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Manish Kakraliya madhu choudhary Mahesh Gathala Parbodh Chander Sharma ML JAT (2024, [Artículo])
The future of South Asia’s major production system (rice–wheat rotation) is at stake due to continuously aggravating pressure on groundwater aquifers and other natural resources which will further intensify with climate change. Traditional practices, conventional tillage (CT) residue burning, and indiscriminate use of groundwater with flood irrigation are the major drivers of the non-sustainability of rice–wheat (RW) system in northwest (NW) India. For designing sustainable practices in intensive cereal systems, we conducted a study on bundled practices (zero tillage, residue mulch, precise irrigation, and mung bean integration) based on multi-indicator (system productivity, profitability, and efficiency of water, nitrogen, and energy) analysis in RW system. The study showed that bundling conservation agriculture (CA) practices with subsurface drip irrigation (SDI) saved ~70 and 45% (3-year mean) of irrigation water in rice and wheat, respectively, compared to farmers’ practice/CT practice (pooled data of Sc1 and Sc2; 1,035 and 318 mm ha−1). On a 3-year system basis, CA with SDI scenarios (mean of Sc5–Sc8) saved 35.4% irrigation water under RW systems compared to their respective CA with flood irrigation (FI) scenarios (mean of Sc3 and Sc4) during the investigation irrespective of residue management. CA with FI system increased the water productivity (WPi) and its use efficiency (WUE) by ~52 and 12.3% (3-year mean), whereas SDI improved by 221.2 and 39.2% compared to farmers practice (Sc1; 0.69 kg grain m−3 and 21.39 kg grain ha−1 cm−1), respectively. Based on the 3-year mean, CA with SDI (mean of Sc5–Sc8) recorded −2.5% rice yield, whereas wheat yield was +25% compared to farmers practice (Sc1; 5.44 and 3.79 Mg ha−1) and rice and wheat yield under CA with flood irrigation were increased by +7 and + 11%, compared to their respective CT practices. Mung bean integration in Sc7 and Sc8 contributed to ~26% in crop productivity and profitability compared to farmers’ practice (Sc1) as SDI facilitated advancing the sowing time by 1 week. On a system basis, CA with SDI improved energy use efficiency (EUE) by ~70% and partial factor productivity of N by 18.4% compared to CT practices. In the RW system of NW India, CA with SDI for precise water and N management proved to be a profitable solution to address the problems of groundwater, residue burning, sustainable intensification, and input (water and energy) use with the potential for replication in large areas in NW India.
Direct Seeded Rice Subsurface Drip Irrigation Economic Profitability Energy and Nitrogen Efficiency CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CONSERVATION AGRICULTURE RICE SUBSURFACE IRRIGATION IRRIGATION SYSTEMS WATER PRODUCTIVITY ECONOMIC VIABILITY ENERGY EFFICIENCY NITROGEN-USE EFFICIENCY
Ana Luisa Garcia-Oliveira Mahalingam Govindaraj Rodomiro Ortiz (2023, [Artículo])
Bioaccessibility and Absorption Biofortified Crop Cultivars Genes and Genetic Markers Nutrient Acquisition Transport and Storage CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BIOAVAILABILITY ABSORPTION CLIMATE CHANGE GENETIC MARKERS GENETIC ENGINEERING NUTRIENTS TRANSPORT STORAGE
Low nitrogen narrows down phenotypic diversity in durum wheat
Tesfaye Geleta Aga Bekele Abeyo (2023, [Artículo])
Clusters Durum Wheat Nitrogen Efficiency CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA HARD WHEAT GENETIC DIVERGENCE NORMALIZED DIFFERENCE VEGETATION INDEX NITROGEN PRINCIPAL COMPONENT ANALYSIS
Manish Kakraliya Deepak Bijarniya Parbodh Chander Sharma ML JAT (2022, [Artículo])
Intensive Tillage Conventional Rice–Wheat Systems Energy Efficiency On-Farm Studies Climate-Smart Agricultural Practices CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE-SMART AGRICULTURE RICE WHEAT CROPPING SYSTEMS
Gatien Falconnier Marc Corbeels Frédéric Baudron Antoine Couëdel leonard rusinamhodzi bernard vanlauwe Ken Giller (2023, [Artículo])
Can farmers in sub-Saharan Africa (SSA) boost crop yields and improve food availability without using more mineral fertilizer? This question has been at the center of lively debates among the civil society, policy-makers, and in academic editorials. Proponents of the “yes” answer have put forward the “input reduction” principle of agroecology, i.e. by relying on agrobiodiversity, recycling and better efficiency, agroecological practices such as the use of legumes and manure can increase crop productivity without the need for more mineral fertilizer. We reviewed decades of scientific literature on nutrient balances in SSA, biological nitrogen fixation of tropical legumes, manure production and use in smallholder farming systems, and the environmental impact of mineral fertilizer. Our analyses show that more mineral fertilizer is needed in SSA for five reasons: (i) the starting point in SSA is that agricultural production is “agroecological” by default, that is, very low mineral fertilizer use, widespread mixed crop-livestock systems and large crop diversity including legumes, but leading to poor soil fertility as a result of widespread soil nutrient mining, (ii) the nitrogen needs of crops cannot be adequately met solely through biological nitrogen fixation by legumes and recycling of animal manure, (iii) other nutrients like phosphorus and potassium need to be replaced continuously, (iv) mineral fertilizers, if used appropriately, cause little harm to the environment, and (v) reducing the use of mineral fertilizers would hamper productivity gains and contribute indirectly to agricultural expansion and to deforestation. Yet, the agroecological principles directly related to soil fertility—recycling, efficiency, diversity—remain key in improving soil health and nutrient-use efficiency, and are critical to sustaining crop productivity in the long run. We argue for a nuanced position that acknowledges the critical need for more mineral fertilizers in SSA, in combination with the use of agroecological practices and adequate policy support.
