Soil CO2 efflux fluctuates in three different annual seasons in a semideciduous tropical forest in Yucatan, Mexico

El flujo de CO2 del suelo fluctúa en tres temporadas del año en un bosque tropical semideciduo de Yucatán, México

Fernando Arellano-Martín JUAN MANUEL DUPUY RADA ROBERTH ARMANDO US SANTAMARIA José Luis Andrade Torres (2022, [Artículo])

Tropical forest soils store a third of the global terrestrial carbon and control carbon dioxide (CO2) terrestrial effluxes to the atmosphere produced by root and microbial respiration. Soil CO2 efflux varies in time and space and is known to be strongly influenced by soil temperature and water content. However, little is known about the influence of seasonality on soil CO2 efflux, especially in tropical dry forests. This study evaluated soil CO2 efflux, soil temperature, and soil volumetric water content in a semideciduous tropical forest of the Yucatan Peninsula under two sites (flat areas close to and far from hills), and three seasons: dry, wet, and early dry (a transition between the rainy and dry seasons) throughout a year. Additionally, six 24-h periods of soil CO2 efflux were measured within these three seasons. The mean annual soil CO2 efflux was 4±2.2 μmol CO2 m-2 s-1, like the mean soil CO2 efflux during the early dry season. In all seasons, soil CO2 efflux increased linearly with soil moisture, which explained 45% of the spatial-temporal variation of soil CO2 efflux. Soil CO2 efflux was higher close to than far from hills in some months. The daily variation of soil CO2 efflux was less important than its spatial and seasonal variation likely due to small diel variations in temperature. Transition seasons are common in many tropical dry forests, and they should be taken into consideration to have a better understanding of the annual soil CO2 efflux, especially under future climate-change scenarios. © 2022 Mexican Society of Soil Science. All Rights Reserved.

EARLY DRY SEASON SOIL TEMPERATURE SOIL VOLUMETRIC WATER CONTENT TROPICAL DRY FOREST BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOLOGÍA VEGETAL (BOTÁNICA) ECOLOGÍA VEGETAL ECOLOGÍA VEGETAL

Avances en Agricultura Sustentable : Resultados de plataformas de investigación Hub Pacífico Norte 2010-2021

Simon Fonteyne Nele Verhulst (2022, [Libro])

Esta edición presenta los resultados de la red de plataformas en el Hub Pacífico Norte, misma que resulta de la colaboración entre el CIMMYT; el Patronato para la Investigación y Experimentación Agrícola del Estado de Sonora A.C. (PIEAES); el Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias (INIFAP); la Asociación de Agricultores del Río Sinaloa Poniente (AARSP); la Asociación de Agricultores del Río Fuerte Sur (AARFS); la Asociación de Agricultores del Río Culiacán (AARC); la Universidad Autónoma de Sinaloa (UAS); Servicios Agrofinancieros del Norte S.A. de C.V. (SAFINSA); el Club de Labranza de Conservación del Valle del Évora; Granera del Noroeste S.A. de C.V; y el Instituto de Ciencias Agrícolas de la Universidad Autónoma de Baja California (ICA-UABC). Los lectores podrán encontrar en este libro los resultados de las plataformas con más tiempo de operación, en donde ya se han podido generar suficientes datos para sacar conclusiones basadas en evidencias sólidas. Esperamos que el libro pueda servir de inspiración a los productores para que busquen que sus actividades en el campo sean más productivas, rentables y sustentables.

Plataformas de Investigación Maíz Amarillo Pulgón Áreas de extensión Módulos demostrativos Autosuficiencia Alimentaria Uso de Insumos Ganancias para el Productor Nodos de Innovación CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURA DE CONSERVACIÓN COSTOS DE PRODUCCIÓN EUTROFIZACIÓN MONOCULTIVO DEGRADACIÓN DEL SUELO CONTAMINACIÓN PLAGUICIDAS CAMBIO CLIMÁTICO PLATAFORMAS DE INNOVACIÓN EXTENSIÓN AGRÍCOLA AUTOSUFICIENCIA INSUMOS AGRÍCOLAS CONSERVATION AGRICULTURE PRODUCTION COSTS EUTROPHICATION MONOCULTURE SOIL DEGRADATION CONTAMINATION PESTICIDES CLIMATE CHANGE INNOVATION PLATFORMS AGRICULTURAL EXTENSION SELF-SUFFICIENCY FARM INPUTS

Establishment of heterotic groups for hybrid wheat breeding

Yunbi Xu (2022, [Artículo])

Genomic Prediction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE CROPS FORECASTING PLANTS COMBINING ABILITY HETEROSIS HETEROTIC GROUPS MALE INFERTILITY PLANT HEIGHT WHEAT

Salivary effector Sm9723 of grain aphid sitobion miscanthi suppresses plant defense and is essential for aphid survival on wheat

Yong Zhang Leonardo Abdiel Crespo Herrera Julian Chen (2022, [Artículo])

Cereal Aphid Salivary Protein Plant Immunity RNA Interference Aphid Performance CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA APHIDOIDEA PLANTS RNA PROTEINS

Point placement of late vegetative stage nitrogen splits increase the productivity, N-use efficiency and profitability of tropical maize under decade long conservation agriculture

Hari Sankar Nayak C.M. Parihar Shankar Lal Jat ML JAT Ahmed Abdallah (2022, [Artículo])

