml) consisted of 0.25% (v/v) guaiacol in 10 mM sodium phosphate buffer (pH 6, containing 10 mM H₂O₂). A volume of 100µl of crude enzyme extract was added to initiate the reaction, which was measured spectrophotometrically at 470 nm per min. One international unit (IU) of enzyme activity was expressed as ΔOD = 0.01, and POX activity was expressed as unit min^− 1 mg^− 1 protein.

Catalase Activity (CAT)

The activity of catalase (EC 1.11.1.6) was estimated by the method of Montavon et al. (2007). Fresh tissues were homogenized in 50 mmol sodium phosphate buffer (pH 7.0, 1/10, w/v), including 150 mmol NaCl and 0.5 mmol EDTA. One unit of CAT activity was expressed as the amount of enzyme needed to reduce 1 µmol of H₂O₂ per min and was expressed as unit min^− 1 mg^− 1 protein.

2.3.4 Yield Parameter Measurements and Water Use Efficiency (WUE)

Green pods were harvested 60 days after sowing, and the total number of pods per plant, pod length, pod diameter, and pod yield were calculated. Water use efficiency (WUE) was expressed as pod yield per quantity of irrigation water, and it was computed according to Hoffman et al. (2007) as follows:

WUE = \(\frac{\mathbf{P}\mathbf{o}\mathbf{d} \mathbf{y}\mathbf{i}\mathbf{e}\mathbf{l}\mathbf{d} \left(\mathbf{g}\right)}{\mathbf{A}\mathbf{p}\mathbf{p}\mathbf{l}\mathbf{i}\mathbf{e}\mathbf{d} \mathbf{i}\mathbf{r}\mathbf{r}\mathbf{i}\mathbf{g}\mathbf{a}\mathbf{t}\mathbf{i}\mathbf{o}\mathbf{n} \mathbf{w}\mathbf{a}\mathbf{t}\mathbf{e}\left(\varvec{l}\right)}\left(\frac{\varvec{g}}{\varvec{l}}\right)\)

2.3.5 Yield Response Factor (Ky)

The yield response factor (Ky), defined as a decrease in yield with respect to per unit decrease in ET, was computed from the fruit yield for each PGPR treatment using the pooled data across the two experimental years (Doorenbos and Kassam 1979), using the following equation:

(1 - \(\frac{\varvec{Y}\varvec{a}}{\varvec{Y}\varvec{m}}\)) = Ky (1 - \(\frac{\varvec{E}\varvec{T}\varvec{a}}{\varvec{E}\varvec{T}\varvec{m}}\))

where Ya and Ym are the fruit yields (kg ha^–1) obtained from deficit and full irrigation treatments, respectively, 1 − (Ya/Ym) is the decrease in relative yield, ETa and ETm are the crop water consumptions (m³ ha^–1) under deficit and full irrigations, respectively, and 1 − (ETa/ETm) is the decrease in relative crop water consumption.

2.3.6 Drought Tolerance Index (DTI)

Drought tolerance index (DTI) was estimated for each of the studied parameters (Sbei et al. 2014) as follows:

DTI =\(\frac{Trait under drought stress}{Trait under \text{w}\text{e}\text{l}\text{l}-\text{w}\text{a}\text{t}\text{e}\text{r}\text{e}\text{d} \text{c}\text{o}\text{n}\text{d}\text{i}\text{t}\text{i}\text{o}\text{n}\text{s}}\) X 100

2.4 Statistical Analysis

The treatment effects were evaluated by analysis of variance. The mean values were compared using Duncan’s multiple range test at P ≤ 5% to determine the differences among treatment means, according to Gomez and Gomez (1984), using the CoStat package program for Windows (version 6.303; CoHort Software, USA). Principal component analysis (PCA) was also performed using the JMP Pro software.

The experiment was conducted to investigate the effects of PGPR on the morphological, physiological, and biochemical traits of snap bean plants under water deficit. The experiment showed the following results:

3.1 Vegetative Growth Parameters

Drought stress had detrimental effects on all recorded vegetative growth parameters (plant length, leaf number per plant, leaf area, and fresh and dry weights of shoot and root systems), which steeply decreased, particularly under severe drought conditions in the two tested seasons (Tables 2 and 3). Notwithstanding, the results demonstrated that PGPR inoculants significantly increased all recorded growth parameters compared with the check plants in both growing seasons. Bacillus megaterium application significantly increased all these parameters and was more effective in attenuating the negative effect of severe water deficiency on vegetative growth characteristics in both seasons.

Table 2

Effect of plant growth promoting rhizobacteria (PGPR) applications on some vegetative growth parameters of green beans cv. Valentino under different irrigation levels in 2020 and 2021 growing seasons.
Treatments		Plant length (cm)		Number of leaves/plant		Leaf area (cm²)
Treatments		1st season	2nd season	1st season	2nd season	1st season	2nd season
Water requirements (WR)^*
WR_100%		53.20 ± 1.01 a	59.80 ± 0.86 a	10.13 ± 0.17 a	19.20 ± 0.46 a	64.91 ± 2.36 a	65.91 ± 4.04 a
WR_80%		43.40 ± 0.38 b	54.00 ± 0.24 b	8.13 ± 0.13 b	15.26 ± 0.24 b	44.25 ± 1.37 b	40.72 ± 1.03 b
WR_60%		35.07 ± 0.52 c	47.00 ± 1.83 c	6.47 ± 0.17 c	11.40 ± 0.34 c	28.52 ± 1.49 c	26.56 ± 1.49 c
Plant growth promoting rhizobacteria (PGPR)
Without PGPR		40.22 ± 2.17 d	48.22 ± 3.49 c	7.56 ± 0.56 c	13.56 ± 1.07 e	36.87 ± 5.00 d	33.81 ± 4.61 e
Azospirillium brazilense		44.44 ± 3.09 b	54.00 ± 2.11 b	8.22 ± 0.49 b	15.11 ± 1.16 c	49.75 ± 5.85 a	49.63 ± 7.49 b
Bacillus megaterium		46.89 ± 2.99 a	57.56 ± 1.99 a	8.67 ± 0.60 a	17.11 ± 1.29 a	50.86 ± 6.73 a	52.45 ± 8.67 a
Rhizobium leguminosarum		43.78 ± 2.28 c	53.89 ± 0.99 b	8.00 ± 0.58 b	14.54 ± 1.01 d	44.35 ± 4.78 c	41.04 ± 4.29 d
Pseudomonas fluorescens		44.11 ± 2.70 bc	54.33 ± 1.40 b	8.78 ± 0.49 a	16.11 ± 1.16 b	47.64 ± 4.88 b	45.04 ± 50 c
WR x PGPR interactions
WR_100%	Without PGPR	47.00 ± 0.58 e	56.00 ± 0.01 cde	9.33 ± 0.33 c	17.00 ± 0.01 e	53.95 ± 0.52 e	48.66 ± 1.41 e
	A. brazilense	55.33 ± 0.33 b	60.67 ± 0.33 b	10.00 ± 0.01 b	19.00 ± 0.01 c	71.61 ± 2.52 b	78.32 ± 4.56 b
	B. megaterium	58.00 ± 1.00 a	65.33 ± 0.33 a	11.00 ± 0.01 a	22.00 ± 0.01 a	77.59 ± 0.36 a	86.99 ± 0.59 a
	R. leguminosarum	52.00 ± 0.58 d	57.67 ± 0.33 bcd	10.00 ± 0.01 b	18.00 ± 0.01 d	58.39 ± 0.99 d	53.89 ± 1.18 d
	P. fluorescens	53.67 ± 0.33 c	59.33 ± 0.33 bc	10.33 ± 0.33 b	20.00 ± 0.01 b	62.99 ± 0.68 c	61.69 ± 4.25 c
WR_80%	Without PGPR	41.33 ± 0.88 h	53.00 ± 0.01 efg	7.67 ± 0.33 d	14.00 ± 0.01 i	36.95 ± 0.51 i	35.42 ± 0.47 ij
	A. brazilense	44.00 ± 0.01 fg	55.00 ± 0.01 def	8.00 ± 0.01 d	15.33 ± 0.33 g	45.46 ± 0.73 g	41.09 ± 0.86 gh
	B. megaterium	45.00 ± 0.58 f	55.00 ± 0.01 def	8.00 ± 0.01 d	16.00 ± 0.01 f	39.99 ± 0.34 h	37.53 ± 0.14 hi
	R. leguminosarum	43.00 ± 0.01 g	53.00 ± 0.01 efg	8.00 ± 0.01 d	14.62 ± 0.06 h	48.48 ± 0.83 f	44.27 ± 0.23 fg
	P. fluorescens	43.67 ± 0.33 g	54.00 ± 0.01 def	9.00 ± 0.01 c	16.33 ± 0.33 f	50.36 ± 0.19 f	45.30 ± 0.12 ef
WR_60%	Without PGPR	32.33 ± 0.67 l	35.67 ± 5.04 i	5.67 ± 0.33 f	9.67 ± 0.33 m	19.71 ± 2.53 m	17.35 ± 2.35 n
	A. brazilense	34.00 ± 0.58 k	46.33 ± 1.20 h	6.67 ± 0.33 e	11.00 ± 0.01 l	32.17 ± 0.72 j	29.49 ± 0.08 kl
	B. megaterium	37.67 ± 0.33 i	52.33 ± 0.33 efg	7.00 ± 0.01 e	13.33 ± 0.33 j	35.00 ± 0.64 i	32.84 ± 1.00 jk
	R. leguminosarum	36.33 ± 0.33 j	51.00 ± 0.00 fg	6.00 ± 0.01 f	11.00 ± 0.01 l	26.18 ± 0.32 l	24.96 ± 1.41 m
	P. fluorescens	35.00 ± 0.01 k	49.67 ± 0.33 gh	7.00 ± 0.01 e	12.00 ± 0.01 k	29.56 ± 0.90 k	28.14 ± 0.59 lm
Each value is a mean of 3 replicates ± standard error. Means into every group within a column for the same factor followed by the same letter are not significantly different (P ≤ 0.05) according to Duncan’s multiple range test. ^* WR_100%, WR_80% and WR_60% are water requirements at 100, 80, and 60% of the estimated crop evapotranspiration, respectively.

