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Formulations of Pseudomonas fluorescens and Burkholderia pyrrocinia control rice blast of upland rice cultivated under no-tillage system
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Formulations of Pseudomonas fluorescens and Burkholderia pyrrocinia control rice blast of upland rice cultivated under no-tillage system Maythsulene Inácio de Sousa Oliveiraa,d, Amanda Abdallah Chaibubb,d, Thatyane Pereira Sousac, Marcio Vinicius Carvalho Barros Cortesd, Alan Carlos Alves de Souzae, ⁎ Edemilson Cardoso da Conceiçãoa, Marta Cristina Corsi de Filippid, a Pos graduate Program in Pharmaceutical Innovation, Federal University of Goiás, Rua 240, esquina com 5ª Avenida, s/n, Setor Leste Universitário, CEP: 74605-170, Goiânia, Goiás, Brazil b Departament of Phytopathology, University of Brasília, Brasília, DF CEP: 70.910-900, Brazil c Federal University of Goiás, Goiânia, GO CEP: 74.690-900, Brazil d Embrapa Rice and Beans, Rodovia GO-462, Km 12, Fazenda Capivara, CEP: 75375-000, Santo Antônio de Goiás, GO, Brazil e Federal University of Lavras, Lavras, MG 37200-000, Brazil
G R A P H I C A L A B S T R A C T
A R T I C LE I N FO
A B S T R A C T
Keywords: Biological control Rhizobacteria Magnaporthe oryzae Oryza sativa Sustainable management
Leaf blast caused by Magnaporthe oryzae is among the major diseases that limit rice productivity in the world, and control of the disease occurs, basically, through the application of fungicides. Control methods such as the application of growth promoting rhizobacteria could be inserted in the integrated management of rice blast. The objective of this work was to evaluate the potential of four liquid formulations containing Pseudomonas fluorescens (BRM 32111) and Burkholderia pyrrocina (BRM 32113) to suppress leaf blast, under field conditions. The trials were conducted at Embrapa Rice and Beans, between December 2018 and April 2019. The experiments were performed in a randomized block containing 7 treatments, 4 replicates. The treatments consisted of microbiolized seeds and sprays at 14 and 21 days after planting with: Formulation 11 + BRM 32,113 (T1); Formulation 32 + BRM 32,113 (T2); Formulation 11 + BRM 32,111 (T3): Formulation 20 + BRM 32,111 (T4); BRM 32,111 (T5); BRM 32,113 (T6) and Absolute control (water – T7). Severity of leaf blast and panicle, gas exchange and grain yield were evaluated. Plants treated with P. fluorescens (T3, T4 and T5) or B. pyrrocinia (T1, T2 and T6) presented 49%, 39%, 60%, 15% increase in the assimilation rate of CO2 (A), transpiration (E), stomatal conductance (gs) and internal CO2 concentration (Ci), respectively. All treatments were efficient in suppressing leaf and panicle blast and in promoting biomass increase in 55%. The yields of T1, T4, T5 and T6
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Corresponding author at: Agricultural Microbiology Laboratory, Embrapa Rice and Beans, Santo Antônio de Goiás, GO 75375-000, Brazil. E-mail address: cristina.fi[email protected] (M.C.C.d. Filippi).
https://doi.org/10.1016/j.biocontrol.2019.104153 Received 19 August 2019; Received in revised form 4 November 2019; Accepted 19 November 2019 1049-9644/ © 2019 Elsevier Inc. All rights reserved.
Please cite this article as: Maythsulene Inácio de Sousa Oliveira, et al., Biological Control, https://doi.org/10.1016/j.biocontrol.2019.104153
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treatments increased 481, 424, 688 and 427 kg ha−1, respectively. Our results indicate that the formulated rhizobacteria have the potential to be included in the integrated management for blast control in rice fields.
1. Introduction
industrial waste and evaluated in suppress rice blast, influence in physiological parameters and productivity in field conditions.
Rice (Oryza sativa) represents the greatest crop in economics and social importance in the world, being, traditionally, one of the most consumed cereal. Brazil is among the ten largest rice producers, and stands out as the largest producer outside the Asian continent, with an estimated production of 12 million tons (National Supply Company, CONAB, 2018; Food and Agriculture Organization of the United Nations, FAO, 2018). However, rice low productivity is directly related to the diseases that affect it during crop cultivation. Rice crop ecosystems are classified as irrigated and upland. The upland system presents sustainable advantages, such as, water economy, and less emission of greenhouse gases (Intergovernmental Panel on Climate Change, IPCC, 2014). However, the low productivity of upland system relates to the heterogeneity of climate, soil fertility, rainfall distribution, weed control, and inadequate cultural practices for sustainable management of pests and diseases (Galinato et al., 1999; Heinemann and Sentelhas, 2011). The rice blast disease (Magnaporthe oryzae) represents the most destructive diseases affecting rice crops, its distribution is geographically wide, and occurs in practically all regions where rice is grown. The disease can infect leaves, stalks, panicles and consequently seeds, which can lead to 100% losses in yield destroying approximately 10–30% of the world's rice harvested (Filippi et al., 2011; Fernandez and Orth, 2018). Currently, disease control depends on integrated management that includes the planting of resistant cultivars, cultural practices and fungicides application. However, the genetic resistance of the genetically improved cultivars becomes fragile due to the high genetic variability of the pathogen population, leading to the indiscriminate use of fungicides, which has admittedly caused several environmental problems (Filippi et al., 2011; Souza et al., 2015). Nevertheless, given the projections of population growth, in contrast to the concern of society about the impacts caused by the indiscriminate use of pesticides, biological control is considered an attractive technology to be inserted into the integrated management. Its contribution to the development of sustainable agriculture is related to the reduction of environmental and social impact (Compant et al., 2005; Prathap and Ranjitha, 2017). Studies carried out under controlled conditions demonstrated the potential of the rhizobacteria Pseudomonas fluorescens (BRM 32111) and Burkholderia pyrrocinia (BRM 32113) in growth promotion, resistance induction, leaf blast suppression, dry matter gain, promote positive changes in physiological parameters and induce positives morphoanatomic in rice roots (increase in root length, root cortex expansion and increase spaces aerenchyme. (Filippi et al., 2011; Rêgo et al., 2014; Prathap and Ranjitha, 2017; Arriel-Elias et al., 2019) However, the success of biological control depends on obtaining the same promising results, recorded under controlled conditions, under natural field conditions. This implies in the development of commercial scale bioformulations containing ingredients that prolong the shelf life of microorganisms (Fravel, 2005; Selvaraj et al., 2014). Liquid formulations have advantages over other techniques because of the low development cost, ease of preparation and application, and the development of sustainable formulations with agroindustrial residues as, molasses and glycerol, enables the use of products that would be discarded in the environment (Fravel, 2005; Arriel-Elias, et al., 2018; Arriel-Elias et al., 2019). In this context, our objective was to determine the efficiency of four formulations containing Pseudomonas fluorescens (BRM 32111) and Burkholderia pyrrocinia (BRM 32113) developed based from agro-
2. Material and methods 2.1. Microorganisms The bacterias P. fluorescens (BRM 32111) e B. pyrrocinia (BRM 32113), used in this study belong to the Multifunctional Collection of Microorganisms from Embrapa. The strains are preserved by Castellani methods and deep freezing, respectively. The bacterial isolates were transferred and cultured in Petri plates containing Nutrient Agar (NA), which were then incubated for 48 h at 28 °C. 2.2. Field experiments 2.2.1. Experimental area characterization The experiments were installed in twice in the same season in the years 2017 and 2018. Experiments E1 were sowed at December 5th (E1), and Experiment E2 at January 5th (E2). The experimental area is located at Fazenda Capivara, Embrapa Rice and Beans, in the municipality of Santo Antônio de Goiás, GO, Brazil (16° 28′00 “S and 49° 17′00″ W). The region presents an altitude of 823 m, the predominant climate is tropical, with two well defined seasons, one rainy (October – April) and one dry (May – September). Soil chemical analysis (0–20 cm) of the experimental area was performed according to Claessen (1997), showing that the soil presented pH (em água) 6.0, Ca 28.7 mmolc/dm3, Mg 22.8 mmolc/dm3, P 20.7 mg/dm3, K 187 mg/dm3 and 43.51 g/kg organic matter. 2.2.1.1. Experimental design. In a randomized block design both experiment, E1 and E2, were composed of 7 treatments in 4 replicates. Each plot was composed of 8 rows × 5 m with spacing between rows of 0.35 cm. The treatments consisted of: T1: Formulation 11 + BRM 32113; T2: Formulation 32 + BRM 32113; T3: Formulation 11 + BRM 32111; T4: Formulation 20 + BRM 32111; T5: BRM 32111; T6: BRM 32,113 and T7: Absolute control (H2O). 2.3. Bioformulations The bacterial strains were cultured separately in Erlenmeyers containing 500 ml of nutrient broth and incubated under constant stirring at 150 rpm for 48 h at 28 °C ( ± 2). These are the necessary conditions to ensure that both bacteria were in the stationary phase at the time of incorporation into the formulations. The development of the formulations and selection of the most efficient for P. fluorescens and B. pyrrocinia are described in Arriel-Elias et al. (2018). Formulation 11, containing glycerol, K2HPO4, NaCl and MgSO4 was used for both bacteria. Formulation 20, consisting of molasses, K2HPO4 and NaCl, was only used for P. fluorescens, and formulation 32, containing molasses and K2HPO4, used only for B. pyrrocinia. All formulations were prepared containing 60% adjuvants and 40% active ingredients. 2.4. Seed microbiolization and foliar applications Bioformulated were applied by seed microbiolization and by foliar spray pulverization. Rice seeds were immersed in the formulations containing the respective bacterial strains, or not (controls for each formulation). The seeds of the control treatment were immersed in water, and all treatments were maintained for 24 h under constant 2
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stirring at 25 °C, added to a 24 h drying period at 25 °C (Filippi et al., 2011). At 14 and 21 days after planting, the formulations containing the respective bacterial strains, or not (controls for each formulation) were spray pulverized. Control treatments were spray pulverized with water.