Non-Linear Growth Model Nitrogen Remobilization Right Placement Precision Nitrogen Management CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GROWTH MODELS NITROGEN NUTRIENT MANAGEMENT

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

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

Diversifying with grain legumes amplifies carbon in management-sensitive soil organic carbon pools on smallholder farms

Regis Chikowo Sieglinde Snapp (2023, [Artículo])

Crop diversification with grain legumes has been advocated as a means to increase agroecological resilience, diversify livelihoods, boost household nutrition, and enhance soil health and fertility in cereal-based cropping systems in sub-Saharan Africa and around the world. Soil organic carbon (SOC) is a primary indicator of soil health and there is limited data regarding SOC pools and grain legume diversification on smallholder farms where soils are often marginal. In Malawi, a range of legume diversification options are under investigation, including rotations and a doubled-up legume rotation (DLR) system in which two compatible legumes are intercropped and then rotated with a cereal. The impact of the DLR system on SOC has not yet been determined, and there is a lack of evidence regarding SOC status over a gradient of simple to complex grain legume diversified systems. We address this knowledge gap by evaluating these systems in comparison to continuous sole maize (Zea mays L.) at three on-farm trial sites in central Malawi. After six years of trial establishment, we measured SOC in bulk soils and aggregate fractions and in faster cycling SOC pools that respond more rapidly to management practices, including water extractable organic carbon (WEOC), particulate organic matter carbon (POM-C), potentially mineralizable carbon (C), and macroaggregate C. Cropping treatment differences were not seen in bulk SOC or total N, but they were apparent in SOC pools with a shorter turnover time. The DLR system of intercropped pigeonpea (Cajanus cajan (L.) Millsp.) and groundnut (Arachis hypogaea L.) rotated with maize had higher WEOC, POM-C, potentially mineralizable C, macroaggregate and microaggregate C values than continuous maize. Of the single legume rotations, the pigeonpea-maize rotation had more mineralizable C and microaggregate C compared to continuous maize, while the groundnut-maize rotation had similar C values to the maize system. Overall, this study shows the potential for crop rotations diversified with grain legumes to enhance C in management sensitive SOC pools, and it is one of the first reports to show this effect on smallholder farm sites.

Crop Diversification Water Extractable Organic Carbon CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA DIVERSIFICATION LEGUMES PARTICULATE ORGANIC MATTER SOIL ORGANIC CARBON

The potential of UAV and very high-resolution satellite imagery for yellow and stem rust detection and phenotyping in Ethiopia

Gerald Blasch David Hodson Francelino Rodrigues (2023, [Artículo])

Very high (spatial and temporal) resolution satellite (VHRS) and high-resolution unmanned aerial vehicle (UAV) imagery provides the opportunity to develop new crop disease detection methods at early growth stages with utility for early warning systems. The capability of multispectral UAV, SkySat and Pleiades imagery as a high throughput phenotyping (HTP) and rapid disease detection tool for wheat rusts is assessed. In a randomized trial with and without fungicide control, six bread wheat varieties with differing rust resistance were monitored using UAV and VHRS. In total, 18 spectral features served as predictors for stem and yellow rust disease progression and associated yield loss. Several spectral features demonstrated strong predictive power for the detection of combined wheat rust diseases and the estimation of varieties’ response to disease stress and grain yield. Visible spectral (VIS) bands (Green, Red) were more useful at booting, shifting to VIS–NIR (near-infrared) vegetation indices (e.g., NDVI, RVI) at heading. The top-performing spectral features for disease progression and grain yield were the Red band and UAV-derived RVI and NDVI. Our findings provide valuable insight into the upscaling capability of multispectral sensors for disease detection, demonstrating the possibility of upscaling disease detection from plot to regional scales at early growth stages.

Very High Resolution Imagery Disease Detection Methods Early Growth Stages CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA UNMANNED AERIAL VEHICLES STEM RUST PHENOTYPING HIGH-THROUGHPUT PHENOTYPING WHEAT

Using an incomplete block design to allocate lines to environments improves sparse genome-based prediction in plant breeding

Osval Antonio Montesinos-Lopez ABELARDO MONTESINOS LOPEZ RICARDO ACOSTA DIAZ Rajeev Varshney Jose Crossa ALISON BENTLEY (2022, [Artículo])

Genomic selection (GS) is a predictive methodology that trains statistical machine-learning models with a reference population that is used to perform genome-enabled predictions of new lines. In plant breeding, it has the potential to increase the speed and reduce the cost of selection. However, to optimize resources, sparse testing methods have been proposed. A common approach is to guarantee a proportion of nonoverlapping and overlapping lines allocated randomly in locations, that is, lines appearing in some locations but not in all. In this study we propose using incomplete block designs (IBD), principally, for the allocation of lines to locations in such a way that not all lines are observed in all locations. We compare this allocation with a random allocation of lines to locations guaranteeing that the lines are allocated to

the same number of locations as under the IBD design. We implemented this benchmarking on several crop data sets under the Bayesian genomic best linear unbiased predictor (GBLUP) model, finding that allocation under the principle of IBD outperformed random allocation by between 1.4% and 26.5% across locations, traits, and data sets in terms of mean square error. Although a wide range of performance improvements were observed, our results provide evidence that using IBD for the allocation of lines to locations can help improve predictive performance compared with random allocation. This has the potential to be applied to large-scale plant breeding programs.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA Bayes Theorem Genome Inflammatory Bowel Diseases Models, Genetic Plant Breeding