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

Remoción de macronutrientes en el tratamiento de aguas residuales porcícolas

Macronutrients removal in the treatment of swine wastewater

VIOLETA ERENDIRA ESCALANTE ESTRADA MARCO ANTONIO GARZON ZUÑIGA SERGIO VALLE CERVANTES (2012, [Artículo])

Se presentan los resultados de una comparación realizada entre los procesos biológicos más utilizados para el tratamiento de efluentes porcícolas. Estos procesos son: digestores anaerobios, reactor anaerobio de flujo ascendentes, filtros anaerobios, reactor secuencial en lote, sistemas lagunares y biofiltros. Se concluye que una buena opción de tratamiento podría ser un sistema combinado de filtros sumergidos anaerobios con filtro percolador aireado, ya que los filtros anaerobios requieren un menor tiempo de retención hidráulico para la reducción de la materia orgánica y por otra parte, los biofiltros aerados pueden alcanzar eficiencias de remoción de nitrógeno mayores a las de otros sistemas (lagunas, variantes de lodos activados, etcétera). Sin embargo, aunque existen algunos estudios sobre el seguimiento de los mecanismos para la remoción de nitrógeno en biofiltros, se requiere realizar estudios adicionales al respecto. Se propone que una posible estrategia sería estudiando el efecto de la relación C/N y de la tasa aireación en estos sistemas de tratamiento.

Efluentes industriales Porcinos Tratamiento de aguas residuales Nitrógeno INGENIERÍA Y TECNOLOGÍA

Reactor con biomasa inmovilizada (BIOSTAR): alternativa para remoción biológica de nitrógeno

Petia Mijaylova Nacheva GABRIELA ELEONORA MOELLER CHAVEZ gabriela mantilla morales (2012, [Documento de trabajo])

En la Subcoordinación de Tratamiento de Aguas Residuales del IMTA se desarrolló un reactor biológico denominado BIOSTAR el cual ya está comercializado para el tratamiento descentralizado de aguas residuales de pequeñas poblaciones, fraccionamientos habitacionales, zonas residenciales, casas-habitación, hoteles, centros comerciales, edificios públicos, centros comerciales o recreativos. Se puede obtener agua con calidad adecuada para su desinfección con luz UV y posterior reutilización en servicios al público, cumpliendo con los límites máximos permisibles que para esto se establecen en la NOM-002-SEMARNAT/1997, así como con los límites para descarga a cuerpos receptores según la NOM-001-SEMARNAT/1996. El principal objetivo de tratamiento con el BIOSTAR es la remoción de la materia orgánica en el agua residual.

Tratamiento de aguas residuales Filtros biológicos Biomasa Nitrógeno INGENIERÍA Y TECNOLOGÍA

Classification of Cucumber Leaves Based on Nitrogen Content Using the Hyperspectral Imaging Technique and Majority Voting.

Sajad Sabzi Razieh Pourdarbani Mohammad Hossein Rohban Alejandro Fuentes_Penna José Luis Hernández-Hernández Mario Hernández Hernández (2021, [Artículo])

Improper usage of nitrogen in cucumber cultivation causes nitrate accumulation in the fruit and results in food poisoning in humans; therefore, mandatory evaluation of food products becomes inevitable. Hyperspectral imaging has a very good ability to evaluate the quality of fruits and vegetables in a non-destructive manner. The goal of the present paper was to identify excess nitrogen in cucumber plants. To obtain a reliable result, the majority voting method was used, which takes into account the unanimity of five classifiers, namely, the hybrid artificial neural network¿imperialism competitive algorithm (ANN-ICA), the hybrid artificial neural network¿harmonic search (ANN-HS) algorithm, linear discrimination analysis (LDA), the radial basis function network (RBF), and the Knearest- neighborhood (KNN). The wavelengths of 723, 781, and 901 nm were determined as optimal wavelengths using the hybrid artificial neural network¿biogeography-based optimization (ANNBBO) algorithm, and the performance of classifiers was investigated using the optimal spectrum. The results of a t-test showed that there was no significant difference in the precision of the algorithm when using the optimal wavelengths and wavelengths of the whole range. The correct classification rate of the classifiers ANN-ICA, ANN-HS, LDA, RBF, and KNN were 96.14%, 96.11%, 95.73%, 64.03%, and 95.24%, respectively. The correct classification rate of majority voting (MV) was 95.55% for test data in 200 iterations, which indicates the system was successful in distinguishing nitrogen-rich leaves from leaves with a standard content of nitrogen.

artificial neural network cucumber hyperspectral imaging majority voting nitrogen INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ALIMENTOS

Targeted nitrogen management to increase cereal production while reducing nitrogen consumption in India

Tek Sapkota Sieglinde Snapp (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CEREAL PRODUCTS PRODUCTION SYSTEMS CEREALS NITROGEN RICE WHEAT MAIZE

Optimization of N dose in rice under conservation agriculture with sub-surface drip fertigation

C.M. Parihar Hari Sankar Nayak Renu Pandey Avinash Kumar ML JAT (2021, [Artículo])

Biological Yield Economic N Dose Yield Attributes CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA YIELDS NITROGEN ZERO TILLAGE DIRECT SOWING RICE

GWAS identifies genetic loci underlying nitrogen responsiveness in the climate resilient C4 model Setaria italica (L.)

