Finding optimal microorganisms to increase crop productivity and sustainability under drought – a structured reflection

Author(s): Ana Paula Rosa, Teresa Dias, Abdul M. Mouazen, Cristina Cruz & Margarida Maria Santana

Published in: Microorganisms, 2023:9

DOI: https://doi.org/10.1080/17429145.2023.2178680

Abstract: Considering the more frequent and longer drought events due to climate change, improving plant drought tolerance became a priority. The search for plant growth promoting rhizobacteria (PGPR) able to improve plant drought tolerance has been long addressed, but with inconsistent results. Here, we summarize the PGPR mechanisms that improve plant drought tolerance, identify the pitfalls in current PGPR isolation and selection routines, and discuss the key points to define new strategies to get optimal PGPR for plant drought tolerance. Drought and host genotype impact rhizo-communities, and host-mediated selection strategies may be used to obtain a drought-adapted rhizomicrobiome that can be a source for PGPR isolation. Alternatively, an integrated omics-level analysis can improve our knowledge on the mechanisms of rhizomicrobiome construction, and a targeted approach can be designed, which will be focused on key PGP traits. New strategies to build PGPR consortia for improvement of plant drought tolerance are also suggested.

Site-Specific Seeding for Maize Production Using Management Zone Maps Delineated with Multi-sensors Data Fusion Scheme

Author(s): Munnaf, M.A., Haesaert, G., Mouazen, A.M.

Published in: 2022. Soil Tillage Res. 220, 1-16

DOI: https://doi.org/10.1016/j.still.2022.105377

Abstract: Uniform rate seeding (URS) density may result in under-or over-optimal plant population that negatively affects crop growth and yield. Site-specific seeding (SSS) is one of the solutions to manage in-field soil variation by optimizing the input seed rate to match soil fertility. This study has evaluated the agronomic and economic response of maize to SSS compared to the URS using a data fusion scheme. Two fields of 5.5 ha and 10 ha in Belgium and France, respectively, were scanned using an on-line visible and near-infrared spectroscopy sensor to measure soil pH, organic carbon (OC), phosphorus (P), potassium (K), magnesium (Mg), calcium (Ca), sodium (Na), moisture content (MC), and cation exchange capacity (CEC). Crop normalized difference vegetation indices (NDVI) were retrieved from several Sentinel-2 images. Measured crop yield, retrieved NDVI and on-line measured soil attributes were then fussed using k-means clustering algorithm to delineate management zone (MZ) maps, whose classes were ranked based on their fertility level and crop yield. A parallel strips experiment was overlaid upon the MZ map, to allow comparing the performance of SSS against URS. Two SSS treatments were implemented in the strip experiment, e.g., the “Kings ” approach that recommended the highest seeding density for the highest fertile MZ class and vice versa, and the “Robin Hood ” approach followed the opposite principle. Results revealed that SSS treatments increased maize grain yield by 0.25-0.70 Mg ha(-1) and thus improved gross margin by 26.7-92.67 euro ha(-1), compared to the URS. Besides, the SSS-Kings treatment outperformed the URS and SSS-Robin Hood in both fields, whereas the SSS-Robin Hood outperformed the URS treatment only in one field. Soil OC, MC, Mg, and pH revealed a positive correlation each with grain yield in the SSS-Kings treatment. The SSS-Kings treatment is therefore recommended to manage in-field soil variation, which can result in optimizing input seed rates for increasing maize productivity and profitability.

The Potential of Ectomycorrhizal Fungi to Modulate below and Aboveground Communities May Be Mediated by 1-Octen-3-ol