conditioned in paper bags and oven dried with forced air circulation at a temperature of 65 °C until reaching constant weight. Grain yield was determined by weighing the samples harvested from each plot, and the moisture content of the grains corrected to 13% and converted to kg ha−1.
2.5. Gas exchange
2.8. Statistical analysis
It was measured by using a portable gas exchange analyzer in the infrared region (LCpro+, ADC BioScientific, Hoddesdon, England). Three upland rice plants per plot were selected randomly (two leaves per plant) to perform gas exchange measurements, at the stages. Photosynthetic rate (A, μmol CO2 m−2 s−1), transpiration rate (E, mmol H2O m−2 s−1), stomatal conductance (gs, mol H2O m−2 s−1), internal CO2 concentration (Ci, vpm) and efficiency of water use (WUE) were obtained. The reading was taken from from 09:30 to 11:00 AM, and the minimum balance time for reading was 2 min, at 42 (vegetative stage) and 63 (reproductive stage) DAS for the first growing season (2017/18) and 59 (vegetative stage) and 88 (reproductive stage) DAS for the second growing season (2017/18). Samples were taken in the middle third of the first fully expanded leaf (top to base) during the first evaluation and on the flag leaf in the second evaluation in the two-year experiment. The equipment was set to use concentrations of 370–400 mol mol−1 CO2 in the air, which is the reference condition used in the IRGA phothosynthesis chamber. The photon flux density photosynthetic active (PPFD) used was 1200 μmol [quanta] m−2 s−1.
Data were submitted to analysis of variance using Statistical Package for the Social Sciences (SPSS), version 18.0. Treatments and planting times were considered fixed effects. Blocks and all block interactions were considered random effects. The averages were compared by the Tukey test and the results were considered statistically significant at p ≤ 0.05 or p ≤ 0.1. 3. Results 3.1. Gas exchange The joined statistical analysis showed significance (p < 0.1) for experiments (E1 and E2) and treatments concerning gas exchange. The analysis also showed significance in the interaction between experiments (E1 and E2) and treatments, in this way, the necessary statistical analysis unfolding were performed. At E1, during the vegetative phase, no significant differences were observed between treatments (p < 0.1). On the other hand, during the reproductive phase, all treatments presented higher rates of A, gs and WUE, when compared to the control (Table 1). In E2, during the vegetative phase, all treatments presented E, A, gs and Ci superior to the control, with emphasis on T1, T2, T4 and T5. During the reproductive period, the highest A rate was observed in T1, T2 and T4 treatments. For gs the treatments T6 and T3 highlighted, WUE higher values also observed presenting values higher than the control (Table 2).
2.6. Leaf and panicle blast assessment The area under the disease progress curve (AUDPC) was calculated from four evaluations at 20 randomly selected plants with the same physiological age. Leaf blast assessment (LBS%) at E1 was perfomed between 57 LB0, 58 LB1, 64 LB2 e 67 LB3 DAP and E2 were carried in the 22 LB0, 25 LB1, 34 LB2 and 41 LB3 dap, with the aid of a visual scale of ten degree grades (Notteghem, 1981). The severity of the panicle blast (PBS%) was determined out for E1 at 103 PB0 and 110 PB1 DAP and E2 at 104 PB0 and 113 PB1 DAP. Twenty-five panicles from each plot were randomly scored and evaluated using a six-note scale (0: no observed disease, 1: < 5%, 3: 5–10%, 5: 11–25%, 7: 26–50% e 9: more than 50%), according to (IRRI, 2013). Estimates of the area under the disease progress curve (AACPD) of leaf and panicle were calculated according to the method of Shaner and Finney (1977).
3.2. Leaf and panicle blast assessment The joint statistical analysis showed that there was a significance (p < 0.1) for experiments (E1 and E2), treatments and in the interaction between experiments (E1 and E2) and treatments. In E1, leaf blast severity (LBS), at all days evaluated, and area under the disease progress curve (AUDPC) were significantly lower in T1, T4 and T6 treatments. In E2, LBS and AUDPC were lower in treatments T1, T2, T3, T4, T5 and T6 when compared to the control (Table 3). In the panicles, all treatments differed statistically from each other. At E1, all treatments suppressed the bladder on the panicle. On the other hand, in T1, T1, T3 and T5 presented lower severity of panicle blast (PBS). As for AUCPD reduction, the most prominent treatments were T2, T3, T5 and T6 (Table 4).
2.7. Biomass and grain yield The sampling was composed of the aerial part of rice plants in 0.60 cm continuous of a row, of each plot, 101 days after planting, when 50% of the plants were in full bloom. The samples were
Table 1 Gas exchange rates of rice plants treated with bioagents P. fluorescens and B. pyrrocinia formulates or not: Photosynthesis A (μmol CO2 m−2 s−1), transpiration - E (mmol H2O m−2 s−1), stomatal conductance - gs (mol H2O m−2 s−1), internal CO2 concentration – Ci (μmol CO2 mol−1) and water use efficiency – WUE (μmol CO2 mol−1 H2O) during experiment 1 (E1), growing season 2017/18. Treatments
T1 T2 T3 T4 T5 T6 T7
Vegetative
Reprodutive
A
E
gs
Ci
WUE
A
E
gs
Ci
WUE
16.76 16.69 16.57 17.15 14.96 15.12 15.23
4.92 5.4 5.37 5.46 5.15 5.59 5.57
0.337 0.352 0.352 0.355 0.3 0.305 0.308
284.75 288.62 287.75 284.25 278.25 278.62 282.75
3.55 3.17 3.17 3.19 3.1 2.77 2.81
41.59 a 40.82 a 39.09 a 40,96 a 38.84 a 41.16 a 27.74b
9.32 a 8.51 a 8.83 a 9.12 a 10.14 a 8.64 a 12.34b
0.887 a 0.803 ab 0.708c 0.776 bc 0.823 ab 0.81 ab 0.56 d
268.5 a 254.25b 234.25 d 239.75 cd 248 bc 251.25 bc 247 bc
4.84 a 4.84 a 4.59 a 4.52 a 3.9b 4.88 a 2.24c
Analysis of variance for the physiological parameters according to the treatments: T1: Form11 + BRM32113, T2: FORM32 + BRM32113, T3: FORM11 + BRM32111, T4: FORM20 + BRM 32111, T5: BRM32111, T6: BRM32113 e T7: Absolute control. Vegetative stage 42 DAP and reprodutive 63 DAP. Means followed by the same letters in the column were not significantly different according to Tukey test (p < 0,1). 3
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Table 2 Gas exchange rates of rice plants treated with bioagents P. fluorescens and B. pyrrocinia formulates or not: Photosynthesis A (μmol CO2 m−2 s−1), transpiration - E (mmol H2O m−2 s−1), stomatal conductance - gs (mol H2O m−2 s−1), internal CO2 concentration – Ci (μmol CO2 mol−1) and water use efficiency – WUE (μmol CO2 mol−1 H2O) during experiment 2 (E2), growing season 2017/18. Vegetative
Reprodutive
Treatments
A
E
gs
Ci
WUE
A
E
gs
Ci
WUE
T1 T2 T3 T4 T5 T6 T7
49.91 a 50.0 a 46.39 ab 53.61 a 49.94 a 47.69 ab 39.00b
14.51 a 15.17 a 14.79 a 13.78 a 14.84 a 13.88 a 10.85b
1.49 a 1.45 a 1.27 ab 1.44 a 1.40 a 1.27 ab 0.93b
318.87 a 318.25 a 302.87 ab 316.75 a 301.62 ab 307.75 a 266.87b
3.51 ab 3.34 ab 3.14b 3.92 a 3.36 ab 3.57 ab 3.66 ab
36.04 a 36.32 a 33.86 ab 35.23 a 30.1b 32.19 ab 29.63b
12.21 bc 12.17 bc 11.79 bc 12.01 bc 13.93 a 12.94 ab 11.07c
0.767 ab 0.797 ab 0.686b 0.732 ab 0.722 ab 0.818 a 0.743 ab
254 a 252.5 a 222.5 bc 249.62 a 205c 236.75 ab 254.25 a
3.22 a 3.18 a 2.90 a 2.95 a 2.22b 2.61b 3.00 a
Analysis of variance for the physiological parameters according to the treatments: T1: Form11 + BRM32113, T2: FORM32 + BRM32113, T3: FORM11 + BRM32111, T4: FORM20 + BRM 32111, T5: BRM32111, T6: BRM32113 e T7: Absolute control. Vegetative stage 59 DAP and reprodutive 88 DA. Means followed by the same letters in the column were not significantly different according to Tukey test (p < 0,1).
