Novel mutant alleles reveal a role of the extra-large G protein in rice grain filling, panicle architecture, plant growth, and disease resistance

Akshaya Biswal Daisuke Urano (2022, [Artículo])

Heterotrimeric G Proteins Extra-Large G Proteins Cas9 OsXLG CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CRISPR RICE PROTEINS PLANT GROWTH DISEASE RESISTANCE

Exploring GWAS and genomic prediction to improve Septoria tritici blotch resistance in wheat

Admas Alemu Abebe Pawan Singh Aakash Chawade (2023, [Artículo])

Septoria Tritici Blotch Wheat Breeding Genomic Prediction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENOME-WIDE ASSOCIATION STUDIES MYCOSPHAERELLA GRAMINICOLA DISEASE RESISTANCE WHEAT PLANT GROWTH

The water crisis in the south-central region of the Chihuahua State and the 1997 UN Convention

Jorge Arturo Salas Plata Mendoza Thelma J. Garcia (2022, [Artículo, Artículo])

The present writing focuses on the water crisis in the south-central part of Chihuahua State in the year 2020. Recent literature points to the drought, excess demand for the vital liquid and overpopulation of this region, among other issues, as the causes of the emergency. This paper argues that the reasons mentioned above are not causes, but effects of an economic policy of capital valorization and accumulation, which go far beyond the carrying capacity of the ecosystems and their capacity to regulate the polluting processes. The obsolescence of the water treaties between Mexico and the US make it necessary to consider other alternatives such as the 1997 UN Convention on water.

Chihuahua water crisis hydro-agricultural crisis carrying capacity expansive growth 1997 UN Convention Ecological Economics crisis del agua crisis hidroagrícola capacidad de carga crecimiento expansivo Convención de la ONU de 1997 Economía Ecológica CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA

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

Expanding the WOFOST crop model to explore options for sustainable nitrogen management: A study for winter wheat in the Netherlands

João Vasco Silva Pytrik Reidsma (2024, [Artículo])

Nitrogen (N) management is essential to ensure crop growth and to balance production, economic, and environmental objectives from farm to regional levels. This study aimed to extend the WOFOST crop model with N limited production and use the model to explore options for sustainable N management for winter wheat in the Netherlands. The extensions consisted of the simulation of crop and soil N processes, stress responses to N deficiencies, and the maximum gross CO2 assimilation rate being computed from the leaf N concentration. A new soil N module, abbreviated as SNOMIN (Soil Nitrogen for Organic and Mineral Nitrogen module) was developed. The model was calibrated and evaluated against field data. The model reproduced the measured grain dry matter in all treatments in both the calibration and evaluation data sets with a RMSE of 1.2 Mg ha−1 and the measured aboveground N uptake with a RMSE of 39 kg N ha−1. Subsequently, the model was applied in a scenario analysis exploring different pathways for sustainable N use on farmers' wheat fields in the Netherlands. Farmers' reported yield and N fertilization management practices were obtained for 141 fields in Flevoland between 2015 and 2017, representing the baseline. Actual N input and N output (amount of N in grains at harvest) were estimated for each field from these data. Water and N-limited yields and N outputs were simulated for these fields to estimate the maximum attainable yield and N output under the reported N management. The investigated scenarios included (1) closing efficiency yield gaps, (2) adjusting N input to the minimum level possible without incurring yield losses, and (3) achieving 90% of the simulated water-limited yield. Scenarios 2 and 3 were devised to allow for soil N mining (2a and 3a) and to not allow for soil N mining (2b and 3b). The results of the scenario analysis show that the largest N surplus reductions without soil N mining, relative to the baseline, can be obtained in scenario 1, with an average of 75%. Accepting negative N surpluses (while maintaining yield) would allow maximum N input reductions of 84 kg N ha−1 (39%) on average (scenario 2a). However, the adjustment in N input for these pathways, and the resulting N surplus, varied strongly across fields, with some fields requiring greater N input than used by farmers.

