Nutrigenomics: An Interface of Gene-Diet-Disease Interaction

Healthy diet and proper nutrition are basic necessity of life and play a key role in preventing diseases. Nutrigenomics (NG) is an emerging approach in nutritional research which deals with the gene-diet interactions. The concept of nutrigenomics is not new and it is commonly associated with “inborn errors of metabolism”, the rare genetic (inherited) disorders in which the body cannot properly turn food into energy. These disorders are related to insufficient availability of metabolic enzymes or cofactors due to alteration of gene. Usually cure of these diseases lies in restricted diet. Presently non communicable diseases (NCDs) like cardiovascular diseases, obesity, diabetes and cancers are outnumbering the other health ailments among the different human populations of world. The main reason behind the occurrence of these NCDs is the abruptly changing life style and food habits after industrial revolution. With the advent of industrial revolution and economical concerns, the life style of people across the world has changed so much so that it resulted in approximately millions of death cases due to these NCDs. Study related to NG is one step forward in nutritional research involving the techniques of nutrition, molecular biology, genomics, bioinformatics, molecular medicine and epidemiology together to understand the role of food as an epigenetic factor which unravel its role in the occurrence of these diseases. Hence, under the prevailing scenario of world health, it has become an urgency to boost NG research to find cure for dreaded diseases caused due to lack of healthy food and improper nutrition. Thus, such type of research findings ensures the effective benefit of genomic revolution for mankind near future

Seed Priming: An Interlinking Technology between Seeds, Seed Germination and Seedling Establishment

Biologically seed is a small embryonic plant along with either endosperm or cotyledons, enclosed with in an outer protecting covering called seed coat. During the time of seed development large metabolic conversions take place, including proper partitioning of photo-assimilates and the formation of complex polymeric forms of carbohydrate, protein and fats for storing as seed reserves. In developing phase of seeds, every detail information stored in the embryonic plant are genetically and sometimes epigenetically also predetermined and influenced by various environmental/external factors already faced by the mother plant. In the growth cycle of plants, seed germination and seedling establishment are the two critical phases where survivability of the seedlings in natural habitats is a matter of question until the onset of photosynthesis by the established seedling. The various sequence of complex processes known to occur in both the phases i.e., an array of metabolic activities are initiating which eventually leads to the renewal of embryo growth of the dormant seeds and ultimately seedlings are established. Efficient seed germination is an important factor for agricultural sciences and successful establishment of germinated seedling requires a rapid and uniform emergence and root growth. With these aspects of seed physiology kept in mind the present chapter will be designed in such a way where, a gap filling, inter linking, eco- and farmers\u27 friendly technology i.e., ‘seed priming’ (a pre-sowing partial hydration of seeds) will be considered to improve the rate and uniformity of germination and seedling establishment. Under optimal and adverse environmental conditions, the primed seeds of diversified species lead to an enhanced germination performance with increased vigor index has been reported by various scientists which indicates a good establishment of seedlings in the field and thereafter enhance the performance of crops as a whole

Projecting Climate and Land Use Change Impacts on Actual Evapotranspiration for the Narmada River Basin in Central India in the Future

Assessment of actual evapotranspiration (ET) is essential as it controls the exchange of water and heat energy between the atmosphere and land surface. ET also influences the available water resources and assists in the crop water assessment in agricultural areas. This study involves the assessment of spatial distribution of seasonal and annual ET using Surface Energy Balance Algorithm for Land (SEBAL) and provides an estimation of future changes in ET due to land use and climate change for a portion of the Narmada river basin in Central India. Climate change effects on future ET are assessed using the ACCESS1-0 model of CMIP5. A Markov Chain model estimated future land use based on the probability of changes in the past. The ET analysis is carried out for the years 2009-2011. The results indicate variation in the seasonal ET with the changed land use. High ET is observed over forest areas and crop lands, but ET decreases over crop lands after harvest. The overall annual ET is high over water bodies and forest areas. ET is high in the premonsoon season over the water bodies and decreases in the winter. Future ET in the 2020s, 2030s, 2040s, and 2050s is shown with respect to land use and climate changes that project a gradual decrease due to the constant removal of the forest areas. The lowest ET is projected in 2050. Individual impact of land use change projects decreases in ET from 1990 to 2050, while climate change effect projects increases in ET in the future due to rises in temperature. However, the combined impacts of land use and climate changes indicate a decrease in ET in the future

Uncertainty analysis of soil erosion modelling using different resolution of open-source DEMs