3.3. Biomass and grain yield
Table 4 Panicule blast severity and area under disease progress in rice plants treated bioagents P. fluorescens and B. pyrrocinia formulates or not with bioaformulates or not the at experiment 1 (E1) and 2 (E2), during growing season 2017/18.
There was no statistical difference (p < 0.1) between experiments, treatments and the interaction between experiment and treatments was not significant for productivity. Concerning biomass, treatments T3 and T6 were larger than the control (Table 5). However, there was no significant difference between the interactions (time × treatment) or E1 (3,636 kg ha−1) and E2 (2,709 kg ha−1) among treatments.
First growing season
4. Discussion The search for sustainable components, to be incorporated into the integrated management for plant diseases control has been a challenge, since there are limitations on the availability of large scale biofungicides and the lack of training of commercial agents. However, largescale biofungicides production, containing bioagents such as PGRPs, requires a sustainable and stable formulation, able to bring repeatability of the results. Here we investigated the efficacy of 4 bioproducts, and demonstrated that rhizobacterias formulated from agroindustrial residues (molasses and glycerol), were as efficient as bacterial suspension. Considering the best results for each physiological parameters, treatments exerted positive effects on the physiological parameters, as photossyntetic rate increased 49% (T1, T2, T3 and T6) stomatical condutance 58% (T1, T2, T5 and T6) and water use efficiency 74% (T1, T2, T3, T4, T5 and T6). This is a very important information because, besides the biotic stress such as diseases, it is known that upland rice crop is expose to multiple abiotic stresses, including low fertility, heterogeneity of both soil and climate, and variability of precipitation. However, rice plants have superficial root systems, so low availability or water deficiency
Second growing season
Treatments
PB1 (%)
PB2 (%)
AUDPC
PB1 (%)
PB2 (%)
AUDPC
T1 T2 T3 T4 T5 T6 T7
1.25 a 1.24 a 0,13 a 0.00 a 0.44 a 0.22 a 4.39b
2.05 a 2.51 a 1.75 a 1.68 a 3.99 a 0.88 a 8.45b
20.36 a 24.1 a 10.79 a 9.38 a 23.3 a 7.04 a 71.16b
0.37 a 2 ab 1.06 a 4.12b 0.47 a 1.66 ab 2.31b
4.95 3.67 5.36 5.46 7.2 3.65 6.55
28.7 a 35.2 ab 36 ab 60.2b 37.9 ab 32.5 a 52.2 ab
Analysis of variance for biomass and productivity according to treatments: T1: Form11 + BRM32113, T2: FORM32 + BRM32113, T3: FORM11 + BRM32111, T4: FORM20 + BRM 32111, T5: BRM32111, T6: BRM32113 e T7: Absolute control. E1: PB0 – 103 e PB1 – 110 DAP e E2: PB0 – 104 e PB1 – 113 DAP. Means followed by the same letters in the column were not significantly different according to Tukey test (p < 0,1).
that occurs mainly during summer periods remains the most important factor limiting upland rice productivity. Understanding the physiological changes that occur in plants treated with formulated bioagents can help to predict their effects on crops and grain yield under abiotic stress (Tuong et al., 2000; Nascente et al., 2017a). In addition, we observed increases of 17–56% in biomass and increase in grain yield, in T1, T2, T3, T4, T5 and T6, of 481 kg ha−1, 238 kg ha−1, 133 kg ha−1 and 424 kg ha−1, 688 kg ha−1 and 427 kg ha−1, respectively, when compared to the 3054.78 kg ha−1 of the control treatment. Although there was increase in biomass (56%),
Table 3 Leaf blast severity and area under disease progress in rice plants treated bioagents P. fluorescens and B. pyrrocinia formulates or not with bioformulates or not the at experiment 1 (E1) and 2 (E2), during growing season 2017/18. Experiment 1 (E1)
Experiment 2 (E2)
Treatments
LB1 (%)
LB2 (%)
LB3 (%)
AUDPC
LB1 (%)
LB2 (%)
LB3 (%)
AUDPC
T1 T2 T3 T4 T5 T6 T7
0.73 ab 1.16 bcd 1.02 bcd 0.7 abc 1.18 cd 0.63 a 1.61 d
9.43b 8.65b 9.07b 7.67 ab 7.56 ab 5.75 a 15.5c
7.42 a 5.43 a 6.43 a 6.25 a 6.83 a 5.07 a 27.75b
80.36b 70.55 ab 75.81b 66.2 ab 68.26 ab 50.98 a 179.47c
0.90 ab 0.69 a 0.67 a 0.71 a 0.81 a 0.72 a 1.38b
2.26 a 2.28 a 1.62 a 1.70 a 2.05 a 1.60 a 5.33b
6.68 bc 4.96 ab 4.23 a 4.32 a 5.33 a 7.69 cd 11.21 d
69.89b 57.40 ab 46.29 a 47.78 ab 58.19 ab 70.48b 130.65c
Analysis of variance for panicle severity according to treatments: T1: Form11 + BRM32113, T2: FORM32 + BRM32113, T3: FORM11 + BRM32111, T4: FORM20 + BRM 32111, T5: BRM32111, T6: BRM32113 e T7: Absolute control. E1: LB0 – 57, LB1 – 58, LB2 – 64 e LB3 – 67 DAP e E2: LB0 – 22, LB1 – 25, LB2 – 34 e LB3 – 41 DAP. Means followed by the same letters in the column were not significantly different according to Tukey test (p < 0,1). 4
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addition, consumers are becoming more demanding about the quality of products consumed and with greater ecological awareness, thus questioning the use of chemical inputs. Therefore, the development and use of biopesticides is one of the viable options to meet the demands of society in the constant search for sustainable solutions. Given the data presented here, we demonstrate that the development of bioproducts, using easily accessible inputs, opens doors for small startups to invest in process innovation and standardization, with the necessary quality for large scale production, competitiveness and economic return to the sector related to this segment.
Table 5 Effect of P. fluorescens and B. pyrrocinia formulates or not on biomass and yield the grains. Treatments
Biomass
Grain yield (kg ha−1)
T1 T2 T3 T4 T5 T6 T7
132.45 145.70 175.54 134.86 159.99 175.64 112.68
3262.57 3020.00 2915.09 3205.99 3469.44 3208.61 2781.29
ab ab a ab ab a b
5. Conclusions
Analysis of variance for second panicle blast according to treatments: T1: Form11 + BRM32113, T2: FORM32 + BRM32113, T3: FORM11 + BRM32111, T4: FORM20 + BRM 32111, T5: BRM32111, T6: BRM32113 e T7: Absolute control. E1: PB0 – 103 e PB1 – 110 DAP e E2: PB0 – 104 e PB1 – 113 DAP. Means followed by the same letters in the column were not significantly different according to Tukey test (p < 0,1).
