Biostimulants action in common bean crop submitted to water deficit

Biostimulants action in common bean crop submitted to water deficit

Agricultural Water Management 225 (2019) 105762 Contents lists available at ScienceDirect Agricultural Water Management journal homepage: www.elsevi...

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Agricultural Water Management 225 (2019) 105762

Contents lists available at ScienceDirect

Agricultural Water Management journal homepage: www.elsevier.com/locate/agwat

Biostimulants action in common bean crop submitted to water deficit a

a

T

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Ícaro Monteiro Galvão , Osvaldir Feliciano dos Santos , Mara Lúcia Cruz de Souza , ⁎ João de Jesus Guimarãesa, Irineu Eduardo Kühna, Fernando Broettob, a b

Department of Rural Engineering, Faculdade de Ciências Agronômicas -FCA, São Paulo State University (UNESP), Botucatu, CEP: 18610-034, SP, Brazil Department of Chemistry and Biochemistry, Bioscience Institute, São Paulo State University (UNESP), Botucatu, CEP: 18618-000, SP, Brazil

A R T I C LE I N FO

A B S T R A C T

Keywords: Drought stress Growth-promoting bacteria Irrigation management Phaseolus vulgaris L.

The water deficit (WD) is one of the severe problems in agriculture resulting in yield loss. The understating of crops behavior face to this condition becomes of great importance, and the use of biostimulants may act as a vegetal growth-promoting, considering its capacity of attenuate the impacts of WD on plants. This study aimed at evaluating the common bean changes in biometric parameters and its yield supplemented with biostimulants, as a response to the imposition of WD. The assay was conducted in a protected environment in Botucatu, Brazil, with common bean cv. IAC Imperador, disposed in split-plot in randomized blocks, with 4 repetitions. The treatments in the plots correspond to the irrigation depths (10 kPa and 40 kPa) and in the subplots the treatment B1 (control); B2 (Bacillus amyloliquefaciens BV 03) and B3 (Bacillus amyloliquefaciens BV 03 + brown algae extract – Ascophyllum nodosum). The irrigation was by drip and the management using a tensiometer. The biometric variables included stem diameter; leaf number and leaf area; leaf dry mass, stem, root and total; root length, diameter and volume; and yield parameters. Discussing the results, it was possible to conclude that the common bean is a very water dependable crop, with WD imposition interfering in all the studied variables, with growth decrease, biomass accumulation and yield. The applied biostimulants (B2 and B3) presented low capacity to attenuate the WD effects in common bean under the cultivation conditions adopted.

1. Introduction The common bean (Phaseolus vulgaris L.) is one of the main crops produced in the world. The expectation for the total Brazilian grain production in the 2018/2019 harvest is of 3.07 million tons (Conab., 2019). One of the primordial factors to the common bean crop development and acquisition of high productivity is the ideal water supply in the different phenological stages (Kobayashi et al., 2016). The stress caused by the lack of water in the soil has considerable impacts in the growth and productivity of the common bean. However, the effects are highly variable according to the exposure time, the stress intensity imposed to the plants, characteristics of the cultivar used and plants ability to adapt to this adverse condition (Rosales et al., 2012; Emam et al., 2010). This way, like a big part of agricultural crops, it is known that the common bean is very sensitive to the water deficit (WD), especially when this condition is imposed in the phenological stages of flowering and during pod filling (Mathobo et al., 2017). Therefore, it is of big importance the study of plants behavior under water stress, in the conditions and way of conventional cultivation.