Table 3

Effect of plant growth promoting rhizobacteria (PGPR) applications on shoot and root weights of green beans cv. Valentino under different irrigation levels in 2020 and 2021 growing seasons.
Treatments		Shoot fresh weight (g)		Root fresh weight (g)		Shoot dry weight (g)		Root dry weight (g)
Treatments		1st season	2nd season	1st season	2nd season	1st season	2nd season	1st season	2nd season
Water requirements (WR) ^*
WR_100%		60.43 ± 1.89 a	63.39 ± 2.10 a	3.21 ± 0.17 a	4.61 ± 0.15 a	8.61 ± 0.51 a	12.53 ± 0.03 a	0.29 ± 0.03 a	0.39 ± 0.01 a
WR_80%		46.00 ± 0.87 b	48.13 ± 0.78 b	2.09 ± 0.07 b	3.14 ± 0.10 b	5.79 ± 0.09 b	10.55 ± 0.11 b	0.18 ± 0.01 b	0.27 ± 0.01 b
WR_60%		32.80 ± 1.67 c	38.87 ± 1.50 c	1.43 ± 0.04 c	2.15 ± 0.06 c	4.76 ± 0.11 c	8.84 ± 0.16 c	0.12 ± 0.01 b	0.18 ± 0.01 c
Plant growth promoting rhizobacteria (PGPR)
Without PGPR		38.89 ± 4.70 d	43.58 ± 3.77 d	1.87 ± 0.22 c	2.81 ± 0.32 e	5.31 ± 0.34 d	9.94 ± 0.49 e	0.16 ± 0.02 b	0.24 ± 0.03 e
Azospirillium brazilense		45.78 ± 3.66 c	49.14 ± 3.45 c	2.20 ± 0.24 b	3.29 ± 0.36 c	6.37 ± 0.61 b	10.51 ± 0.54 c	0.19 ± 0.02 b	0.28 ± 0.03 c
Bacillus megaterium		53.50 ± 4.49 a	57.25 ± 4.52 a	2.80 ± 0.41 a	3.87 ± 0.44 a	7.70 ± 1.05 a	11.65 ± 0.62 a	0.27 ± 0.06 a	0.33 ± 0.04 a
Rhizobium leguminosarum		45.00 ± 2.89 c	48.37 ± 2.21 c	2.10 ± 0.18 b	3.15 ± 0.27 d	5.96 ± 0.33 c	10.35 ± 0.41 d	0.18 ± 0.02 b	0.27 ± 0.02 d
Pseudomonas fluorescens		48.89 ± 4.70 b	52.30 ± 4.57 b	2.25 ± 0.28 c	3.38 ± 0.41 b	6.59 ± 0.62 b	10.75 ± 0.66 b	0.19 ± 0.02 b	0.29 ± 0.04 b
WR x PGPR interactions
WR_100%	Without PGPR	53.33 ± 1.67 d	54.59 ± 0.63 de	2.67 ± 0.04 de	4.01 ± 0.06 e	6.49 ± 0.14 d	11.45 ± 0.12 e	0.23 ± 0.01 bcde	0.34 ± 0.01 e
	A. brazilense	56.67 ± 1.67 c	60.70 ± 1.78 c	2.99 ± 0.03 c	4.48 ± 0.04 c	8.63 ± 0.09 b	12.20 ± 0.07 c	0.25 ± 0.01 bc	0.38 ± 0.00 c
	B. megaterium	70.50 ± 0.29 a	74.56 ± 0.22 a	4.31 ± 0.38 a	5.46 ± 0.07 a	11.70 ± 0.96 a	13.98 ± 0.03 a	0.45 ± 0.14 a	0.47 ± 0.01 a
	R. leguminosarum	55.00 ± 0.01 cd	57.03 ± 0.60 d	2.78 ± 0.01 cd	4.18 ± 0.01 d	7.24 ± 0.20 c	11.89 ± 0.03 d	0.24 ± 0.01 bcd	0.36 ± 0.01 d
	P. fluorescens	66.67 ± 1.67 b	70.05 ± 1.87 b	3.29 ± 0.12 b	4.93 ± 0.18 b	9.01 ± 0.13 b	13.14 ± 0.30 b	0.28 ± 0.01 b	0.42 ± 0.02 b
WR_80%	Without PGPR	41.67 ± 1.67 g	46.03 ± 0.11 gh	1.73 ± 0.05 ij	2.60 ± 0.07 i	5.27 ± 0.06 fg	10.26 ± 0.04 hi	0.15 ± 0.01 cde	0.22 ± 0.01 j
	A. brazilense	48.33 ± 1.67 e	49.53 ± 0.81 f	2.25 ± 0.08 fg	3.37 ± 0.12 g	6.05 ± 0.01 de	10.78 ± 0.10 g	0.19 ± 0.01 bcde	0.29 ± 0.01 g
	B. megaterium	50.00 ± 0.01 e	53.03 ± 0.60 e	2.47 ± 0.04 ef	3.71 ± 0.06 f	6.21 ± 0.02 de	11.17 ± 0.05 f	0.21 ± 0.01 bcde	0.32 ± 0.01 f
	R. leguminosarum	45.00 ± 0.01 f	45.33 ± 0.24 gh	1.96 ± 0.03 hi	2.95 ± 0.04 h	5.57 ± 0.06 efg	10.05 ± 0.03 i	0.17 ± 0.01 bcde	0.25 ± 0.01 i
	P. fluorescens	45.00 ± 0.01 f	46.71 ± 0.05 fg	2.04 ± 0.03 gh	3.07 ± 0.04 h	5.86 ± 0.09 def	10.48 ± 0.05 h	0.17 ± 0.01 bcde	0.26 ± 0.01 h
WR_60%	Without PGPR	21.67 ± 1.67 i	30.11 ± 3.95 k	1.20 ± 0.03 l	1.80 ± 0.05 l	4.17 ± 0.03 i	8.13 ± 0.12 m	0.10 ± 0.01 e	0.15 ± 0.00 m
	A. brazilense	32.33 ± 1.45 h	37.20 ± 0.78 j	1.35 ± 0.03 kl	2.03 ± 0.04 k	4.44 ± 0.11 hi	8.53 ± 0.01 l	0.11 ± 0.01 e	0.17 ± 0.01 l
	B. megaterium	40.00 ± 0.01 g	44.15 ± 0.24 gh	1.63 ± 0.01 jk	2.44 ± 0.01 j	5.19 ± 0.01 fg	9.81 ± 0.13 j	0.14 ± 0.01 cde	0.21 ± 0.01 j
	R. leguminosarum	35.00 ± 0.01 h	42.76 ± 0.66 hi	1.56 ± 0.04 jk	2.33 ± 0.06 j	5.07 ± 0.03 gh	9.11 ± 0.05 k	0.13 ± 0.01 cde	0.20 ± 0.01 k
	P. fluorescens	35.00 ± 0.01 h	40.13 ± 0.30 ij	1.43 ± 0.02 kl	2.15 ± 0.03 k	4.91 ± 0.07 gh	8.63 ± 0.04 l	0.12 ± 0.01 de	0.18 ± 0.01 l
Each value is a mean of 3 replicates ± standard error. Means into every group within a column for the same factor followed by the same letter are not significantly different (P ≤ 0.05) according to Duncan’s multiple range test. ^* WR_100%, WR_80% and WR_60% are water requirements at 100, 80, and 60% of the estimated crop evapotranspiration, respectively.

3.2 Leaf Mineral Content

Data in Table 4 reveal that increasing water stress resulted in significant reductions in N, P, K, Ca, and Mg contents in both growing seasons. However, PGPR application significantly enhanced N, P, K, Ca, and Mg contents compared with the check plants in both tested seasons. As for the PGPR, application of Bacillus megaterium resulted in significant increases in N, P, Ca, and Mg contents, while Bacillus megaterium or Pseudomonas fluorescens gave the highest significant values of K. Concerning the interaction between PGPR and water levels, Bacillus megaterium significantly increased all elemental contents under well-watered conditions. Under moderate water level, P. fluorescens gave the highest N, Ca, and Mg contents compared to its respective control. P. fluorescens gave the highest N and P contents, while Bacillus megaterium gave the highest contents of K, Ca, and Mg under severe water conditions.