Rhizobacteria P. fluorescens and B. pyrrocinia, in formulation T1, T2 and T4, applied by seed microbiolization and by foliar pulverization, at 15 and 21 days after planting, promoted reducing the physiological damages, caused by the disease. The treatments also suppressed leaf and panicle blast, improved the yield components of upland rice plants, even under favorable conditions to disease development (planting season: E1 – December and E2 – January, temperature between 23 °C and 29 °C), with a susceptible genotype, and high relative humidity of the air. Treatments T1 and T4 can be considered an efficient biofungicides to be inserted into the integrated management, and there by reducing dependence on chemical inputs and enhancing sustainable food production. The results reported here represent a breakthrough in the development of biopesticides for application in the blast management, since it is a sustainable low cost and alternative. In addition, the inclusion of biological control in the integrated blast management will allow plant resistance genes cascade to expressed, independently of the pathogen population, ensuring the productivity potential of genetically improved cultivars, and reducing the number of fungicide applications.
the T3 treatment presented low yield, this fact mainly due, to the presence of weeds in the plots. The strains BRM 32113 and BRM 32111 are phosphatase, cellulase and siderophores producers but only BRM 32113 produces AIA and only BRM 32111 produces biofilm (Nascente et al., 2017a,b). Thus it is possible to relate that the increase in the gas exchange rates observed represents a sum of the interactions of the strains BRM 32113 and BRM 32111 with leaves and roots of rice plants, which will provide greater accumulation of biomass, increased absorption of nutrients and indirect form to increase plants resistance abiotic stresses. Generally, PGPRs contribute directly to plant growth through the uptake of nutrients (nitrogen, phosphorus and essential minerals) or by modulating phytohormone levels responsible for plant growth (Ahemad and Kibret, 2014; Sharma et al., 2016; Nascente et al., 2017a,b; Olanrewaju et al., 2017; Tsegaye et al., 2017). Studies have shown that PGPRs are also capable of acting on plant physiological responses over adverse environmental conditions (Bueno et al., 2017). Indirectly, the PGPRs can reduce or prevent the deleterious effects of diseases, by means of the producing resistance-inducing enzymes and antibiotics antagonistic to phytopathogens (Raaijmakers and Mazzola, 2012; Katiyar et al., 2017; Tsegaye et al., 2017). The present study provides direct evidence that the strains, even under field conditions, acted in the induction of the mechanisms associated of plants defense. These mechanisms are related to the activation of importants resistance-inducing enzymes, como β-1,3-glucanase (GLU), chitinase (CHI), phenylalanine ammonia lyase (PAL), lipoxygenase (LOX) and peroxidase (PO) (Filippi et al., 2011). In addition, tests conducted under controlled conditions showed that the FORM 32 + BRM 32113, a liquid formulation, reduced disease severity, increased the activity of the salicilic acid hormone and of the enzymes associated with resistance induction (Arriel-Elias et al., 2019). The suppression of 66% and 80% in leaf blast (LB), and of 50% and 80% in panicle blast (PB) in the first experiment; and the suppression of 30% and 60% in LB, and of 20% and 40% in PB, in second experiment, are some of the expected benefits for plants treated with rhizobacteria. The use of PGPRs is an alternative for plant diseases control, to reduce the number of fungicides application and to increase productivity under field conditions. However, the provision of stable and efficacy biopesticides, that can be inserted into integrated management of conventional, agroecological and organic system, is largely dependent of the formulation. In this context, formulations evaluated under field conditions, with emphasis on formulations FORM 11 + 32113, FORM 32 + 32113 and FORM 20 + 32111, were developed with excipients from agroindustrial residues, rich in nutrients that ensured the stability of strains BRM 32111 and BRM 32113 for 90 and 150 days respectively (Arriel-Elias et al., 2018). Considering the costs and benefits in reducing the impacts on the environment, biological control has become a demand of society. In
Authors contribution MAYTHSULENE INÁCIO DE SOUSA OLIVEIRA: is the first author of the study, was part of her thesis to obtain a PhD in Pharmaceutical Innovation. She was present in all study assays and responsible for writing the papper. AMANDA ABDALLAH CHAIBUB: is the second author of the study, she is PhD in Phytopathology and was present in all field assays and grain yield analyses, contribution in data analysis and manuscript. EDEMILSON CARDOSO DA CONCEIÇÃO: the author is PhD in Pharmaceutical Technological and Teacher at Federal University of Goiás. He contributed to the development of the formulations. MARCIO VINICIUS DE CARVALHO BARROS CORTES: the author is PhD student in Biochemistry and he contributed to the development of the formulations. ALAN CARLOS ALVES DE SOUZA: the author is PhD in Phytopathology and he contribution in planning of field assays. THATYANE PEREIRA de SOUSA: the author is PhD in Agronomy and she contribution in evaluation and training for IRGA data collection. MARTA CRISTINA CORSI DE FILIPPI: the author is PhD in Plant Pathotology and Microbiology, she is a researcher and responsible for the project, guiding the students in all stages of the process. She was responsible for the verification and monitoring of the field data besides, statistical analysis and besides actively participating in the writing of the paper in English. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.biocontrol.2019.104153. References Ahemad, M., Kibret, M., 2014. Mechanisms and applications of plant growth promoting rhizobacteria: current perspective. J. King Saud Univers. Sci. 26 (1). https://doi.org/
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10.1016/j.jksus.2013.05.001. Arriel-Elias, M.T., Côrtes, M.V.C., Chaibub, A.A., De Filippi, M.C.C., 2019. Induction of resistance in rice plants using bioproducts produced from Burkholderia pyrrocinia BRM 32113. Environ. Sci. Pollut. Res. Int. https://doi.org/10.1007/s11356-01905238-3. Arriel-Elias, M.T., Oliveira, M.I.S., Silva-Lobo, V.L., De Filippi, M.C.C., Babana, A.H., Conceição, E.C., Côrtes, M.V.C., 2018. Shelf life enhancement of plant growth promoting rhizobacteria using a simple formulation screening method. Afr. J. Microbiol. Res. 12 (5), 115–126. https://doi.org/10.5897/AJMR2017.8787. Bueno, A.C.S.O., Castro, G.L.S., Silva Junior, D.D., Pinheiro, H.A., Filippi, M.C.C., Silva, G.B., 2017. Response of photosynthesis and chlorophyll a fluorescence in leaf scaldinfected rice under influence of rhizobacteria and silicon fertilizer. Plant Pathol. 66 (9), 1487–1495. https://doi.org/10.1111/ppa.12690. Compant, S., Duffy, B., Nowak, J., Clément, C., Barka, E.A., 2005. Use of plant growthpromoting bacteria for biocontrol of plant diseases: principles, mechanisms of action, and future prospects. Appl. Environ. Microbiol. 71 (9), 4951–4959. https://doi.org/ 10.1128/AEM.71.9.4951-4959.2005. CONAB, 2019 Acompanhamento safra brasileira de grãos, oitavo levantamento. https:// www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja& uact=8&ved=2ahUKEwjS14_8rb7iAhUBA9QKHeRUC6wQFjAAegQIBRAB&url= https%3A%2F%2Fwww.conab.gov.br%2Finfo-agro%2Fsafras%2Fgraos%2Fboletimda-safra-de-graos&usg=AOvVaw0lTp9Gv5O5R4fo3vVGz7cr. (accessed 28 de May 2019). Fernandez, J., Orth, K., 2018. Rise of a cereal killer: the biology of Magnaporthe oryzae biotrophic growth. Trends Microbiol. 26 (7), 582–597. https://doi.org/10.1016/j. tim.2017.12.007. FAO. Food and Agriculture Organization of the United Nations, 2018. https://www. google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8 &ved=2ahUKEwjSq8LJr77iAhV9ILkGHfkNAxEQFjAAegQIAhAC&url=http%3A%2F %2Fwww.fao.org%2F3%2FCA0239EN%2Fca0239en.pdf&usg=AOvVaw0RML_ mLDrDRTL9VXhcdlYw. (accessed 28 May 2019). Filippi, M.C.C., Silva, G.B., Silva-Lobo, V.L., Côrtes, M.V.C.B., Morases, A.J.G., Prabhu, A.S., 2011. Leaf blast (Magnaporthe oryzae) suppression and growth promotion by rhizobacteria on aerobic rice in Brazil. Biol. Control 58 (2), 160–166. https://doi.org/ 10.1016/j.biocontrol.2011.04.016>. Fravel, D.R., 2005. Comercialization and implementation of biocontrole. Ann. Rev. Phytopathol. 43, 337–359. https://doi.org/10.1146/annurev.phyto.43.032904. 092924. Galinato, M.I., Moody, K., Piggin, C.M. 1999. Upland rice weeds of South and southeast Asia. Intenational Rice Research Institute. ISBN : 9712201309. Heinemann, A.B., Sentelhas, P.C., 2011. Environmental group identification for upland rice production in central Brazil. Sci. Agric. 68, 540–547. https://doi.org/10.1590/ S0103-90162011000500005. IPCC, 2014. Intergovernmental Panel on Climate Change -. Agriculture, Forestry and Other Land Use (AFOLU). In: Climate Change 2014: Mitigation of Climate Change. Disponível em: < https://www.ipcc.ch/pdf/assessment-report/ar5/wg3/ipcc_wg3_ ar5_chapter11.pdf > . (accessed 9 december 2018). IRRI, 2013. Injuries caused by diseases. Standard Evaluation System (SES) for Rice, fifth ed. International Rice Research Institute, Manila, Philippines, pp. 18–19.
