Sugarcane as Future Bioenergy Crop: Potential Genetic and Genomic Approaches

Biofuels are gaining increased scientific as well as public attention to fulfill future energy demands and can be the only potential candidates to safeguard and strengthen energy security by reducing the world’s reliance on exhausting fossil energy sources. Sugarcane is an important C4 crop with great potential to contribute to global biofuel production as sugarcane juice can be easily fermented to produce ethanol. The success of bioethanol production from sugarcane in Brazil has widened the scope of the technology and has led to increased demand of purpose-grown sugarcane for biofuel production. Scientific interventions have not only helped to improve the cane crop but industrial procedures have also been upgraded resulting in improved production of bioethanol. Likewise, advancements in omics have led to high hopes for the development of energy cane. This chapter highlights the advancements as well as potential and challenges in the production of sugarcane biofuel, focusing on genetic and genomic interventions improving the crop as energy-cane. Further, controversies in the production and usage of biofuel derived from sugarcane have also been discussed

Emerging Trends to Improve Tropical Plants: Biotechnological Interventions

Tropical plants are an integral part of the ecosystem and are of significance for the well-being of humanity. Since their domestication in 10,000 BC, conventional breeding has played a crucial role in their conservation and widespread adaptation worldwide. Advancements in multi-omics approaches, that is, genomics, metabolomics, transcriptomics, proteomics, whole genome sequencing, and annotation, have led to the identification of novel genes involved in crucial metabolic pathways, thus helping to develop tropical plant varieties with desirable traits. Information retrieved from the pan-genome, super-pan-genome, and pan-transcriptome has further uplifted marker-assisted selection and molecular breeding. Tissue culture techniques have not only helped to conserve endangered plant species but have also opened up new avenues in terms of mass-scale propagation of ornamental plants. Transgenic technology is increasingly contributing to the betterment of tropical plants, and different plant species have been engineered for valuable traits. Likewise, genome editing is appearing to be a promising tool to develop tropical plants having the potential to fulfill future needs. Hence, this chapter highlights the importance of conventional and modern scientific approaches for the conservation and improvement of tropical plant species

Determination of genotype differences through restriction endonuclease in Camels (Camelus dromedarius)

Tyrosinase gene or C locus has long been implicated in the coat colour determination. This gene a copper-containing enzyme located on chromosome 11q14.3 is expressed in melanocytes and controls the major steps in pigment production. In camel, C locus a restriction site provoked by the T variant of the mutation was used in a special restriction fragment length polymorphism analysis (PCR-RFLP) for genotyping of camels from six different Pakistani camel breeds (Marecha, Dhatti, Larri, Kohi, Campbelpuri and Sakrai). Significant differences in the genotype frequency between the breeds were estimated. The Sakrai breed showed in comparison to other studied breeds a distinctly higher frequency of the homozygous with restriction genotype. The objective of the present study was to screen the camel breeds using modern genetic technique that have been so far classified on the basis of performance and tribal ownership.Keywords: Camel, genotype, restriction endonucleas

Application of Geospatial Techniques in Agricultural Resource Management

Although technological advancements have sparked the beginning of the fourth agricultural revolution, human beings are still facing severe problems such as shrinking croplands, dwindling water supplies, negative consequences of climate change, and so on in achieving agricultural resilience to meet the demands of the growing population over the globe. Geospatial techniques involving the integrated use of geographic information system (GIS), remote sensing (RS), and artificial intelligence (AI) provide a strong basis for sustainable management of agricultural resources aimed at increased agricultural production. In recent times, these advanced tools have been increasingly used in agricultural production at local, regional, and global levels. This chapter focuses on the widespread application of geospatial techniques for agricultural resource management by monitoring crop growth and yield forecasting, crop disease and pest infestation, land use and land cover mapping, flood monitoring, and water resource management. Moreover, we also discuss various methodologies involved in monitoring and mapping abovementioned agricultural resources. This chapter will provide deep insight into the available literature on the use of geospatial techniques in the monitoring and management of agricultural resources. Moreover, it will be helpful for scientists to develop integrated methodologies focused on exploring satellite data for sustainable management of agricultural resources