Table 4

Effect of plant growth promoting rhizobacteria (PGPR) applications on leaf nutrients of green beans cv. Valentino under different irrigation levels in 2020 and 2021 growing seasons.
Treatments		Nitrogen (%)		Phosphorus (%)		Potassium (%)		Calcium (%)		Magnesium (%)
Treatments		1st season	2nd season	1st season	2nd season	1st season	2nd season	1st season	2nd season	1st season	2nd season
Water requirements (WR) ^*
WR_100%		1.68 ± 0.02 a	1.54 ± 0.01 a	0.33 ± 0.01 a	0.23 ± 0.01 a	4.97 ± 0.05 a	4.14 ± 0.04 a	1.92 ± 0.04 a	2.3 ± 0.04 a	0.44 ± 0.02 a	0.53 ± 0.03 a
WR_80%		1.51 ± 0.01 b	1.37 ± 0.01 b	0.25 ± 0.00 b	0.18 ± 0.01 b	4.39 ± 0.04 b	3.66 ± 0.04 b	1.69 ± 0.01 b	2.03 ± 0.02 b	0.31 ± 0.01 b	0.37 ± 0.01 b
WR_60%		1.34 ± 0.02 c	1.21 ± 0.02 c	0.16 ± 0.01 c	0.11 ± 0.01 c	3.15 ± 0.28 c	2.74 ± 0.18 c	1.44 ± 0.03 c	1.73 ± 0.04 c	0.23 ± 0.01 c	0.27 ± 0.01 c
Plant growth promoting rhizobacteria (PGPR)
Without PGPR		1.43 ± 0.06 d	1.30 ± 0.05 c	0.19 ± 0.03 d	0.13 ± 0.02 d	3.32 ± 0.54 d	2.95 ± 0.36 d	1.56 ± 0.08 d	1.87 ± 0.10 d	0.26 ± 0.03 d	0.31 ± 0.03 d
Azospirillium brazilense		1.52 ± 0.06 b	1.38 ± 0.06 b	0.25 ± 0.03 c	0.17 ± 0.02 c	4.21 ± 0.32 c	3.51 ± 0.27 c	1.66 ± 0.08 c	2.00 ± 0.10 c	0.35 ± 0.04 b	0.42 ± 0.05 b
Bacillus megaterium		1.57 ± 0.06 a	1.40 ± 0.05 a	0.28 ± 0.04 a	0.20 ± 0.03 a	4.50 ± 0.18 a	3.74 ± 0.14 a	1.80 ± 0.09 a	2.15 ± 0.11 a	0.37 ± 0.05 a	0.44 ± 0.06 a
Rhizobium leguminosarum		1.49 ± 0.04 c	1.37 ± 0.05 b	0.25 ± 0.02 c	0.18 ± 0.01 c	4.31 ± 0.18 b	3.59 ± 0.15 b	1.66 ± 0.06 c	2.00 ± 0.07 c	0.31 ± 0.02 c	0.37 ± 0.03 c
Pseudomonas fluorescens		1.53 ± 0.04 b	1.40 ± 0.04 a	0.26 ± 0.01 b	0.18 ± 0.01 b	4.51 ± 0.16 a	3.76 ± 0.13 a	1.73 ± 0.05 b	2.07 ± 0.06 b	0.34 ± 0.02 b	0.40 ± 0.03 b
WR x PGPR interactions
WR_100%	Without PGPR	1.61 ± 0.01 d	1.48 ± 0.03 d	0.28 ± 0.01 d	0.20 ± 0.01 d	4.64 ± 0.02 d	3.86 ± 0.01 d	1.81 ± 0.01 cd	2.17 ± 0.01 cd	0.33 ± 0.02 e	0.40 ± 0.02 e
	A. brazilense	1.71 ± 0.04 b	1.57 ± 0.01 ab	0.33 ± 0.01 b	0.23 ± 0.01 b	5.14 ± 0.01 a	4.29 ± 0.01 a	1.90 ± 0.01 b	2.32 ± 0.05 b	0.49 ± 0.02 b	0.59 ± 0.03 b
	B. megaterium	1.81 ± 0.01 a	1.59 ± 0.01 a	0.42 ± 0.02 a	0.29 ± 0.01 a	5.19 ± 0.02 a	4.31 ± 0.01 a	2.17 ± 0.08 a	2.56 ± 0.14 a	0.56 ± 0.02 a	0.67 ± 0.03 a
	R. leguminosarum	1.63 ± 0.01 cd	1.53 ± 0.01 c	0.30 ± 0.01 c	0.21 ± 0.01 c	4.87 ± 0.05 c	4.06 ± 0.04 c	1.83 ± 0.01 cd	2.19 ± 0.01 cd	0.39 ± 0.01 d	0.47 ± 0.02 d
	P. fluorescens	1.65 ± 0.01 c	1.54 ± 0.01 bc	0.31 ± 0.01 c	0.22 ± 0.01 c	5.00 ± 0.02 b	4.17 ± 0.01 b	1.87 ± 0.01 bc	2.24 ± 0.01 bc	0.42 ± 0.02 c	0.51 ± 0.03 c
WR_80%	Without PGPR	1.46 ± 0.01 fg	1.32 ± 0.01 h	0.23 ± 0.01 g	0.16 ± 0.01 h	4.15 ± 0.03 h	3.46 ± 0.03 g	1.63 ± 0.01 gh	1.95 ± 0.01 fgh	0.28 ± 0.01 g	0.33 ± 0.01 g
	A. brazilense	1.54 ± 0.01 e	1.39 ± 0.01 ef	0.26 ± 0.01 e	0.18 ± 0.01 f	4.50 ± 0.02 e	3.75 ± 0.02 e	1.71 ± 0.01 ef	2.06 ± 0.01 ef	0.32 ± 0.01 ef	0.39 ± 0.01 ef
	B. megaterium	1.48 ± 0.01 f	1.35 ± 0.01 g	0.24 ± 0.01 f	0.17 ± 0.01 g	4.28 ± 0.02 g	3.57 ± 0.02 f	1.65 ± 0.01 fgh	1.98 ± 0.01 fg	0.30 ± 0.01 fg	0.36 ± 0.02 fg
	R. leguminosarum	1.49 ± 0.01 f	1.37 ± 0.01 fg	0.26 ± 0.01 e	0.18 ± 0.01 ef	4.41 ± 0.05 f	3.68 ± 0.04 e	1.69 ± 0.01 fg	2.03 ± 0.01 ef	0.30 ± 0.01 fg	0.36 ± 0.02 fg
	P. fluorescens	1.57 ± 0.01 e	1.41 ± 0.01 e	0.27 ± 0.01 e	0.19 ± 0.01 e	4.61 ± 0.01 d	3.84 ± 0.01 d	1.77 ± 0.01 de	2.13 ± 0.01 de	0.33 ± 0.02 e	0.40 ± 0.01 e
WR_60%	Without PGPR	1.23 ± 0.03 j	1.11 ± 0.02 l	0.06 ± 0.01 k	0.04 ± 0.01 m	1.16 ± 0.04 m	1.53 ± 0.03 l	1.25 ± 0.04 l	1.49 ± 0.05 k	0.16 ± 0.01 i	0.20 ± 0.01 i
	A. brazilense	1.32 ± 0.01 i	1.18 ± 0.01 k	0.15 ± 0.01 j	0.11 ± 0.01	2.99 ± 0.11 l	2.49 ± 0.09 k	1.37 ± 0.02 k	1.64 ± 0.03 j	0.23 ± 0.01 h	0.27 ± 0.01 h
	B. megaterium	1.43 ± 0.01 g	1.28 ± 0.01 i	0.17 ± 0.01 i	0.12 ± 0.01 k	4.03 ± 0.02 i	3.36 ± 0.01 h	1.59 ± 0.02 hi	1.91 ± 0.02 gh	0.25 ± 0.02 h	0.30 ± 0.01 h
	R. leguminosarum	1.34 ± 0.01 i	1.21 ± 0.01 j	0.19 ± 0.01 h	0.13 ± 0.01 j	3.65 ± 0.07 k	3.04 ± 0.06 j	1.45 ± 0.03 j	1.74 ± 0.03 i	0.24 ± 0.01 h	0.29 ± 0.01 h
	P. fluorescens	1.38 ± 0.01 h	1.26 ± 0.01 i	0.21 ± 0.01 g	0.15 ± 00.1 i	3.92 ± 0.04 j	3.27 ± 0.03 i	1.54 ± 0.01 i	1.85 ± 0.01 h	0.25 ± 0.01 h	0.30 ± 0.01 h
Each value is a mean of 3 replicates ± standard error. Means into every group within a column for the same factor followed by the same letter are not significantly different (P ≤ 0.05) according to Duncan’s multiple range test. ^* WR_100%, WR_80% and WR_60% are water requirements at 100, 80, and 60% of the estimated crop evapotranspiration, respectively.

3.3 SPAD Readings

Data in Table 5 point out that drought stress had a significant negative effect on SPAD readings compared with those in well-watered conditions in both seasons. The effect was more pronounced under severe drought conditions (60% ET_c) than under moderate drought conditions (80% ET_c). Nevertheless, PGPR inoculation treatments positively minimized the harmful effects of drought stress and generated a stimulatory effect on SPAD readings when compared to the uninoculated plants. Inoculation with B. megaterium was more effective in comparison with the other rhizobacteria used. Compared with the respective controls, application of B. megaterium significantly enhanced SPAD readings under well-watered and severely watered conditions, while either R. leguminosarum or Pseudomonas fluorescens inoculation had the highest significant SPAD readings under moderate water level in both seasons.

Table 5

Effect of plant growth promoting rhizobacteria (PGPR) applications on SPAD readings, leaf relative water content and leaf membrane stability of green beans cv. Valentino under different irrigation levels in 2020 and 2021 growing seasons.
Treatments		SPAD readings		Leaf relative water content (%)		Leaf membrane stability (%)
Treatments		1st season	2nd season	1st season	2nd season	1st season	2nd season
Water requirements (WR) ^*
WR_100%		44.83 ± 0.39 a	45.83 ± 0.53 a	65.44 ± 1.16 a	72.71 ± 1.29 a	86.43 ± 1.92 a	80.63 ± 1.19 a
WR_80%		41.07 ± 0.29 b	41.10 ± 0.24 b	58.49 ± 0.23 b	64.98 ± 0.26 b	73.11 ± 0.45 b	73.84 ± 0.45 b
WR_60%		35.54 ± 0.67 c	37.75 ± 0.42 c	48.86 ± 1.53 c	54.29 ± 1.70 c	59.76 ± 3.48 c	62.99 ± 2.39 c
Plant growth promoting rhizobacteria (PGPR)
Without PGPR		38.10 ± 1.72 d	39.41 ± 1.21 d	52.58 ± 3.20 e	58.42 ± 3.55 e	61.41 ± 6.8 e	65.14 ± 4.65 d
Azospirillium brazilense		41.30 ± 1.14 b	42.26 ± 1.25 b	59.33 ± 1.93 b	65.92 ± 2.14 b	77.54 ± 3.78 b	74.64 ± 1.91 b
Bacillus megaterium		41.90 ± 1.33 a	42.87 ± 1.52 a	62.23 ± 2.73 a	69.15 ± 3.03 a	79.61 ± 4.39 a	77.32 ± 2.87 a
Rhizobium leguminosarum		39.96 ± 1.52 c	41.33 ± 1.03 c	55.78 ± 2.64 d	61.98 ± 2.93 d	72.03 ± 2.94 d	71.33 ± 2.63 c
Pseudomonas fluorescens		41.13 ± 1.27 b	41.92 ± 1.05 b	58.05 ± 2.18 c	64.50 ± 2.43 c	74.92 ± 2.63 c	74.00 ± 1.81 b
WR x PGPR interactions
WR_100%	Without PGPR	43.17 ± 0.17 c	43.20 ± 0.26 d	60.46 ± 0.20 e	67.18 ± 0.22 e	78.41 ± 0.32 d	76.34 ± 0.29 cd
	A. brazilense	45.37 ± 0.22 b	46.97 ± 0.26 b	66.32 ± 0.59 b	73.69 ± 0.66 b	92.15 ± 1.48 b	81.50 ± 0.85 b
	B. megaterium	47.03 ± 0.78 a	48.90 ± 0.55 a	73.01 ± 0.77 a	81.12 ± 0.85 a	97.08 ± 0.92 a	88.46 ± 1.73 a
	R. leguminosarum	43.77 ± 0.12 c	44.77 ± 0.15 c	62.73 ± 0.70 d	69.70 ± 0.78 d	80.81 ± 0.83 d	77.68 ± 0.29 bcd
	P. fluorescens	44.80 ± 0.21 b	45.30 ± 0.06 c	64.66 ± 0.32 c	71.85 ± 0.36 c	83.71 ± 0.34 c	79.17 ± 0.43 bc
WR_80%	Without PGPR	39.57 ± 0.35 g	39.87 ± 0.09 gh	57.21 ± 0.04 i	63.57 ± 0.04 i	70.88 ± 0.15 gh	71.00 ± 0.22 efg
	A. brazilense	41.00 ± 0.26 e	41.30 ± 0.12 f	58.49 ± 0.08 gh	64.99 ± 0.09 gh	73.11 ± 0.12 efg	73.97 ± 0.26 def
	B. megaterium	40.33 ± 0.07 f	40.37 ± 0.09 g	58.06 ± 0.24 hi	64.51 ± 0.27 hi	71.87 ± 0.22 fgh	73.37 ± 0.03 def
	R. leguminosarum	42.10 ± 0.10 d	41.60 ± 0.06 ef	59.03 ± 0.17 fg	65.59 ± 0.19 fg	74.26 ± 0.21 ef	75.11 ± 0.11 cde
	P. fluorescens	42.33 ± 0.09 d	42.37 ± 0.18 e	59.64 ± 0.19 ef	66.27 ± 0.21 ef	75.44 ± 0.45 e	75.77 ± 0.05 cd
WR_60%	Without PGPR	31.57 ± 0.50 l	35.17 ± 1.09 j	40.07 ± 1.58 n	44.53 ± 1.76 n	34.95 ± 3.99 l	48.08 ± 5.87 i
	A. brazilense	37.53 ± 0.18 i	38.50 ± 0.10 i	53.17 ± 0.78 k	59.08 ± 0.87 k	67.37 ± 0.68 ij	68.44 ± 0.26 g
	B. megaterium	38.33 ± 0.03 h	39.33 ± 0.09 h	55.64 ± 0.53 j	61.82 ± 0.59 j	69.87 ± 0.23 hi	70.14 ± 0.29 fg
	R. leguminosarum	34.00 ± 0.47 k	37.63 ± 0.09 i	45.57 ± 1.13 m	50.64 ± 1.25 m	61.01 ± 1.11 k	61.21 ± 2.08 h
	P. fluorescens	36.27 ± 0.38 j	38.10 ± 0.06 i	49.86 ± 0.62 l	55.40 ± 0.69 l	65.60 ± 0.45 j	67.06 ± 0.40 g
Each value is a mean of 3 replicates ± standard error. Means into every group within a column for the same factor followed by the same letter are not significantly different (P ≤ 0.05) according to Duncan’s multiple range test. ^* WR_100%, WR_80% and WR_60% are water requirements at 100, 80, and 60% of the estimated crop evapotranspiration, respectively.

