Defining greenspace: Multiple uses across multiple disciplines

Abiotic stressors such as extreme temperatures, drought, flood, light, salt, and heavy metals alter biological diversity and crop production worldwide. Therefore, it is important to know the mechanisms by which plants cope with stress conditions. Polyphenols, which are the largest group of plant-specialized metabolites, are generally recognized as molecules involved in stress protection in plants. This diverse group of metabolites contains various structures, from simple forms consisting of one aromatic ring to more complex ones consisting of large number of polymerized molecules. Consequently, all these molecules, depending on their structure, may show different roles in plant growth, development, and stress protection. In the present review, we aimed to summarize data on how different polyphenol structures influence their biological activity and their roles in abiotic stress responses. We focused our review on phenolic acids, flavonoids, stilbenoids, and lignans.

https://www.mdpi.com/2223-7747/10/1/118/pdf

The Role of Polyphenols in Abiotic Stress Response: The Influence of Molecular Structure

Historically, the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) was the unique satellite sensor used to collect the nighttime light, which is an efficient means to map the global economic activities. Since it was launched in October 2011, the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (NPP) Satellite has become a new satellite used to monitor nighttime light. This study performed the first evaluation on the NPP-VIIRS nighttime light imagery in modeling economy, analyzing 31 provincial regions and 393 county regions in China. For each region, the total nighttime light (TNL) and gross regional product (GRP) around the year of 2010 were derived, and a linear regression model was applied on the data. Through the regression, the TNL from NPP-VIIRS were found to exhibit R2 values of 0.8699 and 0.8544 with the provincial GRP and county GRP, respectively, which are significantly stronger than the relationship between the TNL from DMSP-OLS (F16 and F18 satellites) and GRP. Using the regression models, the GRP was predicted from the TNL for each region, and we found that the NPP-VIIRS data is more predictable for the GRP than those of the DMSP-OLS data. This study demonstrates that the recently released NPP-VIIRS nighttime light imagery has a stronger capacity in modeling regional economy than those of the DMSP-OLS data. These findings provide a foundation to model the global and regional economy with the recently availability of the NPP-VIIRS data, especially in the regions where economic census data is difficult to access.

Potential of NPP-VIIRS Nighttime Light Imagery for Modeling the Regional Economy of China

Deep learning system for paddy plant disease detection and classification

An urgent need for sustainable thinking in agriculture – An Indian scenario

In recent times, several studies around the globe indicate that climatic changes are likely to impact the food production and poses serious challenge to food security. In the face of climate change, agricultural systems need to adapt measures for not only increasing food supply catering to the growing population worldwide with changing dietary patterns but also to negate the negative environmental impacts on the earth. Crop simulation models are the primary tools available to assess the potential consequences of climate change on crop production and informative adaptive strategies in agriculture risk management. In consideration with the important issue, this is an attempt to provide a review on the relationship between climate change impacts and crop production. It also emphasizes the role of crop simulation models in achieving food security. Significant progress has been made in understanding the potential consequences of environment-related temperature and precipitation effect on agricultural production during the last half century. Increased CO2 fertilization has enhanced the potential impacts of climate change, but its feasibility is still in doubt and debates among researchers. To assess the potential consequences of climate change on agriculture, different crop simulation models have been developed, to provide informative strategies to avoid risks and understand the physical and biological processes. Furthermore, they can help in crop improvement programmes by identifying appropriate future crop management practises and recognizing the traits having the greatest impact on yield. Nonetheless, climate change assessment through model is subjected to a range of uncertainties. The prediction uncertainty can be reduced by using multimodel, incorporating crop modelling with plant physiology, biochemistry and gene-based modelling. For devloping new model, there is a need to generate and compile high-quality field data for model testing. Therefore, assessment of agricultural productivity to sustain food security for generations is essential to maintain a collective knowledge and resources for preventing negative impact as well as managing crop practises.

Impact of climate change on crop yield and role of model for achieving food security.

Rapid urbanization and increasing land use changes due to population and economic growth in selected landscapes is being witnessed of late in India and other developing countries. The cities are expanding in all directions resulting in large-scale urban sprawl and changes in urban land use. The spatial pattern of such changes is clearly noticed on the urban fringes or city peripheral rural areas than in the city center. In fact, this is reflected in changing urban land use patterns. There is an urgent need to accurately describe land use changes for planning and sustainable management. In the recent times, remote sensing is gaining importance as vital tool in the analysis and integration of spatial data. This study intends to estimate land use pattern in a planned and unplanned urban setup and also to analyze the impact of change in land use pattern in the Varanasi urban environment. The results indicate that the planned urban setup had a higher tree cover to that of unplanned area in the Varanasi City, although a considerable disparity existed within the planned urban setups. The results emphasize the need to critically review concepts of urban planning and give more consideration to the preservation and management of urban tree cover/greenspace.

https://www.researchgate.net/profile/Manoj_Kumar255/publication/225039740_Land_use_patterns_and_urbanization_in_the_holy_city_of_Varanasi_India_a_scenario/links/0c96052e8803d7f116000000.pdf

Land use patterns and urbanization in the holy city of Varanasi, India: a scenario

The chapter provides an assessment of environmental governance in India which includes the need of environmental metrology, ideal quality infrastructure, interface between stakeholders and the role of National Metrology Institute (NMI). The chapter also discusses the training needs for developing human resources to implement best measurement practices for improving the quality of measurement data. An attempt has also been made to estimate the potential economic impacts of improving the existing quality framework in India. Apex level test and calibration facilities for all of the environmental and emission monitoring systems are currently not available in the country. The lack of these facilities in India is not only a major constraint for industries dealing with manufacturing/production of environmental monitoring equipment but also to user organizations/agencies in respect of ascertaining the data quality. Realizing this need, the Government of India has designated the CSIR-NPL as the national agency for certifying instruments and equipments for monitoring emissions and ambient air. To cater to this need a ‘CSIR-NPL India Certificate Scheme (NPLI CS)’ has been developed to provide certification of performance evaluation of air pollution monitoring equipment. In addition, technologies developed by CSIR-NPL in the field atmospheric measurements are also discussed along with the capacity building efforts undertaken in this field by CSIR-NPL.