Because of the development of new cultivation technologies, some alternatives have been presented in the rural field in order to attenuate the effects of biotic and abiotic stress in the growth and yield of crops. Among the most widespread alternatives, we highlight the use of biostimulants to promote the vegetal growth. These natural compounds may be grouped as beneficial microorganisms, such as the plant growth-promoting bacteria (PGPB) and mycorrhizae, besides extracts from different sources like the ones obtained from brown algae (Grover et al., 2014; Kasim et al., 2013). The action of biostimulants seems to be related to the production of phytohormones, improving the nutrients contribution, induction of root growth, besides helping in the osmotic adjustment through the synthesis of organic compounds and in the induction of antioxidant response systems (Kumar and Verma, 2018; Ngumbi and Kloepper, 2016; Vurukonda et al., 2016; Guiry, 2012). This essay aimed at evaluating the effects of water deficiency on biometric parameters and common bean production. From treatments with the biostimulants we have studied a possible attenuation in the impacts of water deficiency on the vegetal growing and development.

Corresponding author. E-mail address: [email protected] (F. Broetto).

https://doi.org/10.1016/j.agwat.2019.105762 Received 27 May 2019; Received in revised form 17 July 2019; Accepted 26 August 2019 0378-3774/ © 2019 Elsevier B.V. All rights reserved.

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corresponding stage to the beginning of crop flowering at 35 days after emergency (DAE). For phytosanitary treatment it was performed only one application of the insecticide Orthene 750 BR and two applications of the fungicide Cerconil WP in doses according to the manufacturer recommendations. Zinc deficiency was detected in the phenological stage V4, which was corrected with the application of 1 kg ha−1 of zinc sulfate diluted in water via soil. Before the harvest, the irrigation was suspended in both treatments in order to dry the grains in the plant. The harvest of the treatments submitted to WD occurred at 77 DAE and of the treatment of the control irrigation depth at 84 DAE.

2. Materials and methods The experiment was conducted in an agricultural greenhouse with 60 m² of area in Botucatu, Brazil. The climate of the city, according to Koppen, is classified as hot-tempered (mesothermal) with average of annual precipitation of 1.428 mm. The average of annual temperature in this region is 20,5 °C and relative humidity between 70% and 20% (Alvares et al., 2013; Cunha and Martins, 2009v). 2.1. Weather data In order to monitor the weather conditions during the experiment, temperature and relative humidity measurement were performed with the assistance of an automatic datalogger installed at the central region of the greenhouse and programmed to execute readings at each 30 min. The temperature average during all the period was 26 °C and relative humidity was 63,5%, appropriate values to the common bean development.

2.4. Date of evaluations The biometric evaluations were performed at 56 DAE, when the plants were in the grain filling stage, phenological stage corresponding to R8. To which one plant for repetition was used. The collecting occurred in the beginning of the morning. At the end of the experiment, the pods collecting was performed and the yield estimate for the treatments, for which the average of six plants for repetition was used. The analyzed variables were stem diameter; leaf number; leaf area, leaf dry matter, stem, root and total ; length, diameter and root volume; and production parameters.

2.2. Treatments and experimental design The treatments with common bean plants (Phaseolus vulgaris L.; cv. IAC Imperador) were disposed in split-plot, being allotted two irrigation depths in the plots (Control, 10 kPa and moderate water deficiency MWD, 40 kPa) and three combinations of biostimulants in the subplots (B1- control; B2- Bacillus amyloliquefaciens BV 03 (3 × 109 UFC mL−1); B3- Bacillus amyloliquefaciens BV 03 + brown algae extract Ascophyllum nodosum), in experimental design in randomized blocks with 4 repetitions and 10 plants for repetition. The experimental units were constituted of polyethylene pots with capacity of 30 liters, in dystrophic Red Latosol in sandy loam soil, with the following characteristics: Organic matter =7 g dm−3; pH (CaCl2) = 4.2; P (resin.) =2 mg dm−3; K+ = 0.4; Ca2+ = 12; Mg+2 = 2; H + Al = 28 e CTC = 41 mmolc dm−3; S = 18; B = 0.19; Cu = 0.06; Fe = 11; Mn = 3.1; Zn = 0.4 mg dm−3; Total sand = 774; Clay = 177; Silt =49 g kg-1 and 33% of saturation bases. The fertilizations followed the recommendations for common bean crop according to Aguiar et al. (2014). The application of treatments with biostimulants was performed through seed inoculation (SI) one hour before the planting. For treatment B1 the SI was performed with distilled water with dose of 2 mL kg−1 seeds, B2 – biostimulant Bacillus amyloliquefaciens BV 03 with the dose of 2 mL kg−1 seeds; B3- Bacillus amyloliquefaciens BV 03 + algae extract Ascophyllum nodosum in the dosage of 2 mL kg−1 seeds each. After the inoculation the planting was performed on 23/08/2018 with four seeds per pot predicting subsequent roughing, leading 2 plants per pot.