Sustainable Irrigation Management for Higher Yield

Sustainable irrigation is sensible application of watering to plants in agriculture, landscapes that aids in meeting current survival and welfare needs. Sustainable irrigation management can help with climate change adaptation, labor, energy savings, and the production of higher-value and yield of crops to achieve zero hunger in water-scarce world. To ensure equal access to water and environmental sustainability, investments in expanded and enhanced irrigation must be matched by improvements in water governance. Sustainable irrigation must be able to cope with water scarcity, and be resilient to other resource scarcities throughout time in context of energy and finance. The themes and SDGs related to clean water, water resources sustainability, sustainable water usage, agricultural and rural development are all intertwined in the concept of “sustainable irrigation for higher yield.” Sustainable irrigation management refers to the capability of using water in optimum quantity and quality on a local, regional, national, and global scale to meet the needs of humans and agro-ecosystems at present and in the future to sustain life, protect humans and biodiversity from natural and human-caused disasters which threaten life to exist. Resultantly higher yields will ensure food security

Assessment and Monitoring of VIIRS-DNB and SQML-L light Pollution in Lahore-Pakistan

The usage of artificial light is excessive and improper. Earth's night picture has changed significantly from space and studies have shown that over-exposure to artificial light in the night can influence animals, the environment and human beings. The purpose of this study was to monitor and measure skylights of Lahore City and temporary light pollution from 2012-2019. The Suite-Day/Night band of the Visible Image Radiometer was used for time changes analysis with GIS and Remote Sensing tools. Indicators were established as a table tool through zonal statistics, and a field survey was also undertaken to measure the Sky-Glow of Lahore with Sky Quality Meter-L. The results suggest that from 2012 to 2019, light pollution rose by 23.43 percent. Results suggest that around 53.99% of Lahore suffered from light pollution. The number of lights in Lahore has increased by 161.82 percent between 2012 and 2019. In the study period, the mean night light and the standard night light deviation were 127.87 and 98.22 percent, respectively. Lahore's night sky was heavily polluted by light. Lahore's average skylight is 17.15 meters above sea level, which means low quality skies at night. This research aims to provide people an insight into light pollution and the causes of local light pollution. Furthermore, this study aims to enhance public attention to light pollution mitigation attempts by governments and politicians. Full Tex

Intelligent and Smart Irrigation System Using Edge Computing and IoT

Smart parsimonious and economical ways of irrigation have build up to fulfill the sweet water requirements for the habitants of this world. In other words, water consumption should be frugal enough to save restricted sweet water resources. The major portion of water was wasted due to incompetent ways of irrigation. We utilized a smart approach professionally capable of using ontology to make 50% of the decision, and the other 50% of the decision relies on the sensor data values. The decision from the ontology and the sensor values collectively become the source of the final decision which is the result of a machine learning algorithm (KNN). Moreover, an edge server is introduced between the main IoT server and the GSM module. This method will not only avoid the overburden of the IoT server for data processing but also reduce the latency rate. This approach connects Internet of Things with a network of sensors to resourcefully trace all the data, analyze the data at the edge server, transfer only some particular data to the main IoT server to predict the watering requirements for a field of crops, and display the result by using an android application edge

Assessment and Monitoring of VIIRS-DNB and SQML-L light Pollution in Lahore-Pakistan

The usage of artificial light is excessive and improper. Earth's night picture has changed significantly from space and studies have shown that over-exposure to artificial light in the night can influence animals, the environment and human beings. The purpose of this study was to monitor and measure skylights of Lahore City and temporary light pollution from 2012-2019. The Suite-Day/Night band of the Visible Image Radiometer was used for time changes analysis with GIS and Remote Sensing tools. Indicators were established as a table tool through zonal statistics, and a field survey was also undertaken to measure the Sky-Glow of Lahore with Sky Quality Meter-L. The results suggest that from 2012 to 2019, light pollution rose by 23.43 percent. Results suggest that around 53.99% of Lahore suffered from light pollution. The number of lights in Lahore has increased by 161.82 percent between 2012 and 2019. In the study period, the mean night light and the standard night light deviation were 127.87 and 98.22 percent, respectively. Lahore's night sky was heavily polluted by light. Lahore's average skylight is 17.15 meters above sea level, which means low quality skies at night. This research aims to provide people an insight into light pollution and the causes of local light pollution. Furthermore, this study aims to enhance public attention to light pollution mitigation attempts by governments and politicians. Full Tex