Metrology for Atmospheric Environment

images and extensive field observations in Varanasi and Mirzapur districts of Uttar Pradesh. Among these, two were agriculture research farm and another two were farmer’s fields. All sites had adopted conventional agriculture practices, where fertilizers were applied followed by recommended dosage of NPK for dominant crops (rice and wheat). Agricultural NPP of crops were estimated on the basis of peak above ground biomass and this value was compared with SPOT – Vegetation NPP product (available at www.geosuccess.net) to generate a regression model. Results indicated that both estimates; ground truth (F 3, 8 = 6.31, p < 0.05) and remotely sensed (F 3, 8 = 271.0, p < 0.001) provided significant C stock variation among sites. Values ranged from 6.8 – 10.9 and 3.2 – 8.8 t C ha -1 yr -1 for GT AG C and RS AG C, respectively (Fig. 1). On an average, in present study remotely sensed data estimated 34% less C in comparison to ground truth data. C stock based on GT and RS were linearly and significantly related (y = 1.32x – 5.82, R 2 =0.92, p = 0.04; where x is GT C stock and y is RS C stock). The significant relationship between these two variables (GT & RS) suggested that large scale C stock may be predicted by using point scale ground truth data. This study also suggests that validation of remotely sensed data with ground truth estimates is very important for actual quantification of C stock at regional and global level. Below ground root C stock significantly varied (F 3, 68 = 10.9, p < 0.00 ) from 0.98 to 1.3 t C ha -1 yr -1 (Fig. 2) for two crop cycle. Below ground root biomass has major potential for C sequestration in soil with each crop cycle in agroecosystems and it contributed 11.2 % total C stock of agroecosystem.

Assessment of agro-ecosystem carbon stock in a part of middle gangetic plains, india

We estimate the distribution of carbon in soil profile in agroecosystems of Indo- Gangetic Plains and explore factors which control this distribution. The soil texture was loam in the upper soil layers but changed to silt loam as the depth increased. Bulk density increased with soil depth, and had a negative relationship with soil organic C. A significant positive correlation between SOC and clay content was observed. About 69 % of soil carbon in the profile was confined to the upper 40 cm soil layer where C stock ranged from 8.5 to 15.2 t C ha -1 . We estimate that the agricultural soils of Indo-Gangetic Plains may contain 12.4 to 22.6 t ha-1 of organic C in the top 1 m soil depth. Since agricultural soils contain significantly lower C content than the soils of natural forest ecosystem in the same climate zone, management practices such as residue placement and reduced or no tillage are required to enhance C sequestration. A mix of agroforestry with crop fields may be an ideal option to enhance C sequestration in soils. Resumen: Estimamos la distribucion de carbono en el perfil del suelo en agroecosistemas de las Planicies Indo-Gangeticas y exploramos los factores que controlan dicha distribucion. La textura del suelo fue franca en las capas superiores del suelo, pero cambio a franco arcillosa conforme aumento la profundidad. La densidad aparente aumento con la profundidad y tuvo una relacion negativa con el C organico del suelo. Se observo una correlacion positiva significativa entre el C organico del suelo y el contenido de arcilla. Alrededor de 69 % del carbono del suelo en el perfil estuvo confinado a los 40 cm mas superficiales de la capa de suelo, donde el almacen de C fluctuo entre 8.5 y 15.2 t C ha -1 . Estimamos que los suelos agricolas de las Planicies Indo-Gangeticas pueden contener entre 12.4 y 22.6 t ha-1 de C organico en el metro superior del perfil del suelo. Dado que los suelos agricolas poseen un contenido significa- tivamente menor de C que lo suelos de ecosistemas forestales naturales en la misma zona climatica, se requieren practicas de manejo tales como la colocacion de residuos y la reduccion o la ausencia de labranza que promuevan el secuestro de C. Una mezcla de agroforesteria con campos agricolas puede ser una opcion ideal para aumentar el secuestro de C en los suelos. Resumo: Estimou-se a distribuicao de carbono no perfil do solo em agro-ecossistemas nas planicies Indo-Gangeticas e explorar os factores que controlam esta distribuicao. A textura do solo era argilosa nas camadas superiores do solo mas mudou para franco-argilosa a medida que aumentava a profundidade. A densidade bruta aumentou com a profundidade do solo, e apresentou uma relacao negativa com o C orgânico. Observou-se um correlacao positiva significativa entre o SOC e o teor de argila. Cerca de 69% do carbono do solo no perfil encontrava-se confinado a camada dos 40 cm superiores onde o stock de C oscilou entre os 8,5 e os 15,2 t C ha-1. Estimou-se que os solos agricolas das planicies Indo-Gangeticas poderao conter entre os 12,4 e os 22,6 t ha-1 de C orgânico na camada superior do 1 m superior da espessura do solo. Dado que na mesma zona climatica os solos agricolas contem significativamente menor teor de C do que os solos dos ecossistemas florestais naturais, praticas de gestao tais como distribuicao de residuos ou lavoura reduzida ou mesmo nao lavoura, sao necessarias para intensificar o sequestro de C. Um misto de agrosilvicultura com campos de cultura pode ser N

Carbon sequestration potential of Indo-Gangetic agroecosystem soils

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