Salt-Tolerant Compatible Microbial Inoculants Modulate Physio-Biochemical Responses Enhance Plant Growth, Zn Biofortification and Yield of Wheat Grown in Saline-Sodic Soil

A wide range of root-associated mutualistic microorganisms have been successfully applied and documented in the past for growth promotion, biofertilization, biofortification and biotic and abiotic stress amelioration in major crops. These microorganisms include nitrogen fixers, nutrient mobilizers, bio-remediators and bio-control agents. The present study aimed to demonstrate the impact of salt-tolerant compatible microbial inoculants on plant growth; Zn biofortification and yield of wheat (Triticum aestivum L.) crops grown in saline-sodic soil and insight of the mechanisms involved therein are being shared through this paper. Field experiments were conducted to evaluate the effects of Trichoderma harzianum UBSTH-501 and Bacillus amyloliquefaciens B-16 on wheat grown in saline-sodic soil at Research Farm, ICAR-Indian Institute of Seed Sciences, Kushmaur, India. The population of rhizosphere-associated microorganisms changed dramatically upon inoculation of the test microbes in the wheat rhizosphere. The co-inoculation induced a significant accumulation of proline and total soluble sugar in wheat at 30, 60, 90 and 120 days after sowing as compared to the uninoculated control. Upon quantitative estimation of organic solutes and antioxidant enzymes, these were found to have increased significantly in co-inoculated plants under salt-stressed conditions. The application of microbial inoculants enhanced the salt tolerance level significantly in wheat plants grown in saline-sodic soil. A significant increase in the uptake and translocation of potassium (K+) and calcium (Ca2+) was observed in wheat co-inoculated with the microbial inoculants, while a significant reduction in sodium (Na+) content was recorded in plants treated with both the bio-agents when compared with the respective uninoculated control plants. Results clearly indicated that significantly higher expression of TaHKT-1 and TaNHX1 in the roots enhances salt tolerance effectively by maintaining the Na+/K+ balance in the plant tissue. It was also observed that co-inoculation of the test inoculants increased the expression of ZIP transporters (2–3.5-folds) which ultimately led to increased biofortification of Zn in wheat grown in saline-sodic soil. Results suggested that co-inoculation of T. harzianum UBSTH-501 and B. amyloliquefaciens B-16 not only increased plant growth but also improved total grain yield along with a reduction in seedling mortality in the early stages of crop growth. In general, the present investigation demonstrated the feasibility of using salt-tolerant rhizosphere microbes for plant growth promotion and provides insights into plant-microbe interactions to ameliorate salt stress and increase Zn bio-fortification in wheat.

Improving Biomass and Grain Yield Prediction of Wheat GenoTypes on Sodic Soil Using Integrated High-Resolution MultiSpectral, Hyperspectral, 3D Point Cloud, and Machine Learning Techniques

Sodic soils adversely affect crop production over extensive areas of rain-fed cropping worldwide, with particularly large areas in Australia. Crop phenotyping may assist in identifying cultivars tolerant to soil sodicity. However, studies to identify the most appropriate traits and reliable tools to assist crop phenotyping on sodic soil are limited. Hence, this study evaluated the ability of multispectral, hyperspectral, 3D point cloud, and machine learning techniques to improve estimation of biomass and grain yield of wheat genotypes grown on a moderately sodic (MS) and highly sodic (HS) soil sites in northeastern Australia. While a number of studies have reported using different remote sensing approaches and crop traits to quantify crop growth, stress, and yield variation, studies are limited using the combination of these techniques including machine learning to improve estimation of genotypic biomass and yield, especially in constrained sodic soil environments. At close to flowering, unmanned aerial vehicle (UAV) and ground-based proximal sensing was used to obtain remote and/or proximal sensing data, while biomass yield and crop heights were also manually measured in the field. Grain yield was machine-harvested at maturity. UAV remote and/or proximal sensing-derived spectral vegetation indices (VIs), such as normalized difference vegetation index, optimized soil adjusted vegetation index, and enhanced vegetation index and crop height were closely corresponded to wheat genotypic biomass and grain yields. UAV multispectral VIs more closely associated with biomass and grain yields compared to proximal sensing data. The red-green-blue (RGB) 3D point cloud technique was effective in determining crop height, which was slightly better correlated with genotypic biomass and grain yield than ground-measured crop height data. These remote sensing-derived crop traits (VIs and crop height) and wheat biomass and grain yields were further simulated using machine learning algorithms (multitarget linear regression, support vector machine regression, Gaussian process regression, and artificial neural network) with different kernels to improve estimation of biomass and grain yield. The artificial neural network predicted biomass yield (R2 = 0.89; RMSE = 34.8 g/m2 for the MS and R2 = 0.82; RMSE = 26.4 g/m2 for the HS site) and grain yield (R2 = 0.88; RMSE = 11.8 g/m2 for the MS and R2 = 0.74; RMSE = 16.1 g/m2 for the HS site) with slightly less error than the others. Wheat genotypes Mitch, Corack, Mace, Trojan, Lancer, and Bremer were identified as more tolerant to sodic soil constraints than Emu Rock, Janz, Flanker, and Gladius. The study improves our ability to select appropriate traits and techniques in accurate estimation of wheat genotypic biomass and grain yields on sodic soils. This will also assist farmers in identifying cultivars tolerant to sodic soil constraints.

Variation in Sodic Soil Bacterial Communities Associated with Different Alkali Vegetation Types

In this study, we examined the effect of salinity and alkalinity on the metabolic potential and taxonomic composition of microbiota inhabiting the sodic soils in different plant communities. The soil samples were collected in the Pannonian steppe (Hungary, Central Europe) under extreme dry and wet weather conditions. The metabolic profiles of microorganisms were analyzed using the MicroResp method, the bacterial diversity was assessed by cultivation and next-generation amplicon sequencing based on the 16S rRNA gene. Catabolic profiles of microbial communities varied primarily according to the alkali vegetation types. Most members of the strain collection were identified as plant associated and halophilic/alkaliphilic species of Micrococcus, Nesterenkonia, Nocardiopsis, Streptomyces (Actinobacteria) and Bacillus, Paenibacillus (Firmicutes) genera. Based on the pyrosequencing data, the relative abundance of the phyla Proteobacteria, Actinobacteria, Acidobacteria, Gemmatimonadetes and Bacteroidetes also changed mainly with the sample types, indicating distinctions within the compositions of bacterial communities according to the sodic soil alkalinity-salinity gradient. The effect of weather extremes was the most pronounced in the relative abundance of the phyla Actinobacteria and Acidobacteria. The type of alkali vegetation caused greater shifts in both the diversity and activity of sodic soil microbial communities than the extreme aridity and moisture.