Climate-smart agricultural practices influence the fungal communities and soil properties under major agri-food systems

madhu choudhary ML JAT Parbodh Chander Sharma (2022, [Artículo])

Fungal communities in agricultural soils are assumed to be affected by climate, weather, and anthropogenic activities, and magnitude of their effect depends on the agricultural activities. Therefore, a study was conducted to investigate the impact of the portfolio of management practices on fungal communities and soil physical–chemical properties. The study comprised different climate-smart agriculture (CSA)-based management scenarios (Sc) established on the principles of conservation agriculture (CA), namely, ScI is conventional tillage-based rice–wheat rotation, ScII is partial CA-based rice–wheat–mungbean, ScIII is partial CSA-based rice–wheat–mungbean, ScIV is partial CSA-based maize–wheat–mungbean, and ScV and ScVI are CSA-based scenarios and similar to ScIII and ScIV, respectively, except for fertigation method. All the scenarios were flood irrigated except the ScV and ScVI where water and nitrogen were given through subsurface drip irrigation. Soils of these scenarios were collected from 0 to 15 cm depth and analyzed by Illumina paired-end sequencing of Internal Transcribed Spacer regions (ITS1 and ITS2) for the study of fungal community composition. Analysis of 5 million processed sequences showed a higher Shannon diversity index of 1.47 times and a Simpson index of 1.12 times in maize-based CSA scenarios (ScIV and ScVI) compared with rice-based CSA scenarios (ScIII and ScV). Seven phyla were present in all the scenarios, where Ascomycota was the most abundant phyla and it was followed by Basidiomycota and Zygomycota. Ascomycota was found more abundant in rice-based CSA scenarios as compared to maize-based CSA scenarios. Soil organic carbon and nitrogen were found to be 1.62 and 1.25 times higher in CSA scenarios compared with other scenarios. Bulk density was found highest in farmers' practice (Sc1); however, mean weight diameter and water-stable aggregates were found lowest in ScI. Soil physical, chemical, and biological properties were found better under CSA-based practices, which also increased the wheat grain yield by 12.5% and system yield by 18.8%. These results indicate that bundling/layering of smart agricultural practices over farmers' practices has tremendous effects on soil properties, and hence play an important role in sustaining soil quality/health.

Agriculture Management Fungal Community Diversity Indices Climate-Smart Agricultural Practices CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURE TILLAGE CLIMATE-SMART AGRICULTURE SOIL ORGANIC CARBON

Development of a next generation SNP genotyping array for wheat

Simon Griffiths Susanne Dreisigacker Alison Bentley Gina Brown-Guedira (2023, [Artículo])

Axiom Array High Throughput Genotyping Hexaploid Wheat Copy Number Variation Analysis CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SINGLE NUCLEOTIDE POLYMORPHISMS WHEAT GENOTYPING GENETIC DIVERSITY (AS RESOURCE)

Molecular characterization of doubled haploid lines derived from different cycles of the Iowa Stiff Stalk Synthetic (BSSS) maize population

Jode Edwards Sarah Hearne (2023, [Artículo])

Homozygous Lines CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENETIC DIVERSITY (AS RESOURCE) GENETIC RESOURCES ZEA MAYS GENOTYPING DOUBLED HAPLOIDS SINGLE NUCLEOTIDE POLYMORPHISMS

Morphological characterization of native maize populations of the ratón race from Coahuila, Mexico

Froylan Rincon Cesar Petroli (2023, [Artículo])

Repeatability Index Representative Subset of Diversity Maize Raton Race CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENETIC DIVERSITY (AS RESOURCE) ZEA MAYS MORPHOLOGY PHENOTYPING VARIETIES

Nitrogen fertilizer application alters the root endophyte bacterial microbiome in maize plants, but not in the stem or rhizosphere soil

Alejandra Miranda Carrazco Yendi Navarro-Noya Bram Govaerts Nele Verhulst Luc Dendooven (2022, [Artículo])