2.5. Biometric parameters The stem diameter determination was performed with the assistance of a digital caliper (mm) at approximately 1,5 cm from the soil surface. To leaf number and leaf area all the leaves from a plant were collected, counted, and later the leaf area was measured with the assistance of the integrative model LI-COR LI-3000. The results were expressed as cm2 plant−1. The dry matter was determined by putting samples in the greenhouse with forced air circulation at 60 °C ± 5 until constant weight, and later they were weighed in a precision scale. 2.6. Root morphology In order to evaluate the root morphology, we’ve used the root system of a plant for repetition in each treatment. The roots were washed and placed in glass jars with 70% alcohol solution and stored in a fridge to later evaluation of root structures with the assistance of the software WinRhizo. 2.7. Yield and yield components

2.3. Crop management and irrigation

After the harvest, the grains were manually separated from the pods, counted and weighed. The production parameters evaluated were: pod and grain numbers per plant, grain number per pod, 100grain weight, mass of grains per plant (g) and yield estimate (Kg/ha), considering a population of 240 thousand plants per hectare and the grain humidity corrected to 13%. The grain humidity after the harvest was obtained by the greenhouse method at 105 ± 3 °C for 24 h and the data expressed in percentage (wet basis) (Brasil, 2009).

The irrigation system was by drip in which self-compensating medium-flow button type emitters were used 2,0 L h−1 and operation pressure at 10 mca. The distribution uniformity coefficient was calculated and the result found was 98%, classified as excellent according to classification proposed by Bernardo et al. (2006). The irrigation management was via soil through the use of six tensiometers per experimental plot, installed in the depth of 0,15 m. The monitoring of water tension in the soil was performed daily with the assistance from a puncture digital tensiometer and the tension values converted in volumetric humidity based on the adjustment equation of soil water retention curve. The adjustment of soil water retention curve was performed through the pattern proposed by Van Genuchten (1980). Initially all the treatment combinations receive the same water depth, increasing the soil humidity to the tension 10 kPa, near field capacity. The differentiation of irrigation depths in the plots occurred in

2.8. Statistical analysis To perform the statistical analysis the obtained data were initially submitted to the Kolmogorov-Smirnov normality test with the assistance of the software Minitab 17 and when the normality of the data was confirmed, they were submitted to the variance analysis and when significant the Tukey’s test was applied to compare the averages at the depth 5% of probability using the software AgroStat. 2

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Table 1 Stem diameter (mm) due to the application of biostimulants (B1- control, B2Bacillus amyloliquefaciens BV 03, B3- Bacillus amyloliquefaciens BV 03 + algae extract Ascophyllum nodosum) and irrigation depths in the common bean crop cv, IAC Imperador at 56 DAE. Treatments

C MWD Average CV Plot (%) CV Subplot (%)

Table 3 Total leaf area (cm2) due to the application of biostimulants (B1- control, B2Bacillus amyloliquefaciens BV 03, B3- Bacillus amyloliquefaciens BV 03 + algae extract Ascophyllum nodosum) and irrigation depths in the common bean crop cv, IAC Imperador at 56 DAE.