3.4 Relative Water Content (RWC) and Membrane Stability Index (MSI)

Leaf relative water content and membrane stability index significantly decreased by increasing drought stress and recorded the lowest values under severe drought stress in both studied seasons (Table 5). PGPR inoculation resulted in significant enhancements in LRWC and LMSI compared with non-treated plants. The application of Bacillus megaterium significantly improved LRWC and LMSI compared with other PGPR treatments. Either R. leguminosarum or Pseudomonas fluorescens significantly gave the highest values of LRWC and LMSI at 80% ET_c, while the application of B. megaterium significantly enhanced LRWC and reduced the damaging effect of drought on LMSI under severe water stress.

3.5 Proline Content

Water deficit levels (80 and 60% ET_c) resulted in significant accumulations of proline compared with the well-watered plants in both seasons (Fig. 1a). Severe water stress caused the highest significant accumulations. Additionally, PGPR inoculation significantly increased proline accumulation in comparison with the non-treated plants. Pseudomonas fluorescens application gave the highest significant accumulation of proline under 100 and 80% ET_C compared with the respective controls, while Bacillus megaterium significantly accumulated proline content under severe drought stress (60% ET_c) in both seasons.

3.6 Antioxidant Enzyme Activity

As shown in Fig. 1b, c and d, the limited water supplies (80 and 60% ET_c) considerably increased the antioxidant enzyme activities (SOD, POD, and CAT) in snap bean leaves in comparison with the well-watered conditions in both growing seasons. The application of PGPR markedly resulted in significant increments in SOD, POD, and CAT activities compared with the non-PGPR treatment. It is noteworthy that B. megaterium application resulted in the highest significant values of the antioxidant enzyme activities compared with the respective controls under all water treatments.

3.7 Pod Yield Attributes and WUE

The collected data in Fig. 2a, b and c show that pod yield and its attributes were gradually and significantly reduced by increasing the drought severity. Severe drought stress (60% ET_c) decreased pod yield by 49.11, and 57.74% in the first and second seasons, respectively, compared with those in well-watered conditions. However, PGPR applications positively enhanced the pod yield and its components under all water regimes. Bacillus megaterium inoculation showed the best values of these parameters under all water regimes, and its effect was more noticeable under severe drought (60% ET_c) than under moderate drought conditions (80% ET_c). In addition, the data in Fig. 2d demonstrate that WUE progressively increased when decreasing the water application from 100 to 80% of ET_c and then significantly decreased under severe drought stress (80% ET_c). PGPR treatments significantly improved WUE compared with the check plants. Bacillus megaterium application gave the best values of WUE under all water treatments and its application exhibited more pronounced under the severe drought condition.

3.8 Yield Response Factor

To indicate the tolerance level of snap bean crop to water deficit stresses (80 and 60% of ET_c), Ky values were estimated for all PGPR treatments and non-treated plants with pooled data from the two growing seasons (Fig. 3). The Ky factor values of all PGPR were smaller than those of the non-treated plants under the two water deficit levels (80 and 60% of ET_c), indicating the effectiveness of all applied PGPR in alleviating the detrimental impacts of drought stress. Bacillus megaterium gave the lowest ky values under both drought stresses.

3.9 Drought Tolerance Index

Table 6 represents the DTI values (average of the two growing seasons) of the studied traits, which were calculated as a percentage of all measured parameters between the non-PGPR-treated plants grown under well-irrigated and drought-stress conditions. DTI percentages exhibit that proline content and SOD, POD, and CAT activities which have DTI% > 100%, were the traits most sensitive to drought conditions (under both 80 and 60% of ET_c). In addition, the remaining traits demonstrated DTI values < 100% and > 50% except for leaf area, root fresh and dry weights, phosphorus content, and plant yield, which demonstrated the lowest responsiveness to severe drought conditions (60% of ET_c) with the values of 42.12, 45.59, 43.77, 48.16, and 46.58%, respectively.

Table 6

Drought tolerance index (DTI%) of all measured characteristics at 80 and 60% of the estimated crop evapotranspiration.
Traits	DTI (%) at 80% ET_c	DTI (%) at 60% ET_c
Plant length	85.94 ± 6.16	72.26 ± 8.96
Number of leaves/plant	79.87 ± 0.55	61.62 ± 3.18
Leaf area	64.98 ± 4.52	42.12 ± 2.57
Shoot fresh weight	76.02 ± 0.14	57.80 ± 4.98
Root fresh weight	66.61 ± 2.12	45.59 ± 1.48
Shoot dry weight	75.72 ± 11.96	62.92 ± 10.79
Root dry weight	65.65 ± 5.06	43.77 ± 3.38
Nitrogen content	89.10 ± 1.11	79.17 ± 0.84
Phosphorus content	74.84 ± 1.30	48.16 ± 0.47
Potassium content	88.37 ± 0.05	64.78 ± 1.98
Calcium content	88.14 ± 0.17	75.11 ± 0.15
Magnesium content	70.13 ± 0.46	51.61 ± 0.94
SPAD readings	90.65 ± 1.37	80.82 ± 2.19
Leaf relative water content	89.37 ± 0.008	74.67 ± 0.001
Leaf membrane stability	88.08 ± 4.94	73.63 ± 6.35
Proline content	130.96 ± 0.015	158.61 ± 0.04
Superoxide dismutase activity	110.46 ± 0.037	138.66 ± 0.68
Peroxidase activity	117.27 ± 0.056	131.10 ± 4.38
Catalase activity	110.90 ± 0.017	130.75 ± 0.02
Pod length	90.52 ± 2.33	78.79 ± 6.74
Pod diameter	84.97 ± 1.37	69.71 ± 1.36
Plant yield	72.81 ± 4.34	46.58 ± 6.11
The values represent the means of the two growing seasons ± standard deviation of at least three replicates. Comparison of the tolerance index of all estimated traits under drought stress without PGPR applications.

3.10 Principal Component Analysis

A principal component analysis (PCA) was carried out to determine the relationships among the measured parameters and the PGPR treatments under different irrigation water levels (Fig. 4). Each variable is illustrated by an arrow, and the longer its length, the greater its contribution to a given component. The angle formed by the arrows indicates the degree of correlation between variables; the smaller the angle, the greater the correlation. The first principal component (PC1) accounted for 82% of the variance in the obtained data, whereas the second component (PC2) captured 11.5% of the variance under the different treatments. The cumulative proportion of the variation approached 93.5% of the total variance. The results revealed that well-watered plants and water deficit levels combined with inoculation with different PGPR were strongly associated with all evaluated parameters. As the WR_80% and WR_60% combined with Rhizobium leguminosarum application or without PGPR treatment are distant from the different variables tested, they show no direct relation with any of these and were more effected by water deficiency. Additionally, there were strong positive correlations (indicated by an acute angle) between agronomical and physiological variables related to the PGPR treatments under different water irrigation levels. On the contrary, there were strong negative correlations between vegetative growth parameters, physiological traits, and yield attributes on the one hand and proline and antioxidant enzyme activities on the other hand under severe water deficit and the application of Bacillus megaterium had an effective impact in attenuating the negative effects of drought stress.

It has been well documented that drought is considered as one of the major abiotic stresses that influence plant growth and productivity (Ortiz et al. 2015; Anli et al. 2020). In this respect, findings of the current study pointed out that snap bean growth parameters were significantly decreased under various deficit irrigations, whereas the PGPR inoculation significantly enhanced all these variables compared to the respective controls under well-water and deficit-water conditions. Several studies have reported that vegetative growth parameters of many crops significantly decreased under drought stress (Hashem et al. 2019; Batool et al. 2020; Ibrahim et al. 2021; Metwaly et al. 2022). These drought-induced reductions could be due to a loss of turgidity causing a reduction in cell division and expansion (Avramova et al. 2015; Ullah and Farooq 2022), and may also be due to decreased levels of auxins, cytokinins, and gibberellins (Farooq et al. 2012), ultimately resulting in a decline in growth and productivity. However, plant growth–promoting rhizobacteria have also been found to enhance vegetative growth parameters under drought stress in various vegetable crops, like common bean (German et al. 2000), cucumber (Wang et al. 2012), mung bean (Sarma and Saikia 2014), pea (Saikia et al. 2018), tomato (Astorga-Eló et al. 2021; Liu et al. 2023), potato (Batool et al. 2020), okra (Puthiyottil and Akkara 2021), spinach (Petrillo et al. 2022), and lettuce (Ouhaddou et al. 2023). According to numerous studies, the mechanisms of plant growth promotion managed by PGPR include: ¹the production of organic acids that solubilize the nutrients such as phosphorus, iron, and zinc, making them available to the plants, ²chelating compounds that prvent the nutrients from getting precipitated and unavailable for plants, ³phytohormones that stimulate plant growth and development by promoting cell division and elongation, ⁴siderophores that chelate iron from the soil, making it available for plants to absorb, biological N₂ fixation that provide the plants with extra nitrogen, ⁵phosphate solubilization, and ⁶the production of antimicrobial substances that suppress the growth of pathogenic microorganisms in the soil, protecting plants from various diseases (Ahmad et al. 2022). Moreover, the application of PGPR significantly improved the fresh and dry weights of shoot and root systems under drought stress, since plant stress is relieved and normal plant growth is restored by the bacterial enzyme ACC deaminase's degradation of ACC, a precursor of ethylene (Danish et al. 2020a, b; Duan et al. 2021), the stress hormone that hampers root and shoot growth (Glick et al. 2007). Bacillus megaterium stimulates plant growth by releasing phytohormones like auxins, cytokinins, and gibberellins, which lead to an increase in vegetative growth (Ortíz-Castro et al. 2008).