Plant-associated microorganisms that affect plant development, their composition, and their functionality are determined by the host, soil conditions, and agricultural practices. How agricultural practices affect the rhizosphere microbiome has been well studied, but less is known about how they might affect plant endophytes. In this study, the metagenomic DNA from the rhizosphere and endophyte communities of root and stem of maize plants was extracted and sequenced with the “diversity arrays technology sequencing,” while the bacterial community and functionality (organized by subsystems from general to specific functions) were investigated in crops cultivated with or without tillage and with or without N fertilizer application. Tillage had a small significant effect on the bacterial community in the rhizosphere, but N fertilizer had a highly significant effect on the roots, but not on the rhizosphere or stem. The relative abundance of many bacterial species was significantly different in the roots and stem of fertilized maize plants, but not in the unfertilized ones. The abundance of N cycle genes was affected by N fertilization application, most accentuated in the roots. How these changes in bacterial composition and N genes composition might affect plant development or crop yields has still to be unraveled.

Bacterial Community Structure DArT-Seq Bacterial Community Functionality Genes Involved in N Cycling CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURAL PRACTICES MAIZE RHIZOSPHERE STEMS NITROGEN FERTILIZERS

Editorial: Genome wide association studies and genomic selection for crop improvement in the era of Big Data

Alison Bentley Charles Chen Nunzio D'Agostino (2022, [Artículo])

Allele Mining High-Throughput Phenotyping Genomic Estimated Breeding Value CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CROP IMPROVEMENT DNA CHROMOSOME MAPPING GENETIC LINKAGE GENOMES GENOTYPING GERMINATION HEAT STRESS QUALITY CONTROL SINGLE NUCLEOTIDE POLYMORPHISM TRITICUM AESTIVUM GENETIC DIVERSITY (AS RESOURCE) HIGH-THROUGHPUT SEQUENCING

Rust research to enhance resistance durability

sridhar bhavani (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA RUSTS DISEASE RESISTANCE SPRING WHEAT GENETIC DIVERSITY (AS RESOURCE) ADULT PLANT RESISTANCE

Types of resistance

sridhar bhavani (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA RUSTS DISEASE RESISTANCE WHEAT GENETIC DIVERSITY (AS RESOURCE) ADULT PLANT RESISTANCE

Rust research to enhance resistance durability

sridhar bhavani (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA RUSTS DISEASE RESISTANCE SPRING WHEAT GENETIC DIVERSITY (AS RESOURCE) ADULT PLANT RESISTANCE

Using Observed Residual Error Structure Yields the Best Estimates of Individual Growth Parameters

Marcelo Vidal Curiel Bernal EUGENIO ALBERTO ARAGON NORIEGA MIGUEL ANGEL CISNEROS MATA LAURA SANCHEZ VELASCO SYLVIA PATRICIA ADELHEID JIMENEZ ROSENBERG ALEJANDRO FRANCISCO PARES SIERRA (2021, [Artículo])

"Obtaining the best possible estimates of individual growth parameters is essential in studies of physiology, fisheries management, and conservation of natural resources since growth is a key component of population dynamics. In the present work, we use data of an endangered fish species to demonstrate the importance of selecting the right data error structure when fitting growth models in multimodel inference. The totoaba (Totoaba macdonaldi) is a fish species endemic to the Gulf of California increasingly studied in recent times due to a perceived threat of extinction. Previous works estimated individual growth using the von Bertalanffy model assuming a constant variance of length-at-age. Here, we reanalyze the same data under five different variance assumptions to fit the von Bertalanffy and Gompertz models. We found consistent significant differences between the constant and nonconstant error structure scenarios and provide an example of the consequences using the growth performance index _0 to show how using the wrong error structure can produce growth parameter values that can lead to biased conclusions. Based on these results, for totoaba and other related species, we recommend using the observed error structure to obtain the individual growth parameters."

multimodel inference, error structure, totoaba, growth performance BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOLOGÍA ANIMAL (ZOOLOGÍA) FISIOLOGÍA ANIMAL FISIOLOGÍA ANIMAL