The Use of Plant Growth Promoting Rhizobacteria to Reduce Greenhouse Gases in Strawberry Cultivation under Different Soil Moisture Conditions

Paliwoda, Dominika; Mikiciuk, Grzegorz; Mikiciuk, M.; Miller, Tymoteusz; Kisiel, Anna; Sas-Paszt, Lidia; Kozioł, Agnieszka; Brysiewicz, Adam

doi:10.3390/agronomy13030754

Cited by 3 publications

(5 citation statements)

References 45 publications

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“…The use of microorganisms can either reduce or have no effect on CO 2 emissions, depending on a variety of abiotic (moisture conditions, C and N substrates, SOM, fertilization, etc.) and biotic (microbial strains, soil enzymes, and microbial activity) factors [37,93,94]. Previous studies have also reported no effect of fertilization rates on CH 4 emissions [93,95,96].…”

Section: Ghg Emissionsmentioning

confidence: 89%

“…The net transfer of biologically fixed N directly from the bacteria to the host plant occurs concurrently with a significant transfer of photosynthetically fixed plant carbon to the N-fixing bacteria [34]. According to various studies, the inoculation of PGPM significantly reduces GHG emissions depending on the inoculation dose, the different humidity levels of the growth substrate, and the C and N availability of the soil [35][36][37]. This could be critical in evaluating and mitigating the environmental impacts of various agricultural management practices.…”

Section: Introductionmentioning

confidence: 99%

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Effect of Biofertilizers on Broccoli Yield and Soil Quality Indicators

Ollio,

Santás-Miguel,

Gómez

et al. 2023

Horticulturae

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High rates of fertilizer applications potentially have significant environmental consequences, such as soil and water contamination and biodiversity loss. This study aimed to compare the use of biofertilizers and inorganic fertilizers in a broccoli crop to determine their impact on soil microorganism abundance, microbial community structure, functional gene diversity, yield, and greenhouse gas emissions. Four different fertilization treatments were designed: (i) inorganic fertilizers applied at a rate to cover the nutritional demands of the crop (F100); (ii) 50% of the rate of inorganic fertilizers added in F100 (F50); (iii) F50 + the application of a formulation of various bacteria (BA); and (iv) F50 + the application of a formulation of bacteria and non-mycorrhizal fungi (BA + FU). The results showed that reduced fertilization and the addition of both biofertilizer products had no significant effect on soil nutrients, microbial population, microbial activity, or yield when compared to conventional inorganic fertilization. Thus, microbial inoculants were ineffective in enhancing soil microbial abundance and activity, and there were no changes in GHG emissions or crop yields. Nonetheless, crop yield was positively related to total soil N, microbial activity, and CO2 emissions, confirming the positive effect of soil biodiversity on production. The application of biofertilizers can help reduce mineral fertilization in a broccoli crop with no negative effect on yield.

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Section: Ghg Emissionsmentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Effect of Biofertilizers on Broccoli Yield and Soil Quality Indicators

Ollio,

Santás-Miguel,

Gómez

et al. 2023

Horticulturae

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“…The studies employed a range of methods to assess the effects of the microbial strains and drought conditions on the plants. These included the following [30,31]:…”

Section: Data Collection and Measurement Methodsmentioning

confidence: 99%

“…The data used in this study were derived from two previous studies on the effects of rhizosphere bacteria on strawberry plants under water deficit and the use of plantgrowth-promoting rhizobacteria to reduce greenhouse gasses in strawberry cultivation under different soil moisture conditions [30,31].…”

Section: Description Of the Data On Microbial Strains And Drought Con...mentioning

confidence: 99%

Machine Learning Approaches for Forecasting the Best Microbial Strains to Alleviate Drought Impact in Agriculture

Miller,

Mikiciuk,

Kisiel

et al. 2023

Agriculture

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Drought conditions pose significant challenges to sustainable agriculture and food security. Identifying microbial strains that can mitigate drought effects is crucial to enhance crop resilience and productivity. This study presents a comprehensive comparison of several machine learning models, including Random Forest, Decision Tree, XGBoost, Support Vector Machine (SVM), and Artificial Neural Network (ANN), to predict optimal microbial strains for this purpose. Models were assessed on multiple metrics, such as accuracy, standard deviation of results, gains, total computation time, and training time per 1000 rows of data. Notably, the Gradient Boosted Trees model outperformed others in accuracy but required extensive computational resources. This underscores the balance between accuracy and computational efficiency in machine learning applications. Leveraging machine learning for selecting microbial strains signifies a leap beyond traditional methods, offering improved efficiency and efficacy. These insights hold profound implications for agriculture, especially concerning drought mitigation, thus furthering the cause of sustainable agriculture and ensuring food security.

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“…Paliwoda et al [9] assessed plant growth-promoting rhizobacteria (PGPR) to determine their potential in reducing greenhouse gas emissions in strawberry cultivation. Their study involved the inoculation of various bacterial strains and manipulation of soil moisture levels to measure the emissions of NH 3 , CO 2 , N 2 O, and CH 4 .…”

Section: Impact Of Crop Management On Greenhouse Gas Emissionsmentioning

confidence: 99%