Biostimulant

Treatments

B1

B2

B3

Average

6,71 5,22 5,96 A

6,41 5,65 6,02 A

6,03 5,36 5,69 A

6,38 a 5,41 b

C MWD Average CV Plot (%) CV Subplot (%)

6 10

Biostimulant B1

B2

B3

Average

3350 1963 2657A

2912 2083 2497A

2872 1735 2304 A

3045 a 1927 b 31 24

Averages followed by the same letter in lower case in the column and upper case in the lines do not differ statistically at the depth of 5% of probability through Tukey’s test. DAE, Days after emergency; C, irrigation depth with 10 kPA in soil; MWD, irrigation depth with 40 kPa in soil.

Averages followed by the same letter in lower case in the column and upper case in the lines do not differ statistically at the depth of 5% of probability through Tukey’s test. DAE, Days after emergency; C, irrigation depth with 10 kPA in soil; MWD, irrigation depth with 40 kPa in soil.

3. Results

Table 4 Vegetal dry biomass accumulation (g plant −1) due to the application of biostimulants (B1- control, B2- Bacillus amyloliquefaciens BV 03, B3- Bacillus amyloliquefaciens BV 03 + algae extract Ascophyllum nodosum) and irrigation depths in the common bean crop cv, IAC Imperador at 56 DAE.

3.1. Stem diameter To the stem diameter variable (Table 1), after the differentiation of irrigation depths, significant effect was observed only for the water treatment. The moderate water deficiency (MWD) depth (40 kPa) presented plants with stem diameter around 15% smaller when compared to plants with normal irrigation (control, 10 kPa). These results show that the WD caused damage to the stem growing and the use of biostimulants was not efficient to mitigate the stress effect.

Treatments

C MWD Average CV Plot (%) CV Subplot (%) Treatments

3.2. Leaf number and leaf area

C MWD Average CV Plot (%) CV Subplot (%) Treatments

The total leaf number were measured (Table 2) and significant effect was not detected for the evaluation period. In relation to the leaf area variable (Table 3), significance was found only for the principal effect in the irrigation depths. It was found then, that the WD resulted in decrease of 37% in the leaf area when compared to the condition of full irrigation. The treatments with biostimulants did not influence this variable, however it was possible to observe that the treatments B2 and B3 presented reductions of approximately 6% and 13% respectively when compared to treatment B1.

C MWD Average CV Plot (%) CV Subplot (%) Treatments

3.3. Dry matter C MWD Average CV Plot (%) CV Subplot (%)

The evaluations of plant dry biomass accumulation are summarized in Table 4. The leaf dry matter analysis denotes significant difference only for the irrigation depths treatments, where the WD caused a decrease of 42% in this parameter, compared to the control plants. The treatments B1, B2 and B3 did not differ statistically. The stem dry matter was influenced by the irrigation depths treatments with the

C MWD Average CV Plot (%) CV Subplot (%) NS

22 16 19

NS

B2

B3

Average

26 17 21

23 17 20

23 17

B2

B3

Average

9 5,1 7,0 A

8,1 5,1 6,6 A

8,3 4,5 6,4 A

8,5 a 4,9 b 37 25

Stem dry matter B1 B2 11,2 9,5 6 6,2 8,6 A 7,9 A

B3 9,7 5,3 7,5 A

Average 10,1 a 5,9 b 34 24

Root dry matter B1 B2 2,5 NS 2,7 1,7 1,5 2,1 2,1

B3 2,4 1,3 1,9

Average 2,5 1,5 41 30

Total dry matter B1 B2 26,44 20,34 12,78 12,88 19,61 A 16,61 A

B3 20,48 11,15 15,81A

Average 22,42 a 12,27 b 51 35

control depth being 42% superior to the WD treatment. It is observed that the biostimulants did not influence the stem dry mass of the common bean. Also, in Table 4, it was observed that the root dry matter did not present significant difference for none of the treatments. To the total dry matter obtainment it was counted the green pod dry mass completely formed until the harvest period. The presented results indicate that there was a significant effect only for the water treatments, with a decrease of 45% in the total biomass accumulation when the plants were submitted to the condition of WD.