The achieved results showed that leaf nutrient content of N, P, K, Ca, and Mg decreased significantly under deficit irrigations, whereas PGPR inoculation improved all these nutrients compared to the respective controls, under normal conditions as well as water deficiency levels. Numerous studies have shown that drought negatively affected nutrient availability in soils, decreased nutrient uptake, transport, and concentrations in plant tissues, and ultimately caused reductions in plant growth (Cetinkaya et al. 2016; Abdelaal et al. 2021). The application of PGPR significantly improved the nutrient contents (N, P, K, Ca, and Mg) of snap bean leaves. Similar improvements in nutrient contents were observed in many crops with the application of PGPR (Danish et al. 2020a, b; Begum et al. 2022; Jain and Saraf 2023). The enhancement in root growth through the application of PGPR might have also improved nutrient uptake and ultimately enhanced photosynthetic activity, thereby enhancing plant growth and productivity. Additionally, chelation, acidification, exchange reactions, the release of minerals, the synthesis of inorganic and organic acids, the secretion of siderophores, and the production of exopolysaccharides are all ways that PGPRs can increase the availability of nutrients in soil (Ditta et al. 2018; Etesami and Maheshwari 2018).

This study revealed that the SPAD readings of the leaves gradually decreased with increasing water severity. These results are consistent with the previous studies (Alghamdi et al. 2023; Ferioun et al. 2023). These reductions in greenness of the leaves under drought stress could be ascribed to: ¹stomata closure (Raza et al. 2023), ²reduction in water potential (Table 5), ³reduction in N absorption (Table 4), which is an essential component of the chlorophyll molecule, ⁴suppressing the activity of specific enzymes required for the biosynthesis of chlorophyll, ⁵increased degradation of chlorophyll due to the elevated chlorophyllase enzyme activity, ⁶damage to the photosynthetic apparatus, or/and ⁷decreased uptake of magnesium needed for chlorophyll biosynthesis (Oguz et al. 2022). In this concern, the reductions in leaf greenness under drought stress (Table 5) are in good accordance with the reductions in plant growth parameters (Tables 2 and 3). Inoculation with PGPR counterbalanced the damaging effects of drought stress on chlorophyll content. These results are substantiated with the findings of several research works which indicated that PGPR attenuated the negative impacts on chlorophyll content under saline conditions for many vegetable crops. According to several studies, plants treated with PGPR showed better photosynthetic rates than untreated plants (Samaniego-Gámez et al. 2016; Nawaz et al. 2022; Zhao et al. 2023; Yadav et al. 2023). Ansari et al. (2017) hypothesized that PGPR's stimulatory effects on cytokinin synthesis and nutrient uptake, especially Mg, improved chlorophyll content. Additionally, PGPR may enhance chlorophyll content by limiting its breakdown by lowering ethylene because of its unique ACC-deaminase activity (Ibrahim and El-Sawah 2022). Bacillus megaterium gave the highest SPAD readings compared to the respective controls and the other PGPR under all water levels. This result agrees with Acin-Albiac et al. (2023).

Concerning the leaf relative water content (LRWC), the obtained results support the previous research which showed that LRWC and LMSI were reduced in plants under water stress (Ors et al. 2016). The reduction in LRWC lowers the water potential of leaves and closes the stomata, which lowers the transpiration rate, leading to an increase in leaf temperatures causing protein denaturation and altering membrane stability (Laxa et al. 2019). Moreover, membrane instability is mainly due to lipid peroxidation caused by ROS produced by drought stress (Hussain et al. 2018). PGPR improved RWC and may support plants to resist the oxidative and osmotic stresses induced by drought stress conditions (Laxa et al. 2019). Anew, our results stated that Bacillus megaterium was the most efficient treatment in improving LRWC. Such results are in line with those obtained by(Grover et al. 2021) who found that sorghum plants treated with Bacillus sp. under drought stress showed a 24% increase in RWC. Similarly, the obtained results demonstrated that PGPR enhanced leaf membrane stability index under drought treatments. Such results are in harmony with (Silva et al. 2019). This simulative effect could be attributed to the EPSs produced by PGPR which are crucial for protecting and maintaining the membrane structure under drought stress (Bouremani et al. 2023). Furthermore, the increased integrity of cell membranes caused by PGPR inoculation may be a result of PGPR activating the antioxidant defense system, increasing drought tolerance (Mansour et al. 2021).

It is well documented that drought stress boosts the overproduction of ROS in plant cells, inducing oxidative stress (Armada et al. 2014), and to counteract ROS overproduction, plants accumulate several protective osmolytes, proteins, non-enzymatic metabolites, and antioxidant enzymes that can scavenge ROS under water stress (Hosseini et al. 2018). Proline content is considered as an important osmolyte for assessing drought stress tolerance (Abdela et al. 2020), since high proline content protects the cell membrane and maintains the cell water status during drought stress (Ortiz et al. 2015). The obtained data revealed that proline increased proportionately with the severity of the drought stress in both seasons. These results are in accordance with those of Kaushal (2019) and Batool et al. (2020). Application of PGPR improved the accumulation of proline in snap bean plants subjected to drought stress when compared with that in the control plants. Various studies have demonstrated the obvious role of PGPR in the accumulation of proline (Ghosh et al. 2019; Kaushal 2019; Abdela et al. 2020; Batool et al. 2020; Gontia-Mishra et al. 2020). Drought-stressed plants inoculated with Bacillus megaterium exhibited the highest proline content in both seasons. Similarly, proline production has been noted to increase in stressed plants inoculated with Bacillus (Sziderics et al. 2007). Additionally, the study showed a significant increase in antioxidant enzymes (SOD, POD, and CAT) when snap bean plants were exposed to water-deficit conditions. Our results are in accordance with Li et al. (2020) who observed higher antioxidant enzyme activity in drought-stressed plants. Moreover, antioxidant enzyme activities (SOD, POD, and CAT) were positively improved in PGRB-inoculated plants. The increased enzymatic antioxidant activities of SOD, POD, and CAT found in plants treated with PGPR suggested that these plants had improved redox defense status to prevent damage from reactive oxygen species by reducing the peroxidation of cell membrane lipids as well as structural and functional proteins under drought stress (Sharma et al. 2022).

Yield is determined by many physiological and biochemical processes which are highly affected by water supply. The achieved results demonstrated that reducing irrigation level decreased snap bean yield attributes. Reductions in yield and its components were formerly reported in water-stressed snap bean (Nemeskéri et al. 2018; Süheri et al. 2020), which depend upon the severity and duration of the stress. These reductions in yield may be attributed to the reductions in assimilate translocation and dry matter portioning through the impairments of physiological and biochemical processes. In this concern, the reductions in yield and its components under water deficit are in a good accordance with the reductions in plant growth parameters and biomass accumulation, leaf nutrient contents, SPAD readings, leaf water relative content, and leaf membrane stability index. PGPR applications positively yielded more pod yield from snap bean plants than noninoculated plants under water stress. The highest pod yields were significantly observed with B. megaterium under all water levels. Previous studies demonstrated that the application of PGPR such as Pseudomonas spp., Bacillus spp., Rhizobium spp., and Azospirillum has been reported to significantly increase yield in several crops, such as pea (Saikia et al. 2018), tomato (Astorga-Eló et al. 2021), and okra (Puthiyottil and Akkara 2021).

Water use efficiency is also an important criterion, which provides information on the adaptation potential of a plant to drought stress conditions. In the present study, WUE gradually increased when decreasing the water requirement from 100 to 80% of ET_c and then significantly decreased under severe drought stress (80% ET_c). The obtained results are in accordance with those obtained by Nemeskéri et al. (2018). PGPR treatments significantly enhanced WUE compared with the check plants. Bacillus megaterium application gave the best values of WUE under all water treatments, and its application was more noticeable under severe drought conditions. These results coincide with those of Akhtar et al. (2020).

Finally, the obtained Ky values demonstrated that all PGPR ameliorated the harmful impacts of water deficits and Bacillus megaterium was the most effective in indicating the effectiveness of this rhizobacterium in enhancing drought stress tolerance for snap bean crop.

The results showed that the growth and physio-biochemical attributes of snap bean were strongly affected under different deficit irrigation patterns. The addition of PGPR improved all studied traits and alleviated the adverse effects of drought on the growth, yield, and quality of snap bean and enhanced drought stress tolerance of the plants. These enhancements via PGPR applications resulted from enhancing root and shoot systems which promoted water and nutrient uptake, improving plant photosynthetic efficiency, enhancing leaf relative water content and leaf membrane stability index, and stimulating oxygen radical scavenging by proline and antioxidant enzyme accumulations. In addition, the current study evidenced that Bacillus megaterium was the most efficient alleviator in mitigating the detrimental effects of drought. However, further research is needed to deeply investigate the effect of inoculation with the consortia of these rhizobateria on alleviating drought stress in snap bean plants.

Author Contribution Conceptualization, N.A.A. and S.M.Y.; methodology, N.A.A., S.A.A. and S.M.Y.; formal analysis, N.A.A. and S.M.Y.; investigation, N.A.A.; writing—original draft preparation, N.A.A., S.A.A., F.S.A., A.A.G.; writing—review and editing, S.M.Y.; visualization, N.A.A. and S.M.Y.; supervision, S.A.A., F.S.A., A.A.G. and S.M.Y. All authors have read and agreed to the published version of the manuscript.

Conflict of Interest The authors declare that they have no conflict of interest.