Crop Growth Models WOFOST CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CROPS NITROGEN-USE EFFICIENCY WINTER WHEAT SOIL WATER

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

Modeling the growth, yield and N dynamics of wheat for decoding the tillage and nitrogen nexus in 8-years long-term conservation agriculture based maize-wheat system

C.M. Parihar Dipaka Ranjan Sena Prakash Chand Ghasal Shankar Lal Jat Yashpal Singh Saharawat Mahesh Gathala Upendra Singh Hari Sankar Nayak (2024, [Artículo])

Context: Agricultural field experiments are costly and time-consuming, and their site-specific nature limits their ability to capture spatial and temporal variability. This hinders the transfer of crop management information across different locations, impeding effective agricultural decision-making. Further, accurate estimates of the benefits and risks of alternative crop and nutrient management options are crucial for effective decision-making in agriculture. Objective: The objective of this study was to utilize the Crop Environment Resource Synthesis CERES-Wheat model to simulate crop growth, yield, and nitrogen dynamics in a long-term conservation agriculture (CA) based wheat system. The study aimed to calibrate the model using data from a field experiment conducted during the 2019-20-2020-21 growing seasons and evaluation it with independent data from the year 2021–22. Method: Crop simulation models, such as the Crop Environment Resource Synthesis CERES-Wheat (DSSAT v 4.8), may provide valuable insights into crop growth and nitrogen dynamics, enabling decision makers to understand and manage production risk more effectively. Therefore, the present study employed the CERES-Wheat (DSSAT v 4.8) model and calibrated it using field data, including plant phenological phases, leaf area index, aboveground biomass, and grain yield from the 2019-20-2020-21 growing seasons. An independent dataset from the year 2021–22 was used for model evaluation. The model was used to investigate the relationship between growing degree days (GDD), temperature, nitrate and ammonical concentration in soil, and nitrogen uptake by the crop. Additionally, the study explored the impact of contrasting tillage practices and fertilizer nitrogen management options on wheat yields. The experimental site is situated at ICAR-Indian Agricultural Research Institute (IARI), New Delhi, representing Indian Trans-Gangetic Plains Zone (28o 40’N latitude, 77o 11’E longitude and an altitude of 228 m above sea level). The treatments consist of four nitrogen management options, viz., N0 (zero nitrogen), N150 (150 kg N ha−1 through urea), GS (Green seeker based urea application) and USG (urea super granules @150 kg N ha−1) in two contrasting tillage systems, i.e., CA-based zero tillage (ZT) and conventional tillage (CT). Result: The outcomes exhibited favorable agreement between the model’s simulations and the observed data for crop phenology (With less than 2 days variation in 50% onset of flowering), grain and biomass yield (Root mean square error; RMSE 336 kg ha−1 and 649 kg ha−1, respectively), and leaf area index (LAI) (RMSE 0.28 & normalized RMSE; nRMSE 6.69%). The model effectively captured the nitrate-N (NO3−-N) dynamics in the soil profile, exhibiting a remarkable concordance with observed data, as evident from its low RMSE = 12.39 kg ha−1 and nRMSE = 13.69%. Moreover, as it successfully simulated the N balance in the production system, the nitrate leaching and ammonia volatilization pattern as described by the model are highly useful to understand these critical phenomena under both conventional tillage (CT) and CA-based Zero Tillage (ZT) treatments. Conclusion: The study concludes that the DSSAT-CERES-Wheat model has significant potential to assess the impacts of tillage and nitrogen management practices on crop growth, yield, and soil nitrogen dynamics in the western Indo-Gangetic Plains (IGP) region. By providing reliable forecasts within the growing season, this modeling approach can facilitate better planning and more efficient resource management. Future implications: The successful implementation of the DSSAT-CERES-Wheat model in this study highlights its applicability in assessing crop performance and soil dynamics. Future research should focus on expanding the model’s capabilities by reducing its sensitivity to initial soil nitrogen levels to refine its predictions further. Moreover, the model’s integration with decision support systems and real-time data can enhance its usefulness in aiding agricultural decision-making and supporting sustainable crop management practices.

Nitrogen Dynamics Mechanistic Crop Growth Models Crop Simulation CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA NITROGEN CONSERVATION AGRICULTURE WHEAT MAIZE CROP GROWTH RATE SIMULATION MODELS

An efficient transformation method for genome editing of elite bread wheat cultivars

Akshaya Biswal Kanwarpal Dhugga (2023, [Artículo])

Particle Bombardment Wheat Growth-Regulating Factor 4 Wheat Growth-Interacting Factor Wheat Mildew Locus O CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CRISPR GENE EDITING TRANSFORMATION WHEAT