Biostimulant B1

B1

Averages followed by the same letter in lower case in the column and upper case in the lines do not differ statistically at the depth of 5% of probability through Tukey’s test. DAE, Days after emergency; C, irrigation depth with 10 kPA in soil; MWD, irrigation depth with 40 kPa in soil. NS Non-significant through Tukey’s test at 5% of probability.

Table 2 Leaf number due to the application of biostimulants (B1- control, B2- Bacillus amyloliquefaciens BV 03, B3- Bacillus amyloliquefaciens BV 03 + algae extract Ascophyllum nodosum) and irrigation depths in the common bean crop cv, IAC Imperador at 56 DAE. Treatments

Leaf dry matter

26 14

Non-significant through Tukey’s test at 5% of probability. 3

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Table 5 Root morphology due to the application of biostimulants (B1- control, B2Bacillus amyloliquefaciens BV 03, B3- Bacillus amyloliquefaciens BV 03 + algae extract Ascophyllum nodosum) and irrigation depths in the common bean crop cv, IAC Imperador at 56 DAE. Treatments

C MWD Average C MWD Average C MWD Average

Table 6 Yield and yield components due to the application of biostimulants (B1- control, B2- Bacillus amyloliquefaciens BV 03, B3- Bacillus amyloliquefaciens BV 03 + algae extract Ascophyllum nodosum) and irrigation depths in the common bean crop cv, IAC Imperador.

Length (cm)

Treatments

Pod plant−1 B1

B1

B2

B3

Average

2638,9NS 1927,5 2283,2 Diameter (mm) 0,690 0,590 0,64 A Volume (cm3) 9,8 5,3 7,5 A

2134,8 2042,9 2088,8

2360,3 2386,8 2373,5

2378 2119

C MWD Average

0,760 0,560 0,66 A

0,790 0,580 0,68 A

0,74 a 0,58 b

C MWD Average

9,6 5,1 7,3 A

11,6 6,6 9,1 A

10,3 a 5,7 b

C MWD Average C MWD Average

Averages followed by the same letter in lower case in the column and upper case in the lines do not differ statistically at the depth of 5% of probability through Tukey’s test. DAE, Days after emergency; C, irrigation depth with 10 kPA in soil; MWD, irrigation depth with 40 kPa in soil. NS Non-significant through Tukey’s test at 5% of probability.

C MWD Average

3.4. Root morphology C MWD Average

The root morphology evaluation is presented in Table 5. After the root scanning and image treatment using the software WinRhizo, it is possible to evaluate that the root length did not change in a significant way due to the applied treatments. There was effect to the irrigation depths in relation to the root diameter and volume. To these measurements, the control plants, where the soil humidity was kept near field capacity, presented higher averages, differing from the deficit depth. In relation to the treatments with biostimulants there was not significant effect to none of the variables. However, in general, it was possible to observe that the highest averages correspond to treatment B3, highlighting the root volume, which was approximately 18% superior to the control (B1) and 20% superior to B2.

B2

19,25 18,5 10 10,75 14,62 A 14,62 A Grains plant−1 84,25 77 42,25 44 63,25 A 60,5 A Number grains pod−1 4,4NS 4,2 4,3 4,2 4,4 a 4,2 Grain weight plant−1 (g) 19,02 17,42 9,4 9,07 14,21 A 13,24 A 100-grain weight (g) 22,6 NS 22,6 22,3 20,6 22,5 21,6 −1 Yield (kg ha ) 4564,9 4179,7 2257,1 2175,6 3411A 3177,7 A

B3

Average

18,5 10,25 14,37 A

18,75 a 10,33 b

80,75 43,75 62,25 A

80,67 a 43,33 b

4,4 4,3 4,4

4,36 4,28

18,59 9,29 13,93 A

18,34 a 9,26 b

23,0 21,3 22,1

22,7 21,4

4460,5 2228,7 3344,6 A

4401,7 a 2220,4 b

Averages followed by the same letter in lower case in the column and upper case in the lines do not differ statistically at the depth of 5% of probability through Tukey’s test. DAE, Days after emergency; C, irrigation depth with 10 kPA in soil; MWD, irrigation depth with 40 kPa in soil. NS Non-significant through Tukey’s test at 5% of probability.