Abdela AA, Barka GD, Degefu T (2020) Co-inoculation effect of Mesorhizobium ciceri and Pseudomonas fluorescens on physiological and biochemical responses of Kabuli chickpea (Cicer arietinum L.) during drought stress. Plant Physiology Reports 25:359–369. https://doi.org/10.1007/s40502-020-00511-x
Abdelaal K, Alkahtani M, Attia K, Hafez Y, Király L, Künstler A (2021) The role of plant growth-promoting bacteria in alleviating the adverse effects of drought on plants. Biology (Basel) 10(6):520. https://doi.org/10.3390/biology10060520
Abid M, Tian Z, Ata-Ul-Karim ST, Liu Y, Cui Y, Zahoor R, Jiang D, Dai T (2016) Improved tolerance to post-anthesis drought stress by pre-drought priming at vegetative stages in drought-tolerant and -sensitive wheat cultivars. Plant Physiol Biochem 106:218–227. https://doi.org/10.1016/J.PLAPHY.2016.05.003
Acin-Albiac M, García-Jiménez B, Marín Garrido C, Borda Casas E, Velasco-Alvarez J, Serra NS, Acedo A (2023) Lettuce soil microbiome modulated by an L-α-amino acid-based biostimulant. Agriculture (Switzerland) 13(2):344. https://doi.org/10.3390/agriculture13020344
Ahmad HM, Fiaz S, Hafeez S, Hafeez S, Zahra S, Shah AN, Gul B, Aziz O, Fakhar A, Rafique M, Chen Y Yang SH, Wang X (2022) Plant growth-promoting rhizobacteria eliminate the effect of drought stress in plants. Front Plant Sci 13:875774. https://doi.org/10.3389/fpls.2022.875774
Akhtar SS, Amby DB, Hegelund JN, Fimognari L, Großkinsky DK, Westergaard JC, Müller R, Moelbak L, Liu F, Roitsch T (2020) Bacillus licheniformis FMCH001 increases water use efficiency via growth stimulation in both normal and drought conditions. Front Plant Sci 11:297. https://doi.org/10.3389/fpls.2020.00297
Alghamdi SA, Alharby HF, Bamagoos AA, Zaki SS, Abu El-Hassan AMA, Desoky EM, Mohamed IAA, Rady MM (2023) Rebalancing nutrients, reinforcing antioxidant and osmoregulatory capacity, and improving yield quality in drought-stressed Phaseolus vulgaris by foliar application of a bee-honey solution. Plants 12:63. https://doi.org/10.3390/plants12010063
Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration: guidelines for computing crop water requirements-FAO irrigation and drainage paper 56. FAO, Rome, Italy, p. 300
Almeida OAC, de Araujo NO, Mulato ATN, Persinoti GF, Sforca ML, Calderan-Rodrigues MJ, Oliveira JVdC (2023) Bacterial volatile organic compounds (VOCs) promote growth and induce metabolic changes in rice. Front Plant Sci 13: 1056082. https://doi.org/10.3389/fpls.2022.1056082
Anli M, Baslam M, Tahiri A, Raklami A, Symanczik S, Boutasknit A, Ait-El-Mokhtar M, Ben-Laouane R, Toubali S, Ait Rahou Y, Ait Chitt M, Oufdou K, Mitsui T, Hafidi M, Meddich A (2020) Biofertilizers as strategies to improve photosynthetic apparatus, growth, and drought stress tolerance in the date palm. Front Plant Sci 11:516818. https://doi.org/10.3389/fpls.2020.516818
Ansari RA, Rizvi R, Sumbul A, Mahmood I (2017) PGPR: Current vogue in sustainable crop production. In: Probiotics and Plant Health. Springer Singapore, pp 455–472. https://doi.org/10.1007/978-981-10-3473-2_21
Armada E, Roldán A, Azcon R (2014) Differential activity of autochthonous bacteria in controlling drought stress in native Lavandula and Salvia plants species under drought conditions in natural arid soil. Microb Ecol 67:410–420. https://doi.org/10.1007/s00248-013-0326-9
Ashry NM, Alaidaroos BA, Mohamed SA, Badr OAM, El-Saadony MT, Esmael A (2022) Utilization of drought-tolerant bacterial strains isolated from harsh soils as a plant growth-promoting rhizobacteria (PGPR): Utilization of drought-tolerant bacterial strains. Saudi J Biol Sci 29:1760–1769. https://doi.org/10.1016/j.sjbs.2021.10.054
Astorga-Eló M, Gonzalez S, Acuña JJ, Sadowsky MJ, Jorquera MA (2021) Rhizobacteria from ‘flowering desert’ events contribute to the mitigation of water scarcity stress during tomato seedling germination and growth. Sci Rep 11(1): 13745. https://doi.org/10.1038/s41598-021-93303-8
Avramova V, Abdelgawad H, Zhang Z, Fotschki B, Casadevall R, Vergauwen L, Knapen D, Taleisnik E, Guisez Y, Asard H, Beemster GT (2015) Drought induces distinct growth response, protection, and recovery mechanisms in the maize leaf growth zone. Plant Physiol 169:1382–1396. https://doi.org/10.1104/pp.15.00276
Bano H, Athar HUR, Zafar ZU, Kalaji HM, Ashraf M (2021) Linking changes in chlorophyll a fluorescence with drought stress susceptibility in mung bean [Vigna radiata (L.) Wilczek]. Physiol Plant 172:1244–1254. https://doi.org/10.1111/PPL.13327
Bargaz A, Lyamlouli K, Chtouki M, Zeroual Y and Dhiba D (2018) Soil microbial resources for improving fertilizers efficiency in an integrated plant nutrient management system. Front. Microbiol. 9:1606. https://doi.org/10.3389/fmicb.2018.01606
Batool T, Ali S, Seleiman MF, Naveed NH, Ali A, Ahmed K, Abid M, Rizwan M, Shahid MR, Alotaibi M, Al-Ashkar I (2020) Plant growth promoting rhizobacteria alleviates drought stress in potato in response to suppressive oxidative stress and antioxidant enzymes activities. Sci Rep 10(1): 16975. https://doi.org/10.1038/S41598-020-73489-Z
Beauchamp C, Fridovich I (1971) Superoxide dismutase: Improved assays and an assay applicable to acrylamide gels. Anal Biochem 44:276–287. https://doi.org/10.1016/0003-2697(71)90370-8
Begum N, Wang L, Ahmad H, Akhtar K, Roy R, Khan MI, Zhao T (2022) Co-inoculation of arbuscular mycorrhizal fungi and the plant growth-promoting rhizobacteria improve growth and photosynthesis in tobacco under drought stress by up-regulating antioxidant and mineral nutrition metabolism. Microb Ecol 83:971–988. https://doi.org/10.1007/s00248-021-01815-7
Benaffari W, Boutasknit A, Anli M, Ait-El-Mokhtar M, Ait-Rahou Y, Ben-Laouane R, Ben Ahmed H, Mitsui T, Baslam M, Meddich A (2022) The native arbuscular mycorrhizal fungi and vermicompost-based organic amendments enhance soil fertility, growth performance, and the drought stress tolerance of quinoa. Plants 11(3):393. https://doi.org/10.3390/plants11030393
Bouremani N, Cherif-Silini H, Silini A, Bouket AC, Luptakova L, Alenezi FN, Baranov O, Belbahri L (2023) Plant growth-promoting rhizobacteria (PGPR): A rampart against the adverse effects of drought stress. Water (Switzerland) 15(3): 418. https://doi.org/10.3390/w15030418
Bucheli J, Dalhaus T, Finger R (2021) The optimal drought index for designing weather index insurance. European Review of Agricultural Economics 48:573–597. https://doi.org/10.1093/erae/jbaa014
Cetinkaya H, Koc M, Kulak M (2016) Monitoring of mineral and polyphenol content in olive leaves under drought conditions: Application chemometric techniques. Ind Crops Prod 88:78–84. https://doi.org/10.1016/j.indcrop.2016.01.005
Chandra P, Wunnava A, Verma P, Chandra A, Sharma RK (2021) Strategies to mitigate the adverse effect of drought stress on crop plants—influences of soil bacteria: A review. Pedosphere 31:496–509. https://doi.org/10.1016/S1002-0160(20)60092-3
Chapman HD, Pratt PF (1982) Methods of analysis for soils, plants and waters. Soil Sci 93:68. https://doi.org/10.1097/00010694-196201000-00015
Chaudhary P, Singh S, Chaudhary A, Sharma A and Kumar G (2022) Overview of biofertilizers in crop production and stress management for sustainable agriculture. Front. Plant Sci. 13:930340. https://doi.org/10.3389/fpls.2022.930340
Danish S, Zafar-Ul-Hye M, Hussain S, Riaz M, Qayyum MF (2020a) Mitigation of drought stress in maize through inoculation with drought tolerant ACC deaminase containing PGPR under axenic conditions. Pak J Bot 52:49–60. https://doi.org/10.30848/PJB2020-1(7)
Danish S, Zafar-Ul-Hye M, Mohsin F, Hussain M (2020b) ACC-deaminase producing plant growth promoting rhizobacteria and biochar mitigate adverse effects of drought stress on maize growth. PLoS One 15(4): e0230615. https://doi.org/10.1371/journal.pone.0230615
de Andrade LA, Santos CHB, Frezarin ET, Sales LR, Rigobelo EC (2023) Plant growth-promoting rhizobacteria for sustainable agricultural production. Microorganisms 11:1088. https://doi.org/10.3390/microorganisms11041088
Ditta A, Imtiaz M, Mehmood S, Rizwan MS, Mubeen F, Aziz O, Qian Z, Ijaz R, Tu S (2018) Rock phosphate-enriched organic fertilizer with phosphate-solubilizing microorganisms improves nodulation, growth, and yield of legumes. Commun Soil Sci Plant Anal 49(21):2715–2725. https://doi.org/10.1080/00103624.2018.1538374
Doorenbos J, Kassam AH (1979) Yield response to water. FAO irrigation and drainage, p 33
Duan B, Li L, Chen G, Su-Zhou C, Li Y, Merkeryan H, Liu W, Liu X (2021). 1-Aminocyclopropane-1-carboxylate deaminase-producing plant growth-promoting rhizobacteria improve drought stress tolerance in grapevine (Vitis vinifera L.). Frontiers in Plant Science 12:706990. https://doi.org/10.3389/fpls.2021.706990
Etesami H, Maheshwari DK (2018) Use of plant growth promoting rhizobacteria (PGPRs) with multiple plant growth promoting traits in stress agriculture: Action mechanisms and future prospects. Ecotoxicol Environ Saf 156:225–246. https://doi.org/10.1016/j.ecoenv.2018.03.013
FAOSTAT (2022). Food and Agriculture organizations of the United Nations. Statistics Division. http://www.fao.org/faostat/en/#data/QC (accessed 30, December 2022).
Farooq M, Hussain M, Wahid A, Siddique KHM (2012) Drought stress in plants: An overview. In: Aroca, R. (eds) Plant responses to drought stress: From morphological to molecular features. Springer-Verlag Berlin Heidelberg, pp 1–33. https://doi.org/10.1007/978-3-642-32653-0_1
Ferioun M, Srhiouar N, Bouhraoua S, El Ghachtouli N, Louahlia S (2023) Physiological and biochemical changes in Moroccan barley (Hordeum vulgare L.) cultivars submitted to drought stress. Heliyon 9: e13643. https://doi.org/10.1016/j.heliyon.2023.e13643
Ferreira CMH, Vilas-Boas Â, Sousa CA, Soares HM, Soares EV (2019) Comparison of five bacterial strains producing siderophores with ability to chelate iron under alkaline conditions. AMB Express 9: 78. https://doi.org/10.1186/s13568-019-0796-3
German MA, Burdman S, Okon Y, Kigel J (2000) Effects of Azospirillum brasilense on root morphology of common bean (Phaseolus vulgaris L.) under different water regimes. Biol Fertil Soils 32:259–264. https://doi.org/10.1007/s003740000245
Ghosh D, Gupta A, Mohapatra SA (2019) A comparative analysis of exopolysaccharide and phytohormone secretions by four drought-tolerant rhizobacterial strains and their impact on osmotic-stress mitigation in Arabidopsis thaliana. World J Microbiol Biotechnol 35:90. https://doi.org/10.1007/s11274-019-2659-0
Glick BR, Cheng Z, Czarny J, Duan J (2007) Promotion of plant growth by ACC deaminase-producing soil bacteria. In: Bakker PAHM, Raaijmakers JM, Bloemberg G, Höfte M, Lemanceau P, Cooke BM (eds) New Perspectives and Approaches in Plant Growth-Promoting Rhizobacteria Research. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6776-1_8
Gomez AA, Gomez KA (1984) Statistical procedures for agricultural research: Second Edition. A Wiley-Interscience Publication 6:1–690.
Gontia-Mishra, I., Sapre, S., Deshmukh, R., Sikdar, S., Tiwari, S. (2020). Microbe-Mediated Drought Tolerance in Plants: Current Developments and Future Challenges. In: Yadav A, Singh J, Rastegari A, Yadav N (eds) Plant Microbiomes for Sustainable Agriculture. Sustainable Development and Biodiversity, vol 25, pp.351–379, Springer, Cham. https://doi.org/10.1007/978-3-030-38453-1_12
Grover M, Bodhankar S, Sharma A, Sharma P, Singh J, Nain L (2021) PGPR mediated alterations in root traits: Way Toward Sustainable Crop Production. Front Sustain Food Syst 4: 618230. https://doi.org/10.3389/fsufs.2020.618230
Hammerschmidt R, Nuckles EM, Kuć J (1982) Association of enhanced peroxidase activity with induced systemic resistance of cucumber to Colletotrichum lagenarium. Physiol Plant Pathol 20(1):73–82. https://doi.org/10.1016/0048-4059(82)90025-X
Hartmann A, Klink S, Rothballer M (2021) Plant growth promotion and induction of systemic tolerance to drought and salt stress of plants by quorum sensing auto-inducers of the N-acyl-homoserine lactone type: Recent Developments. Front Plant Sci 12(1):73–76. https://doi.org/10.3389/fpls.2021.683546
Hashem A, Kumar A, Al-Dbass AM, Alqarawi AA, Al-Arjani ABF, Singh G, Farooq M, Abd_Allah EF (2019) Arbuscular mycorrhizal fungi and biochar improves drought tolerance in chickpea. Saudi J Biol Sci 26(3):614–624. https://doi.org/10.1016/j.sjbs.2018.11.005
Hoffman GJ, Evans RG, Jensen ME, Martin DL, Elliot RL (2007) Design and operation of farm irrigation Systems (pp. 863p-863p). St. Joseph: American Society of Agricultural and Biological Engineers.
Hosseini MS, Samsampour D, Ebrahimi M, Abadía J, Khanahmadi M (2018) Effect of drought stress on growth parameters, osmolyte contents, antioxidant enzymes and glycyrrhizin synthesis in licorice (Glycyrrhiza glabra L.) grown in the field. Phytochemistry 156:124–134. https://doi.org/10.1016/j.phytochem.2018.08.018
Hussain HA, Hussain S, Khaliq A, Ashraf U, Anjum SA, Men S, Wang L (2018) Chilling and drought stresses in crop plants: Implications, cross talk, and potential management opportunities. Front Plant Sci 9:393. https://doi.org/10.3389/fpls.2018.00393