Tirthankar Bandyopadhyay Stéphanie M. Swarbreck Vandana Jaiswal Rajeev Gupta Alison Bentley Manoj Prasad (2022, [Artículo])

C4 Model Crop Climate Resilience CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE RESILIENCE FOOD SECURITY GENE EXPRESSION NITROGEN

Enhancing maize yield in a conservation agriculture-based maize (Zea mays)- wheat (Triticum aestivum) system through efficient nitrogen management

C.M. Parihar Hari Sankar Nayak Dipaka Ranjan Sena Shankar Lal Jat Mahesh Gathala Upendra Singh (2023, [Artículo])

This study evaluated the impact of contrasting tillage and nitrogen management options on the growth, yield attributes, and yield of maize (Zea mays L.) in a conservation agriculture (CA)-based maize-wheat (Triticum aestivum L.) system. The field experiment was conducted during the rainy (kharif) seasons of 2020 and 2021 at the research farm of ICAR-Indian Agricultural Research Institute (IARI), New Delhi. The experiment was conducted in a split plot design with three tillage practices [conventional tillage with residue (CT), zero tillage with residue (ZT) and permanent beds with residue (PB)] as main plot treatments and in sub-plots five nitrogen management options [Control (without N fertilization), recommended dose of N @150 kg N/ha, Green Seeker-GS based application of split applied N, N applied as basal through urea super granules-USG + GS based application and 100% basal application of slow release fertilizer (SRF) @150 kg N/ha] with three replications. Results showed that both tillage and nitrogen management options had a significant impact on maize growth, yield attributes, and yield in both seasons. However, time to anthesis and physiological maturity were not significantly affected. Yield attributes were highest in the permanent beds and zero tillage plots, with similar numbers of grains per cob (486.1 and 468.6). The highest leaf area index (LAI) at 60 DAP was observed in PB (5.79), followed by ZT(5.68) and the lowest was recorded in CT (5.25) plots. The highest grain yield (2-year mean basis) was recorded with permanent beds plots (5516 kg/ha), while the lowest

was observed with conventional tillage (4931 kg/ha). Therefore, the study highlights the importance of CA practices for improving maize growth and yield, and suggests that farmers can achieve better results through the adoption of CA-based permanent beds and use of USG as nitrogen management option.

Green Seeker Urea Super Granules CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE UREA YIELDS ZERO TILLAGE NITROGEN

Crop performance and nitrogen use-efficiency in maize under conservation agriculture coupled with sub-surface drip fertigation

C.M. Parihar Hari Sankar Nayak Renu Pandey ML JAT (2021, [Artículo])

Biological Yield Permanent Beds Yield Attributes CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA YIELDS NITROGEN NUTRIENT UPTAKE CROP PERFORMANCE MAIZE

Mejoramiento del grado de uso del nitrógeno en maíz mediante técnicas parcelarias de riego por superficie

Improving the usage level of nitrogen in maize, through surface irrigation plot techniques

JAIME MACIAS CERVANTES JESUS DEL ROSARIO RUELAS ISLAS PABLO PRECIADO RANGEL WALDO OJEDA BUSTAMANTE MARCO ANTONIO INZUNZA IBARRA JOSE ALFREDO SAMANIEGO GAXIOLA (2015, [Artículo])

El maíz es uno de los principales cultivos sembrados en el estado de Sinaloa; sin embargo, en esta región la aplicación de riegos se realiza sin considerar las características físicas del suelo incrementando las pérdidas de agua y fertilizantes. Es importante desarrollar tecnologías que permitan optimizar el uso de insumos (agua, fertilizantes, pesticidas) incrementando el potencial productivo de los cultivos y reduciendo los costos de producción, por tal motivo, se desarrollaron una serie de experimentos durante los ciclos otoño-invierno 2006-2007 y 2011-2012 en el norte de Sinaloa, México, con el propósito de conocer el efecto del riego por gravedad por diferentes técnicas en la eficiencia de uso del nitrógeno (N) en el cultivo de maíz.

Riego de baja presión Riego de superficie Nitrógeno Cultivos alimenticios Maíz INGENIERÍA Y TECNOLOGÍA