Manure Crop Yields Smallholder Farming Systems Environmental Hazards CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BIOLOGICAL NITROGEN FIXATION LEGUMES NUTRIENT BALANCE SOIL FERTILITY AGROECOLOGY YIELD INCREASES LITERATURE REVIEWS
Agricultural emissions reduction potential by improving technical efficiency in crop production
Arun Khatri-Chhetri Tek Sapkota sofina maharjan Paresh Shirsath (2023, [Artículo])
CONTEXT: Global and national agricultural development policies normally tend to focus more on enhancing farm productivity through technological changes than on better use of existing technologies. The role of improving technical efficiency in greenhouse gas (GHG) emissions reduction from crop production is the least explored area in the agricultural sector. But improving technical efficiency is necessary in the context of the limited availability of existing natural resources (particularly land and water) and the need for GHG emission reduction from the agriculture sector. Technical efficiency gains in the production process are linked with the amount of input used nd the cost of production that determines both economic and environmental gains from the better use of existing technologies. OBJECTIVE: To assess a relationship between technical efficiency and GHG emissions and test the hypothesis that improving technical efficiency reduces GHG emissions from crop production. METHODS: This study used input-output data collected from 10,689 rice farms and 5220 wheat farms across India to estimate technical efficiency, global warming potential, and emission intensity (GHG emissions per unit of crop production) under the existing crop production practices. The GHG emissions from rice and wheat production were estimated using the CCAFS Mitigation Options Tool (CCAFS-MOT) and the technical efficiency of production was estimated through a stochastic production frontier analysis. RESULTS AND CONCLUSIONS: Results suggest that improving technical efficiency in crop production can reduce emission intensity but not necessarily total emissions. Moreover, our analysis does not support smallholders tend to be technically less efficient and the emissions per unit of food produced by smallholders can be relatively high. Alarge proportion of smallholders have high technical efficiency, less total GHG emissions, and low emissions intensity. This study indicates the levels of technical efficiency and GHG emission are largely influenced by farming typology, i.e. choice and use of existing technologies and management practices in crop cultivation. SIGNIFICANCE: This study will help to promote existing improved technologies targeting GHG emissions reduction from the agriculture production systems.
Technical Efficiency Interventions CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MITIGATION PRODUCTIVITY CROP PRODUCTION GREENHOUSE GAS EMISSIONS
Climate robust soil fertility management by smallholders in Africa, Asia, and Latin America
Tek Sapkota (2023, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SOIL FERTILITY SMALLHOLDERS FERTILIZERS NUTRIENT MANAGEMENT
Soil analysis and integrated nutrient management
Isaiah Nyagumbo (2021, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SOIL ANALYSIS NUTRIENT MANAGEMENT SOIL FERTILITY
Leah Mungai Joseph Messina Leo Zulu Jiaguo Qi Sieglinde Snapp (2022, [Artículo])
Multilayer Perceptrons CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURE LAND USE POPULATION SATELLITE IMAGERY TEXTURE LAND COVER NEURAL NETWORKS REMOTE SENSING
Ricardo Hernández Mejía FRANCISCO JAVIER IBARRA VILLEGAS CAIN PEREZ WENCES (2023, [Artículo])
This work was originated from the increasing interest in several industries to implement voice based virtual assistant solutions powered by the Natural Language Processing field of study. This work is focused on the automotive industry Human Machine Interface related products, specifically the Instrument Panel. Nowadays people are constantly using virtual assistants like Google Assistant, Alexa, Cortana or Siri on their electronic devices. Furthermore, 31% of cars have a built-in virtual assistant, for example Ford uses Alexa, Mercedes-Benz and Hyundai use Google Assistant, BMW and Nissan use Cortana, GM uses IBM Watson, Honda uses Hana and Toyota uses YUI. Apart from the proprietary solutions described earlier, there are also contemporary open-source generic solutions available on the market, such as Mycroft AI which stands out from other technologies due to ready to deploy, well documented, simple installation on a Linux PC or RPI SoC, and simple execution. This paper presents a way to use Mycroft AI as an alternative to add artificial intelligence-based voice assistance to applications in the automotive domain. The voice communication module presented here drives notifications related to three different entities: seat belt, fuel level and battery level, all of them are telltales present in any automotive Instrument Panel. Since the Mycroft AI design approach is based on Human Centered Design (HCD), the voice communication module presented here provides real user experience (UX) based design. As a conclusion, Mycroft AI demonstrates great potential as an alternative to add voice assistance to automotive industry Human Machine Interface related products. About future work, due to the fact that Mycroft AI is based on Python, there are many possibilities for connecting and expanding the voice communication module by using countless Python libraries in order to import and process any type of information, in any format or source, for example the information from communication technologies like CAN, LIN, Ethernet, MOST, GPS or any other device or technology in order to create comprehensive automotive solutions.