Ibrahim HM, El-Sawah AM (2022) The mode of integration between Azotobacter and Rhizobium affect plant growth, yield, and physiological responses of pea (Pisum sativum L.). J Soil Sci Plant Nutr 22:1238–1251. https://doi.org/10.1007/s42729-021-00727-2
Ibrahim MFM, Ibrahim HA, Abd El-Gawad HG (2021) Folic acid as a protective agent in snap bean plants under water deficit conditions. Journal of Horticultural Science and Biotechnology 96:94–109. https://doi.org/10.1080/14620316.2020.1793691
Jain R, Saraf M (2023) ACC deaminase producing PGPR modulates nutrients uptake, soil properties and growth of cluster bean (Cyamopsis tetragonoloba L.) under deficit irrigation. Biologia (Bratisl):1–14. https://doi.org/10.1007/s11756-023-01376-9
Karavidas I, Ntatsi G, Vougeleka V, Karkanis A, Ntanasi T, Saitanis C, Agathokleous E, Ropokis A, Sabatino L, Tran F, Iannetta PP (2022) Agronomic practices to increase the yield and quality of common bean (Phaseolus vulgaris L.): A systematic review. Agronomy 12(2):271. https://doi.org/10.3390/agronomy12020271
Kaushal M (2019) Portraying rhizobacterial mechanisms in drought tolerance: a way forward toward sustainable agriculture In: PGPR amelioration in sustainable agriculture. Elsevier, pp 195–216. https://doi.org/10.1016/B978-0-12-815879-1.00010-0
Kaya C, Higgs D, Ince F, Amador BM, Cakir A, Sakar E (2003) Ameliorative effects of potassium phosphate on salt-stressed pepper and cucumber. J Plant Nutr 26(4):807–820. https://doi.org/10.1081/PLN-120018566
Khan W, Prithiviraj B, Smith DL (2003) Photosynthetic responses of corn and soybean to foliar application of salicylates. J Plant Physiol 160:485–492. https://doi.org/10.1078/0176-1617-00865
Khare T, Desai D, Kumar V (2012) Effect of MgCl₂ stress on germination, plant growth, chlorophyll content, proline content and lipid peroxidation in sorghum cultivars. Journal of Stress Physiology & Biochemistry 8(4):169–178.
Koller HR (1972) Leaf area-leaf weight relationships in the soybean canopy1. Crop Sci 12:180–183. https://doi.org/10.2135/CROPSCI1972.0011183X001200020007X
Ladeiro B (2012) Saline agriculture in the 21^st century: Using salt contaminated resources to cope food requirements. J Bot 2012:1–7. https://doi.org/10.1155/2012/310705
Laxa M, Liebthal M, Telman W, Chibani K, Dietz KJ (2019) The role of the plant antioxidant system in drought tolerance. Antioxidants 8(4):94. https://doi.org/10.3390/antiox8040094
Li B, Feng Y, Zong Y, Zhang D, Hao X, Li P (2020) Elevated CO₂-induced changes in photosynthesis, antioxidant enzymes and signal transduction enzyme of soybean under drought stress. Plant Physiology and Biochemistry 154:105–114. https://doi.org/10.1016/j.plaphy.2020.05.039
Liu FC, Ma HL, Du ZY, Ma B, Liu X, Peng L, Zhang, W (2019) Physiological response of North China red elder container seedlings to inoculation with plant growth-promoting rhizobacteria under drought stress. PLoS One 14(12): e0226624. https://doi.org/10.1371/journal.pone.0226624
Liu J, Zhang J, Shi Q, Liu X, Yang Z, Han P, Li J, Wei Z, Hu T, Liu F (2023) The interactive effects of deficit irrigation and Bacillus pumilus inoculation on growth and physiology of tomato plant. Plants 12(3):670. https://doi.org/10.3390/plants12030670
Mansour E, Mahgoub HAM, Mahgoub SA, El-Sobky ESE, Abdul-Hamid MI, Kamara MM, AbuQamar SF, El-Tarabily KA, Desoky ESM (2021) Enhancement of drought tolerance in diverse Vicia faba cultivars by inoculation with plant growth-promoting rhizobacteria under newly reclaimed soil conditions. Sci Rep 11(1): 24142. https://doi.org/10.1038/s41598-021-02847-2
McCarl BA, Musumba M, Smith JB, Kirshen P, Jones R, El-Ganzori A, Ali MA, Kotb M, El-Shinnawy I, El-Agizy M, Bayoumi M (2015) Climate change vulnerability and adaptation strategies in Egypt’s agricultural sector. Mitigation and Adaptation Strategies for Global Change 20:1097–1109. https://doi.org/10.1007/S11027-013-9520-9/TABLES/6
Mehrasa H, Farnia A, Kenarsari MJ, Nakhjavan S (2022) Endophytic bacteria and SA application improve growth, biochemical properties, and nutrient uptake in white beans under drought stress. J Soil Sci Plant Nutr 22:3268–3279. https://doi.org/10.1007/S42729-022-00884-Y
Metwaly ESE, Al-Yasi HM, Ali EF, Farouk HA, Farouk S (2022) Deteriorating harmful effects of drought in cucumber by spraying glycinebetaine. Agriculture (Switzerland) 12(12):2166. https://doi.org/10.3390/agriculture12122166
Molinari HBC, Marur CJ, Daros E, De Campos MKF, De Carvalho JFRP, Filho JCB, Pereira LFP, Vieira LGE (2007) Evaluation of the stress-inducible production of proline in transgenic sugarcane (Saccharum spp.): Osmotic adjustment, chlorophyll fluorescence and oxidative stress. Physiol Plant 130(2):218–229. https://doi.org/10.1111/j.1399-3054.2007.00909.x
Montavon P, Kukic KR, Bortlik K (2007) A simple method to measure effective catalase activities: optimization, validation, and application in green coffee. Anal Biochem 360:207–215. https://doi.org/10.1016/J.AB.2006.10.035
Nawaz F, Rafeeq R, Majeed S, Ismail MS, Ahsan M, Ahmad KS, Akram A, Haider G (2022) Biochar amendment in combination with endophytic bacteria stimulates photosynthetic activity and antioxidant enzymes to improve soybean yield under drought stress. J Soil Sci Plant Nutr 23(1): 746–760. https://doi.org/10.1007/s42729-022-01079-1
Nemeskéri E, Molnár K, Pék Z, Helyes L (2018) Effect of water supply on the water use-related physiological traits and yield of snap beans in dry seasons. Irrig Sci 36:143–158. https://doi.org/10.1007/s00271-018-0571-2
Oguz MC, Aycan M, Oguz E, Poyraz I, Yildiz M (2022) Drought stress tolerance in plants: Interplay of molecular, biochemical and physiological responses in important development stages. Physiologia 2:180–197. https://doi.org/10.3390/physiologia2040015
Ors S, Ekinci M, Yildirim E, Sahin U (2016) Changes in gas exchange capacity and selected physiological properties of squash seedlings (Cucurbita pepo L.) under well-watered and drought stress conditions. Arch Agron Soil Sci 62:1700–1710. https://doi.org/10.1080/03650340.2016.1168517
Ortiz N, Armada E, Duque E, Roldán A, Azcón R (2015) Contribution of arbuscular mycorrhizal fungi and/or bacteria to enhancing plant drought tolerance under natural soil conditions: Effectiveness of autochthonous or allochthonous strains. J Plant Physiol 174:87–96. https://doi.org/10.1016/j.jplph.2014.08.019
Ortíz-Castro R, Valencia-Cantero E, López-Bucio J (2008) Plant growth promotion by Bacillus megaterium involves cytokinin signaling. Plant Signal Behav 3:263–265. https://doi.org/10.4161/psb.3.4.5204
Ouhaddou R, Ech-chatir L, Anli M, Ben-Laouane R, Boutasknit A, Meddich A (2023) Secondary metabolites, osmolytes and antioxidant activity as the main attributes enhanced by biostimulants for growth and resilience of lettuce to drought stress. Gesunde Pflanzen, pp.1-17. https://doi.org/10.1007/s10343-022-00827-8
Pashang D, Weisany W, Ghajar FGK (2021) Changes in the fatty acid and morphophysiological traits of safflower (Carthamus tinctorius L.) cultivars as response to auxin under water-deficit stress. J Soil Sci Plant Nutr 21(3):2164–2177. https://doi.org/10.1007/s42729-021-00512-1
Petrillo C, Vitale E, Ambrosino P, Arena C, Isticato R (2022) Plant growth-promoting bacterial consortia as a strategy to alleviate drought stress in Spinacia oleracea. Microorganisms 10(9):1798. https://doi.org/10.3390/microorganisms10091798
Puthiyottil P, Akkara Y (2021) Pre treatment with Bacillus subtilis mitigates drought induced photo-oxidative damages in okra by modulating antioxidant system and photochemical activity. Physiol Mol Biol Plants 27:945–957. https://doi.org/10.1007/s12298-021-00982-8
Qessaoui R, Bouharroud R, Furze JN, El Aalaoui M, Akroud H, Amarraque A, Vaerenbergh JV, Tahzima R, Mayad EH, Chebli B (2019) Applications of new rhizobacteria Pseudomonas isolates in agroecology via fundamental processes complementing plant growth. Sci Rep 9(1):1–10. https://doi.org/10.1038/s41598-019-49216-8
Ramakrishna W, Yadav R, Li K (2019) Plant growth promoting bacteria in agriculture: Two sides of a coin. Applied Soil Ecology 138:10–18. https://doi.org/10.1016/j.apsoil.2019.02.019
Raza A, Mubarik MS, Sharif R, Habib M, Jabeen W, Zhang C, Chen H, Chen ZH, Siddique KH, Zhuang W, Varshney RK (2023) Developing drought-smart, ready-to-grow future crops. Plant Genome 16(1):e20279. https://doi.org/10.1002/tpg2.20279
Sachdev S, Ansari SA, Ansari MI, Fujita M, Hasanuzzaman M (2021) Abiotic stress and reactive oxygen species: Generation, signaling, and defense mechanisms. Antioxidants 10(2):277. https://doi.org/10.3390/antiox10020277
Saikia J, Sarma RK, Dhandia R, Yadav A, Bharali R, Gupta VK, Saikia R (2018) Alleviation of drought stress in pulse crops with ACC deaminase producing rhizobacteria isolated from acidic soil of Northeast India. Sci Rep 8(1):3560. https://doi.org/10.1038/s41598-018-21921-w
Samaniego-Gámez BY, Garruña R, Tun-Suárez JM, Kantun-Can J, Reyes-Ramírez A, Cervantes-Díaz L (2016) Bacillus spp. inoculation improves photosystem II efficiency and enhances photosynthesis in pepper plants. Chil J Agric Res 76:409–416. https://doi.org/10.4067/S0718-58392016000400003
Sarma RK, Saikia R (2014) Alleviation of drought stress in mung bean by strain Pseudomonas aeruginosa GGRJ21. Plant Soil 377:111–126. https://doi.org/10.1007/s11104-013-1981-9
Sbei H, Shehzad T, Harrabi M, Okuno K (2014) Salinity tolerance evaluation of Asian barley accessions (Hordeum vulgare L.) at the early vegetative stage. J Arid Land Studies 24:183–186.
Seki M, Umezawa T, Urano K, Shinozaki K (2007) Regulatory metabolic networks in drought stress responses. Curr Opin Plant Biol 10:296–302. https://doi.org/10.1016/j.pbi.2007.04.014
Sharma P, Chouhan R, Bakshi P, Gandhi SG, Kaur R, Sharma A and Bhardwaj R (2022) Amelioration of chromium-induced oxidative stress by combined treatment of selected plant-growth-promoting rhizobacteria and earthworms via modulating the expression of genes related to reactive oxygen species metabolism in Brassica juncea. Front Microbiol 13:802512. https://doi.org/10.3389/fmicb.2022.802512
Shi Q, Bao Z, Zhu Z, Ying Q, Qian Q (2006). Effects of different treatments of salicylic acid on heat tolerance, chlorophyll fluorescence, and antioxidant enzyme activity in seedlings of Cucumis sativa L. Plant Growth Regul 48:127–135. https://doi.org/10.1007/s10725-005-5482-6
Silva ER, Zoz J, Oliveira CES, Zuffo AM, Steiner F, Zoz T, Vendruscolo EP (2019) Can co-inoculation of Bradyrhizobium and Azospirillum alleviate adverse effects of drought stress on soybean (Glycine max L. Merrill.)? Arch Microbiol 201:325–335. https://doi.org/10.1007/s00203-018-01617-5
Singh DP, Singh V, Gupta VK, Shukla R, Prabha R, Sarma BK, Patel JS (2020) Microbial inoculation in rice regulates antioxidative reactions and defense related genes to mitigate drought stress. Sci Rep 10(1):1–17. https://doi.org/10.1038/s41598-020-61140-w
Süheri S, Hussein Hussein NM, Kurtar ES, Yavuz N, Yeşim DAL (2020) Determination of yield and quality of different snap bean varieties under deficit irrigation. Journal of Tekirdag Agricultural Faculty 17:252–263. https://doi.org/10.33462/jotaf.654879
Sziderics AH, Rasche F, Trognitz F, Sessitsch A, Wilhelm E (2007) Bacterial endophytes contribute to abiotic stress adaptation in pepper plants (Capsicum annuum L.). Can J Microbiol 53:1195–1202. https://doi.org/10.1139/W07-082
Ullah A, Farooq M (2022) The challenge of drought stress for grain legumes and options for improvement. Arch Agron Soil Sci 68:1601–1618. https://doi.org/10.1080/03650340.2021.1906413
Vasseur-Coronado M, du Boulois HD, Pertot I, Puopolo G (2021) Selection of plant growth promoting rhizobacteria sharing suitable features to be commercially developed as biostimulant products. Microbiol Res 245:126672. https://doi.org/10.1016/j.micres.2020.126672
Wahab A, Abdi G, Saleem MH, Ali B, Ullah S, Shah W, Mumtaz S, Yasin G, Muresan CC, Marc RA (2022) Plants’ physio-biochemical and phyto-hormonal responses to alleviate the adverse effects of drought stress: A comprehensive review. Plants 11:1620. https://doi.org/10.3390/plants11131620
Wang CJ, Yang W, Wang C, Gu C, Niu DD, Liu HX, Wang YP, Guo JH (2012) Induction of drought tolerance in cucumber plants by a consortium of three plant growth-promoting rhizobacterium strains. PLoS One 7(12): e52565. https://doi.org/10.1371/journal.pone.0052565
Watanabe FS, Olsen SR (1965) Test of an ascorbic acid method for determining phosphorus in water and NaHCO₃ extracts from soil. Soil Science Society of America Journal 29:677–678. https://doi.org/10.2136/SSSAJ1965.03615995002900060025X
Yadav A, Kumar S, Verma R, Narayan S, Jatan R, Lata C, Rai SP, Shirke PA, Sanyal I (2023) Overexpression of PGPR responsive chickpea miRNA166 targeting ATHB15 for drought stress mitigation. Plant Cell, Tissue and Organ Culture (PCTOC). https://doi.org/10.1007/s11240-023-02458-x
Zhao X, Yuan X, Xing Y, Dao J, Zhao D, Li Y, Li W, Wang Z (2023) A meta-analysis on morphological, physiological and biochemical responses of plants with PGPR inoculation under drought stress. Plant Cell Environ 46:199–214. https://doi.org/10.1111/pce.14466