Katiyar, D., Hemantaranjan, A., Singh, B., 2017. Application of plant growth promoting rhizobacteria in promising agriculture: Na Appraisal. J. Plant. Physiol. Pathol. 5, (4). https://doi.org/10.4172/2329-955X.1000168. Nascente, A.S., Filippi, M.C.C., Lanna, A.C., Souza, A.C., Silva-Lobo, V.L., Silva, G.B., 2017a. Biomass, gas exchange, and nutrient contents in upland rice plants affected by application forms of microorganism growth promoters. Environ. Sci. Pollut. Res. Int. 24 (3), 2956–2965. https://doi.org/10.1007/s11356-016-8013-2. Nascente, A.S.F., Filippi, M.C.C., Lanna, A.C., Sousa, T.P., Souza, A.C.A., Silva-Lobo, V.L., Silva, G.B., 2017b. Effects of beneficial microorganisms on lowland rice development. Environ. Sci. and Pollut. Res. Int. 24 (32), 25233–25242. https://doi.org/10.1007/ s11356-017-0212-y. Notteghem, J.L., 1981. Cooperative experiment on horizontal resistance to rice blast. BLAST and Upland Rice: Report and Recommendations from the Meeting for International Collaboration in Upland Rice Improvement. International Rice Research Institute, Los Baños, pp. 43–51. Olanrewaju, O.S., Glick, B.R., Babalola, O.O., 2017. Mechanisms of action of plant growth promoting bacteria. World J. Microbiol. Biotechnol 33 (11). https://doi.org/10. 1007/s11274-017-2364-9. Prathap, M., Ranjitha, K.B.D., 2017. Bioformulation in biological control for plant diseases. Rev. Int. J. Biotechnol. Trends Technol. 7 3, 1–8. https://doi.org/10.14445/ 22490183/IJBTT-V22P601. Raaijmakers, J.M., Mazzola, M., 2012. Diversity and natural functions of antibiotics produced by beneficial and plant pathogenic bacteria. Annu. Rev. Phytopathol. 50, 403–424. https://doi.org/10.1146/annurev-phyto-081211-172908. Rêgo, M.C.F., Ilkiu-Borges, F., Filippi, M.C.C., Gonçalves, L.A., Silva, G.B., 2014. Morphoanatomical and biochemical changes in the roots of rice plants induced by plant growth-promoting microorganisms. J. Bot. https://doi.org/10.1155/2014/ 818797. Sharma P., Kumawat K.C., Kaur S. 2016. Plant Growth Promoting Rhizobacteria in Nutrient Enrichment: Current Perspectives. In: Singh, U., Praharaj, C., Singh, S., Singh, N. (eds) Biofortification of Food Crops. Springer, New Delhi. DOI: https://doi. org/10.1007/978-81-322-2716-8_20. Selvaraj, S., Ganeshamoorthi, P., Anand, T., Raguchander, T., Seenivasan, N., Samiyappan, R., 2014. Evaluation of a liquid formulation Pseudomonas fluorescens against Fusarium oxysporum f. sp. cubense and Helicotylenchus multicinctus in banana plantation. Biol. Control 59, 345–355. https://doi.org/10.1007/s10526-014-9569-8. Shaner, G., Finney, R.F., 1977. The effects of nitrogen fertilization on the expression slowmildewing in Knox wheat. Phytopathology. https://doi.org/10.1094/Phyto-67-1051. Souza, A.C.A.D., Côrtes, M.V.C.B., Silva, G.B., Souza, T.P., Rodrigues, F.A., Filippi, M.C.C., 2015. Enzyme-induced defense response in the suppression of rice leaf blast (Magnaporthe Oryzae) by silicon fertilization and bioagents. Int. J. Res. Stud. Biosc. 3 (5), 22–32. Tsegaye, Z., Assefa, F., Beyene, D., 2017. Properties and application of plant growth promoting rhizobacteria. Int. J. Curr. Trend. Pharmacobiol. Med. Sci. 2, 30–43. https://doi.org/10.15413/ajmr.2017.0104. Tuong, T.P., Kam, S.P., Wade, L., Pandey, S., Bouman, B.A.M., Hardy, B. editors. 2000. Characterizing and understanding rainfed environments. Proceedings of the International Workshop on Characterizing and Understanding Rainfed Environments. Bali, Indonesia. Los Baños (Philippines): International Rice Research Institute. 488 p.
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Formulations of Pseudomonas fluorescens and Burkholderia pyrrocinia control rice blast of upland rice cultivated under no-tillage system Maythsulene Inácio de Sousa Oliveiraa,d, Amanda Abdallah Chaibubb,d, Thatyane Pereira Sousac, Marcio Vinicius Carvalho Barros Cortesd, Alan Carlos Alves de Souzae, ⁎ Edemilson Cardoso da Conceiçãoa, Marta Cristina Corsi de Filippid, a Pos graduate Program in Pharmaceutical Innovation, Federal University of Goiás, Rua 240, esquina com 5ª Avenida, s/n, Setor Leste Universitário, CEP: 74605-170, Goiânia, Goiás, Brazil b Departament of Phytopathology, University of Brasília, Brasília, DF CEP: 70.910-900, Brazil c Federal University of Goiás, Goiânia, GO CEP: 74.690-900, Brazil d Embrapa Rice and Beans, Rodovia GO-462, Km 12, Fazenda Capivara, CEP: 75375-000, Santo Antônio de Goiás, GO, Brazil e Federal University of Lavras, Lavras, MG 37200-000, Brazil
G R A P H I C A L A B S T R A C T
A R T I C LE I N FO
A B S T R A C T
Keywords: Biological control Rhizobacteria Magnaporthe oryzae Oryza sativa Sustainable management
Leaf blast caused by Magnaporthe oryzae is among the major diseases that limit rice productivity in the world, and control of the disease occurs, basically, through the application of fungicides. Control methods such as the application of growth promoting rhizobacteria could be inserted in the integrated management of rice blast. The objective of this work was to evaluate the potential of four liquid formulations containing Pseudomonas fluorescens (BRM 32111) and Burkholderia pyrrocina (BRM 32113) to suppress leaf blast, under field conditions. The trials were conducted at Embrapa Rice and Beans, between December 2018 and April 2019. The experiments were performed in a randomized block containing 7 treatments, 4 replicates. The treatments consisted of microbiolized seeds and sprays at 14 and 21 days after planting with: Formulation 11 + BRM 32,113 (T1); Formulation 32 + BRM 32,113 (T2); Formulation 11 + BRM 32,111 (T3): Formulation 20 + BRM 32,111 (T4); BRM 32,111 (T5); BRM 32,113 (T6) and Absolute control (water – T7). Severity of leaf blast and panicle, gas exchange and grain yield were evaluated. Plants treated with P. fluorescens (T3, T4 and T5) or B. pyrrocinia (T1, T2 and T6) presented 49%, 39%, 60%, 15% increase in the assimilation rate of CO2 (A), transpiration (E), stomatal conductance (gs) and internal CO2 concentration (Ci), respectively. All treatments were efficient in suppressing leaf and panicle blast and in promoting biomass increase in 55%. The yields of T1, T4, T5 and T6
⁎
Corresponding author at: Agricultural Microbiology Laboratory, Embrapa Rice and Beans, Santo Antônio de Goiás, GO 75375-000, Brazil. E-mail address: cristina.fi[email protected] (M.C.C.d. Filippi).
https://doi.org/10.1016/j.biocontrol.2019.104153 Received 19 August 2019; Received in revised form 4 November 2019; Accepted 19 November 2019 1049-9644/ © 2019 Elsevier Inc. All rights reserved.
Please cite this article as: Maythsulene Inácio de Sousa Oliveira, et al., Biological Control, https://doi.org/10.1016/j.biocontrol.2019.104153
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treatments increased 481, 424, 688 and 427 kg ha−1, respectively. Our results indicate that the formulated rhizobacteria have the potential to be included in the integrated management for blast control in rice fields.
1. Introduction
industrial waste and evaluated in suppress rice blast, influence in physiological parameters and productivity in field conditions.