INFLUENCIA DE CONDICIONES AMBIENTALES SOBRE LA DISTRIBUCIÓN, ABUNDANCIA Y DESARROLLO DE LARVAS DE Totoaba macdonaldi (Gilbert, 1890), EN EL ALTO GOLFO DE CALIFORNIA

Marcelo Vidal Curiel Bernal (2023, [Tesis de doctorado])

"La presente tesis aborda una investigación sobre la biología, ecología y crecimiento de la Totoaba macdonaldi en el alto golfo de California. La totoaba, una especie endémica a esta región se encuentra actualmente en peligro de extinción debido a una serie de amenazas como: cambios en su ecosistema reproductivo y de crianza, pesca, incidental de juveniles e ilegal de adultos. Aunque en los últimos 30 años la población dio signos de recuperación, existen indicios de que tanto la población adulta como las abundancias de larvas presentan una tendencia decreciente. Lo que resalta la importancia de estudiar cómo la variabilidad ambiental incide en la distribución y abundancia de larvas de totoaba y subsecuentemente en el stock recluta de la especie. El estudio comienza con un análisis de la variabilidad del crecimiento individual en etapas juveniles y adultas de la totoaba. Para este propósito, se utiliza la varianza observada como elemento clave para parametrizar modelos de crecimiento individual. Los resultados indican que este enfoque proporciona estimaciones sólidas de los parámetros de crecimiento. A continuación, se investiga el crecimiento de las larvas de totoaba en condiciones de cultivo. Los datos revelan que un modelo sigmoideo describe mejor el crecimiento y se identifican dos puntos de inflexión en el crecimiento de las larvas. Estos hallazgos tienen importantes implicaciones para la cría y el cultivo de la totoaba para efectos de repoblación. Por último, se analiza la ecología y el transporte de las larvas de totoaba en el alto golfo de California. Se identifica una ventana óptima para el desove de la totoaba en términos de temperatura y concentración de clorofila, y se sugiere que las condiciones ambientales y la distribución de los adultos pueden influir en las abundancias de larvas en diferentes años. Además, se destaca la importancia del frente permanente al sur del alto golfo de California como una posible zona de acumulación de larvas como factor que contribuye al endemismo en la región. En conjunto, esta tesis representa un enfoque multidisciplinario para comprender los aspectos clave de la biología, ecología y crecimiento de la totoaba en el alto golfo de California. Los resultados proporcionan información valiosa para la conservación de esta especie amenazada y destacan la importancia de un enfoque integral en la gestión de los recursos marinos en esta región única."

"The following thesis addresses a research on the biology, ecology, and growth of Totoaba macdonaldi in the upper gulf of California. The totoaba, a fish species endemic to this region, is currently endangered due to a series of threats such as: changes in its reproductive and breeding ecosystem, juvenile bycatch, and illegal fishing. Although over the last 30 years, the population has shown signs of recovery, there are indications that both the adult population and larval abundances are on a declining trend. This underscores the importance of studying how environmental variability affects the distribution and abundance of totoaba larvae and subsequently the recruitment stock of the species. The study begins with an analysis of growth in juvenile and adult stages of the totoaba. For this purpose, observed variance is used to parameterize individual growth models. Results indicate that this approach provides robust estimates of growth parameters. Next, the growth of cultivated totoaba larvae is investigated. The data reveal that a sigmoid model better describes the growth in the early life stages of the totoaba, and two inflection points in larval growth are identified. These findings have important implications for the breeding and cultivation of the totoaba for restocking purposes. Finally, the ecology and transport of totoaba larvae in the upper gulf of California are analyzed. An optimal window for totoaba spawning in terms of temperature and chlorophyll concentration is identified, and it is suggested that environmental conditions and the distribution of adults may influence larval abundances in different years. Additionally, the importance of the permanent front to the south of the upper gulf of California is highlighted as a possible larval accumulation zone and a contributing factor to endemism in the region. Overall, this thesis represents a multidisciplinary approach to understanding key aspects of the biology, ecology, and growth of the totoaba in the upper gulf of California. The results provide valuable information for the conservation of this threatened species and underscore the importance of a comprehensive approach in the management of marine resources in this unique region."

Variabilidad ambiental, crecimiento, dispersión, rutas larvarias Environmental variability, growth, dispersion, larval routes CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CIENCIAS AGRARIAS PECES Y FAUNA SILVESTRE PROPAGACIÓN Y ORDENACIÓN PROPAGACIÓN Y ORDENACIÓN

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