No competing interests reported.

Download PDF

Version 1

posted

You are reading this latest preprint version

Snap Bean Plants' Physio-Biochemical Reactions to Plant Growth-Promoting Rhizobacteria to Mitigate the Negative Effects of Drought Stress

Status:

Version 1

Abstract

Figures

1 Introduction

2 Material and Methods

2.1 Experimental site and plant material

2.2 Experimental layout

2.3 Data Recorded

2.3.1 Vegetative Growth Parameters

2.3.2 Determination of Leaf Mineral Content

2.3.3 PhysioBiochemical Parameters

2.3.4 Yield Parameter Measurements and Water Use Efficiency (WUE)

2.3.5 Yield Response Factor (Ky)

2.3.6 Drought Tolerance Index (DTI)

2.4 Statistical Analysis

3 Results

3.1 Vegetative Growth Parameters

3.2 Leaf Mineral Content

3.3 SPAD Readings

3.4 Relative Water Content (RWC) and Membrane Stability Index (MSI)

3.5 Proline Content

3.6 Antioxidant Enzyme Activity

3.7 Pod Yield Attributes and WUE

3.8 Yield Response Factor

3.9 Drought Tolerance Index

3.10 Principal Component Analysis

4 Discussion

5 Conclusion

Declarations

References

Additional Declarations

Status:

Version 1