Rice (Oryza sativa) represents the greatest crop in economics and social importance in the world, being, traditionally, one of the most consumed cereal. Brazil is among the ten largest rice producers, and stands out as the largest producer outside the Asian continent, with an estimated production of 12 million tons (National Supply Company, CONAB, 2018; Food and Agriculture Organization of the United Nations, FAO, 2018). However, rice low productivity is directly related to the diseases that affect it during crop cultivation. Rice crop ecosystems are classified as irrigated and upland. The upland system presents sustainable advantages, such as, water economy, and less emission of greenhouse gases (Intergovernmental Panel on Climate Change, IPCC, 2014). However, the low productivity of upland system relates to the heterogeneity of climate, soil fertility, rainfall distribution, weed control, and inadequate cultural practices for sustainable management of pests and diseases (Galinato et al., 1999; Heinemann and Sentelhas, 2011). The rice blast disease (Magnaporthe oryzae) represents the most destructive diseases affecting rice crops, its distribution is geographically wide, and occurs in practically all regions where rice is grown. The disease can infect leaves, stalks, panicles and consequently seeds, which can lead to 100% losses in yield destroying approximately 10–30% of the world's rice harvested (Filippi et al., 2011; Fernandez and Orth, 2018). Currently, disease control depends on integrated management that includes the planting of resistant cultivars, cultural practices and fungicides application. However, the genetic resistance of the genetically improved cultivars becomes fragile due to the high genetic variability of the pathogen population, leading to the indiscriminate use of fungicides, which has admittedly caused several environmental problems (Filippi et al., 2011; Souza et al., 2015). Nevertheless, given the projections of population growth, in contrast to the concern of society about the impacts caused by the indiscriminate use of pesticides, biological control is considered an attractive technology to be inserted into the integrated management. Its contribution to the development of sustainable agriculture is related to the reduction of environmental and social impact (Compant et al., 2005; Prathap and Ranjitha, 2017). Studies carried out under controlled conditions demonstrated the potential of the rhizobacteria Pseudomonas fluorescens (BRM 32111) and Burkholderia pyrrocinia (BRM 32113) in growth promotion, resistance induction, leaf blast suppression, dry matter gain, promote positive changes in physiological parameters and induce positives morphoanatomic in rice roots (increase in root length, root cortex expansion and increase spaces aerenchyme. (Filippi et al., 2011; Rêgo et al., 2014; Prathap and Ranjitha, 2017; Arriel-Elias et al., 2019) However, the success of biological control depends on obtaining the same promising results, recorded under controlled conditions, under natural field conditions. This implies in the development of commercial scale bioformulations containing ingredients that prolong the shelf life of microorganisms (Fravel, 2005; Selvaraj et al., 2014). Liquid formulations have advantages over other techniques because of the low development cost, ease of preparation and application, and the development of sustainable formulations with agroindustrial residues as, molasses and glycerol, enables the use of products that would be discarded in the environment (Fravel, 2005; Arriel-Elias, et al., 2018; Arriel-Elias et al., 2019). In this context, our objective was to determine the efficiency of four formulations containing Pseudomonas fluorescens (BRM 32111) and Burkholderia pyrrocinia (BRM 32113) developed based from agro-
2. Material and methods 2.1. Microorganisms The bacterias P. fluorescens (BRM 32111) e B. pyrrocinia (BRM 32113), used in this study belong to the Multifunctional Collection of Microorganisms from Embrapa. The strains are preserved by Castellani methods and deep freezing, respectively. The bacterial isolates were transferred and cultured in Petri plates containing Nutrient Agar (NA), which were then incubated for 48 h at 28 °C. 2.2. Field experiments 2.2.1. Experimental area characterization The experiments were installed in twice in the same season in the years 2017 and 2018. Experiments E1 were sowed at December 5th (E1), and Experiment E2 at January 5th (E2). The experimental area is located at Fazenda Capivara, Embrapa Rice and Beans, in the municipality of Santo Antônio de Goiás, GO, Brazil (16° 28′00 “S and 49° 17′00″ W). The region presents an altitude of 823 m, the predominant climate is tropical, with two well defined seasons, one rainy (October – April) and one dry (May – September). Soil chemical analysis (0–20 cm) of the experimental area was performed according to Claessen (1997), showing that the soil presented pH (em água) 6.0, Ca 28.7 mmolc/dm3, Mg 22.8 mmolc/dm3, P 20.7 mg/dm3, K 187 mg/dm3 and 43.51 g/kg organic matter. 2.2.1.1. Experimental design. In a randomized block design both experiment, E1 and E2, were composed of 7 treatments in 4 replicates. Each plot was composed of 8 rows × 5 m with spacing between rows of 0.35 cm. The treatments consisted of: T1: Formulation 11 + BRM 32113; T2: Formulation 32 + BRM 32113; T3: Formulation 11 + BRM 32111; T4: Formulation 20 + BRM 32111; T5: BRM 32111; T6: BRM 32,113 and T7: Absolute control (H2O). 2.3. Bioformulations The bacterial strains were cultured separately in Erlenmeyers containing 500 ml of nutrient broth and incubated under constant stirring at 150 rpm for 48 h at 28 °C ( ± 2). These are the necessary conditions to ensure that both bacteria were in the stationary phase at the time of incorporation into the formulations. The development of the formulations and selection of the most efficient for P. fluorescens and B. pyrrocinia are described in Arriel-Elias et al. (2018). Formulation 11, containing glycerol, K2HPO4, NaCl and MgSO4 was used for both bacteria. Formulation 20, consisting of molasses, K2HPO4 and NaCl, was only used for P. fluorescens, and formulation 32, containing molasses and K2HPO4, used only for B. pyrrocinia. All formulations were prepared containing 60% adjuvants and 40% active ingredients. 2.4. Seed microbiolization and foliar applications Bioformulated were applied by seed microbiolization and by foliar spray pulverization. Rice seeds were immersed in the formulations containing the respective bacterial strains, or not (controls for each formulation). The seeds of the control treatment were immersed in water, and all treatments were maintained for 24 h under constant 2
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stirring at 25 °C, added to a 24 h drying period at 25 °C (Filippi et al., 2011). At 14 and 21 days after planting, the formulations containing the respective bacterial strains, or not (controls for each formulation) were spray pulverized. Control treatments were spray pulverized with water.
conditioned in paper bags and oven dried with forced air circulation at a temperature of 65 °C until reaching constant weight. Grain yield was determined by weighing the samples harvested from each plot, and the moisture content of the grains corrected to 13% and converted to kg ha−1.
2.5. Gas exchange
2.8. Statistical analysis
It was measured by using a portable gas exchange analyzer in the infrared region (LCpro+, ADC BioScientific, Hoddesdon, England). Three upland rice plants per plot were selected randomly (two leaves per plant) to perform gas exchange measurements, at the stages. Photosynthetic rate (A, μmol CO2 m−2 s−1), transpiration rate (E, mmol H2O m−2 s−1), stomatal conductance (gs, mol H2O m−2 s−1), internal CO2 concentration (Ci, vpm) and efficiency of water use (WUE) were obtained. The reading was taken from from 09:30 to 11:00 AM, and the minimum balance time for reading was 2 min, at 42 (vegetative stage) and 63 (reproductive stage) DAS for the first growing season (2017/18) and 59 (vegetative stage) and 88 (reproductive stage) DAS for the second growing season (2017/18). Samples were taken in the middle third of the first fully expanded leaf (top to base) during the first evaluation and on the flag leaf in the second evaluation in the two-year experiment. The equipment was set to use concentrations of 370–400 mol mol−1 CO2 in the air, which is the reference condition used in the IRGA phothosynthesis chamber. The photon flux density photosynthetic active (PPFD) used was 1200 μmol [quanta] m−2 s−1.
Data were submitted to analysis of variance using Statistical Package for the Social Sciences (SPSS), version 18.0. Treatments and planting times were considered fixed effects. Blocks and all block interactions were considered random effects. The averages were compared by the Tukey test and the results were considered statistically significant at p ≤ 0.05 or p ≤ 0.1. 3. Results 3.1. Gas exchange The joined statistical analysis showed significance (p < 0.1) for experiments (E1 and E2) and treatments concerning gas exchange. The analysis also showed significance in the interaction between experiments (E1 and E2) and treatments, in this way, the necessary statistical analysis unfolding were performed. At E1, during the vegetative phase, no significant differences were observed between treatments (p < 0.1). On the other hand, during the reproductive phase, all treatments presented higher rates of A, gs and WUE, when compared to the control (Table 1). In E2, during the vegetative phase, all treatments presented E, A, gs and Ci superior to the control, with emphasis on T1, T2, T4 and T5. During the reproductive period, the highest A rate was observed in T1, T2 and T4 treatments. For gs the treatments T6 and T3 highlighted, WUE higher values also observed presenting values higher than the control (Table 2).
2.6. Leaf and panicle blast assessment The area under the disease progress curve (AUDPC) was calculated from four evaluations at 20 randomly selected plants with the same physiological age. Leaf blast assessment (LBS%) at E1 was perfomed between 57 LB0, 58 LB1, 64 LB2 e 67 LB3 DAP and E2 were carried in the 22 LB0, 25 LB1, 34 LB2 and 41 LB3 dap, with the aid of a visual scale of ten degree grades (Notteghem, 1981). The severity of the panicle blast (PBS%) was determined out for E1 at 103 PB0 and 110 PB1 DAP and E2 at 104 PB0 and 113 PB1 DAP. Twenty-five panicles from each plot were randomly scored and evaluated using a six-note scale (0: no observed disease, 1: < 5%, 3: 5–10%, 5: 11–25%, 7: 26–50% e 9: more than 50%), according to (IRRI, 2013). Estimates of the area under the disease progress curve (AACPD) of leaf and panicle were calculated according to the method of Shaner and Finney (1977).