Author(s): Inês Ferreira, Teresa Dias, Cristina Cruz

Published in: Journal of Fungi 2023, 9(2), 180; 
DOI: 10.3390/jof9020180
Abstract: It is known that ectomycorrhizal (ECM) fungi can modulate below and aboveground communities. They are a key part of belowground communication as they produce a vast array of metabolites, including volatile organic compounds (VOCs) such as 1-octen-3-ol. Here, we tested if the VOC 1-octen-3-ol may be involved in the ECM fungal mechanisms that modulate below and aboveground communities. For that, we conducted three in vitro assays with ECM fungi and the 1-octen-3-ol volatile to (i) explore the effects of mycelium growth of three ECM species, (ii) investigate the impact on the germination of six host Cistaceae species, and (iii) study the impact on host plant traits. The effects of 1-octen-3-ol on mycelium growth of the three ECM species depended on the dose and species: Boletus reticulatus was the most sensitive species to the low (VOC) dose, while T. leptoderma was the most tolerant. In general, the presence of the ECM fungi resulted in higher seed germination, while 1-octen-3-ol resulted in lower seed germination. The combined application of the ECM fungus and the volatile further inhibited seed germination, possibly due to the accumulation of 1-octen-3-ol above the plant species’ threshold. Seed germination and plant development of Cistaceae species were influenced by ECM fungal volatiles, suggesting that 1-octen-3-ol may mediate changes in below and aboveground communities.

Non-Toxic Increases in Nitrogen Availability Can Improve the Ability of the Soil Lichen Cladonia rangiferina to Cope with Environmental Changes

Author(s):  Morillas, L.; Roales J.; Cruz, C.; Munzi S.
Published in: Journal of Fung,i 2022, 8(4), 333;
DOI: 10.3390/jof8040333
Abstract: Climate change and atmospheric nitrogen (N) deposition on drylands are greatly threatening these especially vulnerable areas. Soil biocrust-forming lichens in drylands can provide early indicators of these disturbances and play a pivotal role, as they contribute to key ecosystem services. In this study, we explored the effects of different long-term water availability regimes simulating climate changes and their interaction with N addition on the physiological response of the soil lichen Cladonia rangiferina. Three sets of this lichen were subjected to control, reduced watering, and reduced watering and N addition (40 kg NH₄NO₃ ha⁻¹ year⁻¹) treatments for 16 months. Finally, all samples were subjected to daily hydration cycles with N-enriched water at two levels (40 and 80 kg NH₄NO₃ ha⁻¹ year⁻¹) for 23 days. We found that reduced watering significantly decreased the vitality of this lichen, whereas N addition unexpectedly helped lichens subjected to reduced watering to cope with stress produced by high temperatures. We also found that long-term exposure to N addition contributed to the acclimation to higher N availability. Overall, our data suggest that the interactions between reduced watering and increased N supply and temperature have an important potential to reduce the physiological performance of this soil lichen.

Spectra Fusion of Mid-Infrared (MIR) and X-ray Fluorescence (XRF) Spectroscopy for Estimation of Selected Soil Fertility Attributes

Author(s): Lalit M. Kandpal, Muhammad A. Munnaf ,Cristina Cruz and Abdul M. Mouazen.
Published in: Sensors 2022, 22(9), 3459
DOI: 10.3390/s22093459
Abdul Mouazen, professor at the University of Ghent and member of the SOILdarity team, is the guest editor of the special issue “Precision Agriculture ans Sensor Systems”, an initiative taken in the Framework of the MDPI jornal “Sensors”. The aim of this issue is to summarize cutting-edge research on the development and application of new sensor systems to support precision agriculture, and to highlight novel approaches to characterize soil, plants and animals as well as new ways to use sensor data to support the decision-making process. The SOILdarity team lead by Prof Mouazen took this opportunity to publish the work entitled “Spectra Fusion of Mid-Infrared (MIR) and X-ray Fluorescence (XRF) Spectroscopy for Estimation of Selected Soil Fertility Attributes”. The work used two proximal soil sensing techniques mid-infrared (MIR) and X-ray fluorescence (XRF) spectroscopy to assess seven soil fertility attributes: pH, organic carbon, phosphorous, potassium, magnesium, calcium, and moisture content (Figure). The performance of the several spectra fusion models, when compared with those obtained from single sensors, improved performance prediction for pH, phosphorous, calcium and soil moisture content. Overall, the study recommends the spectra fusion approach for improving the prediction accuracy of soil attributes. Moreover, the authors emphasize that the multi-sensor spectra fusion approach is not limited to MIR and XRF data, but it can be extended for complementary information fusion to improve the model performance in precision agriculture applications.