reduction was 37% lower, when compared to the control plot (Table 3). These results show that a smaller water availability in the soil may affect the development of new leaves, accelerating leaf senescence, besides slowing down the growth of remaining leaves (Emam et al., 2010). Mathobo et al. (2017) observed a decrease in the leaf area in common bean submitted to different conditions of water stress. The same effect was found by Soureshjani et al. (2019) in common bean kept on WD. The plants perform this morphological artifice, as a strategy to decrease the transpiration area and, as a consequence, mitigate the water loss to the environment. When the stress is too severe, the plants in prolonged dehydration stage cannot keep or recuperate their leaf area. This way, they reduce the light interception area and the essential metabolic activities, which eventually results in plant death. (Sahoo et al., 2013). In this essay, the decrease in leaf number and leaf area with the imposition of WD, reflected on the leaf dry matter (Table 4), which presented decrease of 42% compared to the irrigation depth of control plants (10 kPa). A similar behavior was observed to stem dry matter, also with a significant decrease of 42% and 40% to root dry matter. The total dry matter presented decrease of 45% in the deficit irrigation depth. The results show that the WD affected the biomass accumulation in a very significant way. The lowest dry matter production can be related to the total leaf area decrease, thus changing the light interception surface, as a consequence resulting in the decline of photosynthetic activity (Mathobo et al., 2017). Several authors have related the decrease of biomass accumulation and growth in common bean submitted to WD, being this morphological variable one of the most affected by this adverse condition. These effects vary due to the genetic material (cultivar), phenological stage and stress intensity (Chacón et al., 2019; Soureshjani et al., 2019; Mathobo et al., 2017).

3.5. Yield and yield components The production components and the yield are presented in Table 6. There was not significant effect with application of the treatments to the grains per pod number and 100-grain weight. For the pod per plant number, grains per plant, grain mass per plant it was observed that the irrigation depths influenced significantly. To these variables, the deficit irrigation depth was responsible for a decrease of 45%, 46% and 50% respectively when compared to the control treatment. On the other hand, the treatments with biostimulants did not present effect to these measurements. These results can affect the yield, considering that the WD treatment induced a decrease of 50% in the total yield average. 4. Discussion The imposition of the water deficit resulted in significant decrease in stem diameter (Table 1). The decrease of water availability may affect the physiological and metabolic activities in plants which modify morphologic characteristics especially in the ones related to growth (Chai et al., 2016). According to Padilha et al. (2016) the growth decrease occurs due to the cell turgor decrease, which is a factor directly related to the cell expansion. Thus, globally, WD events induce to the lowest growth rates. Although a significant difference for leaf number was not found, it was possible to notice a reduction tendency as a response to stress (Table 2). This reduction was observed in a significant manner for leaf area, when the irrigation depths differentiation was established. The 4

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better to the environmental conditions and present higher capacity of promoting the growth and stimulate the plants when they are associated with other microorganisms (SINGH et al., 2014). The lineage in this paper, Bacillus amyloliquefaciens BV 03, neither in the isolated treatment nor associated to the algae extract was capable of stimulate the plants in control conditions or water deficit. Therefore, the species used was not effective as growth promoting, even when associated to algae extract. Kumar et al. (2016) studied the synergetic effect of Pseudomonas putidaand Bacillus amyloliquefaciens in chickpea plants submitted to water stress. In that study, the authors noticed that the synergetic application of biostimulants has a better potential to promote the plant growth, under water stress conditions when compared to the use of lineages individually. Yet, Kasim et al. (2013) studied the inoculation effect of Bacillus amyloliquefaciens 5113 and Azospirillum brasilense NO40 in wheat plant submitted to WD. The authors noticed that the bacterial inoculation improved the wheat growth under drought conditions, besides better survival, fresh and dry weight and water content. The authors also reported that the rhizobacteria has been used mainly to promote the growth, because they stimulate the plants through different means such as the production of growth regulators which interfere in the crop production. Similar results were found by Naveed et al. (2014) to the corn crop and Sarma and Saikia (2014) to the common bean. Such reports found in the literature reinforce that knowledge about the species to be used and the isolated lineage is of great importance to reach the expected results and bring return to the development and yield of crops with the use of this technology.