3.2. Leaf and panicle blast assessment The joint statistical analysis showed that there was a significance (p < 0.1) for experiments (E1 and E2), treatments and in the interaction between experiments (E1 and E2) and treatments. In E1, leaf blast severity (LBS), at all days evaluated, and area under the disease progress curve (AUDPC) were significantly lower in T1, T4 and T6 treatments. In E2, LBS and AUDPC were lower in treatments T1, T2, T3, T4, T5 and T6 when compared to the control (Table 3). In the panicles, all treatments differed statistically from each other. At E1, all treatments suppressed the bladder on the panicle. On the other hand, in T1, T1, T3 and T5 presented lower severity of panicle blast (PBS). As for AUCPD reduction, the most prominent treatments were T2, T3, T5 and T6 (Table 4).
2.7. Biomass and grain yield The sampling was composed of the aerial part of rice plants in 0.60 cm continuous of a row, of each plot, 101 days after planting, when 50% of the plants were in full bloom. The samples were
Table 1 Gas exchange rates of rice plants treated with bioagents P. fluorescens and B. pyrrocinia formulates or not: Photosynthesis A (μmol CO2 m−2 s−1), transpiration - E (mmol H2O m−2 s−1), stomatal conductance - gs (mol H2O m−2 s−1), internal CO2 concentration – Ci (μmol CO2 mol−1) and water use efficiency – WUE (μmol CO2 mol−1 H2O) during experiment 1 (E1), growing season 2017/18. Treatments
T1 T2 T3 T4 T5 T6 T7
Vegetative
Reprodutive
A
E
gs
Ci
WUE
A
E
gs
Ci
WUE
16.76 16.69 16.57 17.15 14.96 15.12 15.23
4.92 5.4 5.37 5.46 5.15 5.59 5.57
0.337 0.352 0.352 0.355 0.3 0.305 0.308
284.75 288.62 287.75 284.25 278.25 278.62 282.75
3.55 3.17 3.17 3.19 3.1 2.77 2.81
41.59 a 40.82 a 39.09 a 40,96 a 38.84 a 41.16 a 27.74b
9.32 a 8.51 a 8.83 a 9.12 a 10.14 a 8.64 a 12.34b
0.887 a 0.803 ab 0.708c 0.776 bc 0.823 ab 0.81 ab 0.56 d
268.5 a 254.25b 234.25 d 239.75 cd 248 bc 251.25 bc 247 bc
4.84 a 4.84 a 4.59 a 4.52 a 3.9b 4.88 a 2.24c
Analysis of variance for the physiological parameters according to the treatments: T1: Form11 + BRM32113, T2: FORM32 + BRM32113, T3: FORM11 + BRM32111, T4: FORM20 + BRM 32111, T5: BRM32111, T6: BRM32113 e T7: Absolute control. Vegetative stage 42 DAP and reprodutive 63 DAP. Means followed by the same letters in the column were not significantly different according to Tukey test (p < 0,1). 3
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Table 2 Gas exchange rates of rice plants treated with bioagents P. fluorescens and B. pyrrocinia formulates or not: Photosynthesis A (μmol CO2 m−2 s−1), transpiration - E (mmol H2O m−2 s−1), stomatal conductance - gs (mol H2O m−2 s−1), internal CO2 concentration – Ci (μmol CO2 mol−1) and water use efficiency – WUE (μmol CO2 mol−1 H2O) during experiment 2 (E2), growing season 2017/18. Vegetative
Reprodutive
Treatments
A
E
gs
Ci
WUE
A
E
gs
Ci
WUE
T1 T2 T3 T4 T5 T6 T7
49.91 a 50.0 a 46.39 ab 53.61 a 49.94 a 47.69 ab 39.00b
14.51 a 15.17 a 14.79 a 13.78 a 14.84 a 13.88 a 10.85b
1.49 a 1.45 a 1.27 ab 1.44 a 1.40 a 1.27 ab 0.93b
318.87 a 318.25 a 302.87 ab 316.75 a 301.62 ab 307.75 a 266.87b
3.51 ab 3.34 ab 3.14b 3.92 a 3.36 ab 3.57 ab 3.66 ab
36.04 a 36.32 a 33.86 ab 35.23 a 30.1b 32.19 ab 29.63b
12.21 bc 12.17 bc 11.79 bc 12.01 bc 13.93 a 12.94 ab 11.07c
0.767 ab 0.797 ab 0.686b 0.732 ab 0.722 ab 0.818 a 0.743 ab
254 a 252.5 a 222.5 bc 249.62 a 205c 236.75 ab 254.25 a
3.22 a 3.18 a 2.90 a 2.95 a 2.22b 2.61b 3.00 a
Analysis of variance for the physiological parameters according to the treatments: T1: Form11 + BRM32113, T2: FORM32 + BRM32113, T3: FORM11 + BRM32111, T4: FORM20 + BRM 32111, T5: BRM32111, T6: BRM32113 e T7: Absolute control. Vegetative stage 59 DAP and reprodutive 88 DA. Means followed by the same letters in the column were not significantly different according to Tukey test (p < 0,1).
3.3. Biomass and grain yield
Table 4 Panicule blast severity and area under disease progress in rice plants treated bioagents P. fluorescens and B. pyrrocinia formulates or not with bioaformulates or not the at experiment 1 (E1) and 2 (E2), during growing season 2017/18.
There was no statistical difference (p < 0.1) between experiments, treatments and the interaction between experiment and treatments was not significant for productivity. Concerning biomass, treatments T3 and T6 were larger than the control (Table 5). However, there was no significant difference between the interactions (time × treatment) or E1 (3,636 kg ha−1) and E2 (2,709 kg ha−1) among treatments.
First growing season
4. Discussion The search for sustainable components, to be incorporated into the integrated management for plant diseases control has been a challenge, since there are limitations on the availability of large scale biofungicides and the lack of training of commercial agents. However, largescale biofungicides production, containing bioagents such as PGRPs, requires a sustainable and stable formulation, able to bring repeatability of the results. Here we investigated the efficacy of 4 bioproducts, and demonstrated that rhizobacterias formulated from agroindustrial residues (molasses and glycerol), were as efficient as bacterial suspension. Considering the best results for each physiological parameters, treatments exerted positive effects on the physiological parameters, as photossyntetic rate increased 49% (T1, T2, T3 and T6) stomatical condutance 58% (T1, T2, T5 and T6) and water use efficiency 74% (T1, T2, T3, T4, T5 and T6). This is a very important information because, besides the biotic stress such as diseases, it is known that upland rice crop is expose to multiple abiotic stresses, including low fertility, heterogeneity of both soil and climate, and variability of precipitation. However, rice plants have superficial root systems, so low availability or water deficiency
Second growing season
Treatments
PB1 (%)
PB2 (%)
AUDPC
PB1 (%)
PB2 (%)
AUDPC
T1 T2 T3 T4 T5 T6 T7
1.25 a 1.24 a 0,13 a 0.00 a 0.44 a 0.22 a 4.39b
2.05 a 2.51 a 1.75 a 1.68 a 3.99 a 0.88 a 8.45b
20.36 a 24.1 a 10.79 a 9.38 a 23.3 a 7.04 a 71.16b
0.37 a 2 ab 1.06 a 4.12b 0.47 a 1.66 ab 2.31b
4.95 3.67 5.36 5.46 7.2 3.65 6.55
28.7 a 35.2 ab 36 ab 60.2b 37.9 ab 32.5 a 52.2 ab
Analysis of variance for biomass and productivity according to treatments: T1: Form11 + BRM32113, T2: FORM32 + BRM32113, T3: FORM11 + BRM32111, T4: FORM20 + BRM 32111, T5: BRM32111, T6: BRM32113 e T7: Absolute control. E1: PB0 – 103 e PB1 – 110 DAP e E2: PB0 – 104 e PB1 – 113 DAP. Means followed by the same letters in the column were not significantly different according to Tukey test (p < 0,1).