Este trabajo se originó del creciente interés por parte de diferentes industrias para implementar soluciones de asistente virtual basado en voz impulsadas por el campo de estudio del Procesamiento del Lenguaje Natural. Este trabajo está enfocado en los productos relacionados a la Interfaz Humano Máquina de la industria automotriz, específicamente el Panel de Instrumentos. Hoy en día las personas usan constantemente asistentes virtuales como Google Assistant, Alexa, Cortana o Siri en sus dispositivos electrónicos. Más aún, 31% de los autos tienen un asistente virtual integrado, por ejemplo, Ford usa Alexa, Mercedes-Benz y Hyundai usan Google Assistant, BMW y Nissan usan Cortana, GM usa IBM Watson, Honda usa Hana y Toyota usa YUI. Aparte de las soluciones de marca registrada descritas anteriormente, también hay soluciones genéricas de código abierto contemporáneas disponibles en el mercado, tales como Mycroft AI que se hace notar por sobre otras tecnologías por características como listo para usar, bien documentada, instalación simple en una PC Linux o RPI SoC, y una ejecución simple. Este artículo presenta una manera de usar Mycroft AI como una alternativa para agregar inteligencia artificial basada en asistencia de voz a aplicaciones en el dominio automotriz. El módulo de comunicación de voz presentado aquí maneja notificaciones relacionadas a tres diferentes entidades: cinturón de seguridad, nivel de gasolina y nivel de batería, todos ellos son indicadores virtuales presentes en cualquier Panel de Instrumentos Automotriz. Dado que el enfoque de diseño de Mycroft AI se basa en Diseño Centrado en el Human (HCD), el módulo de comunicación por voz presentado aquí provee un diseño basado en experiencia de usuario (UX) real. Como conclusión, Mycroft AI demuestra gran potencial como una alternativa para agregar asistencia de voz a los productos relacionados a Interfaz Humano Máquina de la industria automotriz. Acerca del trabajo a futuro, debido al hecho que Mycroft AI está basado en Python, existen muchas posibilidades para conectar y expandir el módulo de comunicación por voz a través del uso de innumerables bibliotecas de Python para importar y procesar cualquier tipo de información, en cualquier formato o fuente, por ejemplo la información proveniente de tecnologías de comunicación tales como CAN, LIN, Ethernet, MOST, GPS o cualquier otro dispositivo o tecnología para crear soluciones automotrices integrales.
Authorship acknowledgment. Ricardo Hernández Mejía: Conceptualization, Methodology, Software, Validation, Formal analysis, Research, Resources, Original draft, Visualization, Project administration. Francisco Javier Ibarra Villegas: Review and Editing, Supervision, Project Administration. Cain Pérez Wences: Review and Editing.
Acknowledgment. To Posgrado CIATEQ A.C. due to the institutional support and guidance received to conclude this work in a professional and successful way. To Continental Automotive Occidente due to the sponsorship provided to perform the master’s degree along with Posgrado CIATEQ A.C. which made possible this work. To Dr. Francisco Javier Ibarra Villegas due to their guidance and support on the process to shape and concrete this work.
Instrument panel Virtual assistant Voice communication module Mycroft AI Human centered design User experience Panel de instrumentos Asistente virtual Módulo de comunicación por voz Diseño centrado en el humano Experiencia de usuario INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS OTRAS ESPECIALIDADES TECNOLÓGICAS OTRAS OTRAS