No abstract

Over the last several decades, increased agricultural production has been driven by improved agronomic practices and a dramatic increase in the use of nitrogen-containing fertilizers to maximize the yield potential of crops. To reduce input costs and to minimize the potential environmental impacts of nitrogen fertilizer that has been used to optimize yield, an increased understanding of the molecular responses to nitrogen under field conditions is critical for our ability to further improve agricultural sustainability. Using maize (Zea mays) as a model, we have characterized the transcriptional response of plants grown under limiting and sufficient nitrogen conditions and during the recovery of nitrogen-starved plants. We show that a large percentage (approximately 7%) of the maize transcriptome is nitrogen responsive, similar to previous observations in other plant species. Furthermore, we have used statistical approaches to identify a small set of genes whose expression profiles can quantitatively assess the response of plants to varying nitrogen conditions. Using a composite gene expression scoring system, this single set of biomarker genes can accurately assess nitrogen responses independently of genotype, developmental stage, tissue type, or environment, including in plants grown under controlled environments or in the field. Importantly, the biomarker composite expression response is much more rapid and quantitative than phenotypic observations. Consequently, we have successfully used these biomarkers to monitor nitrogen status in real-time assays of field-grown maize plants under typical production conditions. Our results suggest that biomarkers have the potential to be used as agronomic tools to monitor and optimize nitrogen fertilizer usage to help achieve maximal crop yields.

A Chow test was applied to analyze the structural changes in GDP of India with respect to Fisheries GDP obtained from the states of Andhra Pradesh and Tamil Nadu using Unrestricted and Restricted Linear Regression models in matrix notation for the period of 2000–01 to 2013–14. The GDP and Fisheries GDP data pertaining to the state of Andhra Pradesh and Tamil Nadu for the periods 2000–01 to 2006–07 and 2007–08 to 2013–14 were also collected for analyzing the structural changes between earmarked two periods as well as states from 2000–01 to 2013–14. In this study, the Chow test revealed that there was no structural change between the total GDP of India and Fisheries GDP with respect to the states Andhra Pradesh and Tamil Nadu during the periods 2001–2007 and 2008 –2014. However, significant structural changes could be observed between the GDP of India and Fisheries GDP obtained from the states of Andhra Pradesh and Tamil Nadu during the period 2000–2001 to 2013–14.However, there was a positive trend of structural change observed in the states Andhra Pradesh and Tamil Nadu with respect to the GDP of India and Fisheries GDP during the period 2000–2001 to 2012–14. Owing to theses, it is concluded that the contribution of fisheries with respect to the country’s GDP between the periods made a significant structural change however no many structural changes were observed in two time periods within the states.