that occurs mainly during summer periods remains the most important factor limiting upland rice productivity. Understanding the physiological changes that occur in plants treated with formulated bioagents can help to predict their effects on crops and grain yield under abiotic stress (Tuong et al., 2000; Nascente et al., 2017a). In addition, we observed increases of 17–56% in biomass and increase in grain yield, in T1, T2, T3, T4, T5 and T6, of 481 kg ha−1, 238 kg ha−1, 133 kg ha−1 and 424 kg ha−1, 688 kg ha−1 and 427 kg ha−1, respectively, when compared to the 3054.78 kg ha−1 of the control treatment. Although there was increase in biomass (56%),
Table 3 Leaf blast severity and area under disease progress in rice plants treated bioagents P. fluorescens and B. pyrrocinia formulates or not with bioformulates or not the at experiment 1 (E1) and 2 (E2), during growing season 2017/18. Experiment 1 (E1)
Experiment 2 (E2)
Treatments
LB1 (%)
LB2 (%)
LB3 (%)
AUDPC
LB1 (%)
LB2 (%)
LB3 (%)
AUDPC
T1 T2 T3 T4 T5 T6 T7
0.73 ab 1.16 bcd 1.02 bcd 0.7 abc 1.18 cd 0.63 a 1.61 d
9.43b 8.65b 9.07b 7.67 ab 7.56 ab 5.75 a 15.5c
7.42 a 5.43 a 6.43 a 6.25 a 6.83 a 5.07 a 27.75b
80.36b 70.55 ab 75.81b 66.2 ab 68.26 ab 50.98 a 179.47c
0.90 ab 0.69 a 0.67 a 0.71 a 0.81 a 0.72 a 1.38b
2.26 a 2.28 a 1.62 a 1.70 a 2.05 a 1.60 a 5.33b
6.68 bc 4.96 ab 4.23 a 4.32 a 5.33 a 7.69 cd 11.21 d
69.89b 57.40 ab 46.29 a 47.78 ab 58.19 ab 70.48b 130.65c
Analysis of variance for panicle severity according to treatments: T1: Form11 + BRM32113, T2: FORM32 + BRM32113, T3: FORM11 + BRM32111, T4: FORM20 + BRM 32111, T5: BRM32111, T6: BRM32113 e T7: Absolute control. E1: LB0 – 57, LB1 – 58, LB2 – 64 e LB3 – 67 DAP e E2: LB0 – 22, LB1 – 25, LB2 – 34 e LB3 – 41 DAP. Means followed by the same letters in the column were not significantly different according to Tukey test (p < 0,1). 4
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addition, consumers are becoming more demanding about the quality of products consumed and with greater ecological awareness, thus questioning the use of chemical inputs. Therefore, the development and use of biopesticides is one of the viable options to meet the demands of society in the constant search for sustainable solutions. Given the data presented here, we demonstrate that the development of bioproducts, using easily accessible inputs, opens doors for small startups to invest in process innovation and standardization, with the necessary quality for large scale production, competitiveness and economic return to the sector related to this segment.
Table 5 Effect of P. fluorescens and B. pyrrocinia formulates or not on biomass and yield the grains. Treatments
Biomass
Grain yield (kg ha−1)
T1 T2 T3 T4 T5 T6 T7
132.45 145.70 175.54 134.86 159.99 175.64 112.68
3262.57 3020.00 2915.09 3205.99 3469.44 3208.61 2781.29
ab ab a ab ab a b
5. Conclusions
Analysis of variance for second panicle blast according to treatments: T1: Form11 + BRM32113, T2: FORM32 + BRM32113, T3: FORM11 + BRM32111, T4: FORM20 + BRM 32111, T5: BRM32111, T6: BRM32113 e T7: Absolute control. E1: PB0 – 103 e PB1 – 110 DAP e E2: PB0 – 104 e PB1 – 113 DAP. Means followed by the same letters in the column were not significantly different according to Tukey test (p < 0,1).
Rhizobacteria P. fluorescens and B. pyrrocinia, in formulation T1, T2 and T4, applied by seed microbiolization and by foliar pulverization, at 15 and 21 days after planting, promoted reducing the physiological damages, caused by the disease. The treatments also suppressed leaf and panicle blast, improved the yield components of upland rice plants, even under favorable conditions to disease development (planting season: E1 – December and E2 – January, temperature between 23 °C and 29 °C), with a susceptible genotype, and high relative humidity of the air. Treatments T1 and T4 can be considered an efficient biofungicides to be inserted into the integrated management, and there by reducing dependence on chemical inputs and enhancing sustainable food production. The results reported here represent a breakthrough in the development of biopesticides for application in the blast management, since it is a sustainable low cost and alternative. In addition, the inclusion of biological control in the integrated blast management will allow plant resistance genes cascade to expressed, independently of the pathogen population, ensuring the productivity potential of genetically improved cultivars, and reducing the number of fungicide applications.
the T3 treatment presented low yield, this fact mainly due, to the presence of weeds in the plots. The strains BRM 32113 and BRM 32111 are phosphatase, cellulase and siderophores producers but only BRM 32113 produces AIA and only BRM 32111 produces biofilm (Nascente et al., 2017a,b). Thus it is possible to relate that the increase in the gas exchange rates observed represents a sum of the interactions of the strains BRM 32113 and BRM 32111 with leaves and roots of rice plants, which will provide greater accumulation of biomass, increased absorption of nutrients and indirect form to increase plants resistance abiotic stresses. Generally, PGPRs contribute directly to plant growth through the uptake of nutrients (nitrogen, phosphorus and essential minerals) or by modulating phytohormone levels responsible for plant growth (Ahemad and Kibret, 2014; Sharma et al., 2016; Nascente et al., 2017a,b; Olanrewaju et al., 2017; Tsegaye et al., 2017). Studies have shown that PGPRs are also capable of acting on plant physiological responses over adverse environmental conditions (Bueno et al., 2017). Indirectly, the PGPRs can reduce or prevent the deleterious effects of diseases, by means of the producing resistance-inducing enzymes and antibiotics antagonistic to phytopathogens (Raaijmakers and Mazzola, 2012; Katiyar et al., 2017; Tsegaye et al., 2017). The present study provides direct evidence that the strains, even under field conditions, acted in the induction of the mechanisms associated of plants defense. These mechanisms are related to the activation of importants resistance-inducing enzymes, como β-1,3-glucanase (GLU), chitinase (CHI), phenylalanine ammonia lyase (PAL), lipoxygenase (LOX) and peroxidase (PO) (Filippi et al., 2011). In addition, tests conducted under controlled conditions showed that the FORM 32 + BRM 32113, a liquid formulation, reduced disease severity, increased the activity of the salicilic acid hormone and of the enzymes associated with resistance induction (Arriel-Elias et al., 2019). The suppression of 66% and 80% in leaf blast (LB), and of 50% and 80% in panicle blast (PB) in the first experiment; and the suppression of 30% and 60% in LB, and of 20% and 40% in PB, in second experiment, are some of the expected benefits for plants treated with rhizobacteria. The use of PGPRs is an alternative for plant diseases control, to reduce the number of fungicides application and to increase productivity under field conditions. However, the provision of stable and efficacy biopesticides, that can be inserted into integrated management of conventional, agroecological and organic system, is largely dependent of the formulation. In this context, formulations evaluated under field conditions, with emphasis on formulations FORM 11 + 32113, FORM 32 + 32113 and FORM 20 + 32111, were developed with excipients from agroindustrial residues, rich in nutrients that ensured the stability of strains BRM 32111 and BRM 32113 for 90 and 150 days respectively (Arriel-Elias et al., 2018). Considering the costs and benefits in reducing the impacts on the environment, biological control has become a demand of society. In
Authors contribution MAYTHSULENE INÁCIO DE SOUSA OLIVEIRA: is the first author of the study, was part of her thesis to obtain a PhD in Pharmaceutical Innovation. She was present in all study assays and responsible for writing the papper. AMANDA ABDALLAH CHAIBUB: is the second author of the study, she is PhD in Phytopathology and was present in all field assays and grain yield analyses, contribution in data analysis and manuscript. EDEMILSON CARDOSO DA CONCEIÇÃO: the author is PhD in Pharmaceutical Technological and Teacher at Federal University of Goiás. He contributed to the development of the formulations. MARCIO VINICIUS DE CARVALHO BARROS CORTES: the author is PhD student in Biochemistry and he contributed to the development of the formulations. ALAN CARLOS ALVES DE SOUZA: the author is PhD in Phytopathology and he contribution in planning of field assays. THATYANE PEREIRA de SOUSA: the author is PhD in Agronomy and she contribution in evaluation and training for IRGA data collection. MARTA CRISTINA CORSI DE FILIPPI: the author is PhD in Plant Pathotology and Microbiology, she is a researcher and responsible for the project, guiding the students in all stages of the process. She was responsible for the verification and monitoring of the field data besides, statistical analysis and besides actively participating in the writing of the paper in English. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.biocontrol.2019.104153. References Ahemad, M., Kibret, M., 2014. Mechanisms and applications of plant growth promoting rhizobacteria: current perspective. J. King Saud Univers. Sci. 26 (1). https://doi.org/
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