Based on the root morphology evaluations (Table 5) it was possible to observe that the treatments under WD did not differ significantly from the control treatments, to the length variable. Among the many adaptative characteristics developed by the plants to handle adverse conditions, changes in the root architecture are considered one of the most important (Huang et al., 2014). The plants when submitted to stress conditions use the mechanism of inducing the root growth aiming to explore a larger soil area and seek for water in deeper regions. Therefore, this variable tends to present equal or higher values when they are submitted to ideal conditions of soil humidity (Khonghintaisong et al., 2018; Mittal et al., 2015). The root volume and diameter were smaller in the deficit depths, showing that the cultivar in study uses this mechanism as a way to adapt to the drought. Thus, the plants start to put more energy and photoassimilates to the length, in detriment of the diameter and volume with a consequent increase in the capacity of exploration to the soil profile. Although there is not a significant difference due to the use of biostimulants and root development, in general the averages of these treatments were higher when compared to the control, especially in relation to treatment B3. Several authors discuss that the plant associations, rhizobacteria and algae extract seem to be beneficial and induce the root growth as a response to the environmental stress, especially the water stress (Vurukonda et al., 2016; Ngumbi and Kloepper, 2016; Kasim et al., 2013). The irrigation depths differentiation and the imposition of water deficit conditions to the applied treatments occurred in the phenological stage R6 corresponding to the beginning of the crop flowering stage. The WD at this moment reduce the production parameters such as the pod per plant and grains per plant, when compared to the control condition (Table 6). This decrease can be a result of the senescence process and flower abortion, once the plants under stress reduce the photosynthetic metabolism and photoassimilate accumulation. These events can induce to the viability loss and flower senescence. Similar behavior was observed by several authors (Ghassemi et al., 2018; Mathobo et al., 2017; Rezene et al., 2013) also to the common bean crop. The yield components such as grain number per pod and 100-grain weight were not affected by the water deficit. The variable grain number per pod is an inherent characteristic to the cultivar and can be little affected by moderated environmental variations. Gohari (2013) argues that the 100-grain weight can present decrease, when the common bean plants are submitted to more severe stresses since these conditions are responsible for accelerating the grain maturity, besides that resulting in small grains and smaller mass. In this study, the harvest difference was of only seven days and the imposed stress was moderated, not causing significant decrease for the 100-grain weight. All the observed variables in the common bean yield components under water deficit reflected in the grain mass per plant and consequently in the total yield, which had a decrease of approximately 50% for the deficit depth. The quantity of yield loss because of stress is variable according to the genotype, the intensity and the exposure time in which the plants get exposed to the stressing condition. The common bean decrease yield due to water deficit was reported by several authors and they reinforced that the flowering and grain filling are the most sensitive phenological stages. In case the irrigation depth is imposed in stage corresponding to the grain maturing, the yield loss is smaller, providing to the producers the choice of adopting strategies for the irrigation management to save water and energy (Chacón et al., 2019; Soureshjani et al., 2019; Ghassemi et al., 2018; Mathobo et al., 2017). In this study there was not significant effect of the biostimulants treatments to the variables related to the growth, biomass accumulation and common bean yield kept under water deficit. The stress intensity, the application manner, characteristics of the microorganism used, concentration and the doses may influence the possible benefits of the biostimulants to the growth and yield of agricultural crops. Some authors report that certain beneficial microorganisms respond

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