The Digital Elevation Model (DEM) is one of the important parameters of soil erosion assessment and notable uncertainties are found in using different resolutions of the DEM. Revised Universal Soil Loss Equation model has been applied to analyze the effect of open-source DEMs with different resolution and accuracy on the uncertainties of soil erosion modelling in a part of the Narmada river basin in Madhya Pradesh in central India. Selected open-source DEMs are GTOPO30 (1 km), SRTM (30 and 90 m), CARTOSAT (30 m) and ASTER (30 m), used for estimating erosion rate. Results with better accuracy are achieved with the high-resolution DEMs (30 m) with higher vertical accuracy than the coarse resolution DEMs with lower accuracy. This study has presented potential uncertainties introduced by the open-source DEMs in soil erosion modelling for better understanding of appropriate selection and acceptable errors for researchers

Future changes in rainfall, temperature and reference evapotranspiration in the central India by least square support vector machine

Climate change affects the environment and natural resources immensely. Rainfall, temperature and evapotranspiration are major parameters of climate affecting changes in the environment. Evapotranspiration plays a key role in crop production and water balance of a region, one of the major parameters affected by climate change. The reference evapotranspiration or ET0 is a calculated parameter used in this research. In the present study, changes in the future rainfall, minimum and maximum temperature, and ET0 have been shown by downscaling the HadCM3 (Hadley Centre Coupled Model version 3) model data. The selected study area is located in a part of the Narmada river basin area in Madhya Pradesh in central India. The downscaled outputs of projected rainfall, ET0 and temperatures have been shown for the 21st century with the HADCM3 data of A2 scenario by the Least Square Support Vector Machine (LS-SVM) model. The efficiency of the LS-SVM model was measured by different statistical methods. The selected predictors show considerable correlation with the rainfall and temperature and the application of this model has been done in a basin area which is an agriculture based region and is sensitive to the change of rainfall and temperature. Results showed an increase in the future rainfall, temperatures and ET0. The temperature increase is projected in the high rise of minimum temperature in winter time and the highest increase in maximum temperature is projected in the pre-monsoon season or from March to May. Highest increase is projected in the 2080s in 2081–2091 and 2091–2099 in maximum temperature and 2091–2099 in minimum temperature in all the stations. Winter maximum temperature has been observed to have increased in the future. High rainfall is also observed with higher ET0 in some decades. Two peaks of the increase are observed in ET0 in the April–May and in the October. Variation in these parameters due to climate change might have an impact on the future water resource of the study area, which is mainly an agricultural based region, and will help in proper planning and management

Change in rainfall erosivity in the past and future due to climate change in the central part of India

Temporal change in rainfall erosivity varies due to the rainfall characteristic (amount, intensity, frequency, duration), which affects the conservation of soil and water. This study illustrates the variation of rainfall erosivity due to changing rainfall in the past and the future. The projected rainfall is generated by SDSM (Statistical DownScaling Model) after calibration and validation using two GCMs (general circulation model) data of HadCM3 (A2 and B2 scenario) and CGCM3 (A1B and A2 scenario). The selected study area is mainly a cultivable area with an agricultural based economy. This economy depends on rainfall and is located in a part of the Narmada river basin in central India. Nine rainfall locations are selected that are distributed throughout the study area and surrounding. The results indicate gradually increasing projected rainfall while the past rainfall has shown a declined pattern by Mann–Kendall test with statistical 95% confidence level. Rainfall erosivity has increased due to the projected increase in the future rainfall (2080 s) in comparison to the past. Rainfall erosivity varies from −32.91% to 24.12% in the 2020s, −18.82 to 75.48% in 2050 s and 20.95–202.40% in 2080s. The outputs of this paper can be helpful for the decision makers to manage the soil water conservation in this study area

A comparative study of soil erosion modelling by MMF, USLE and RUSLE

The quantitative assessment of spatial soil erosion is valuable information to control the erosion. The study area in a part of Narmada river in central India is selected. The main objective is to assess and compare the results obtained from three soil erosion models using GIS platform. Variation in the rate of erosion of the three models is compared considering varying slope, soil and land use of the area. Three models selected are Morgan–Morgan–Finney (MMF), Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE). The best fit or the most reliable model for the study area is selected after validation with the observed sedimentation data. The results give –39.45%, –9.60% and 4.80% difference in the values of sedimentation by MMF, USLE and RUSLE, respectively, from the observed data. Finally, RUSLE model has been found to be most reliable for the study area

Uncertainty of soil erosion modelling using open source high resolution and aggregated DEMs

Digital Elevation Model (DEM) is one of the important parameters for soil erosion assessment. Notable uncertainties are observed in this study while using three high resolution open source DEMs. The Revised Universal Soil Loss Equation (RUSLE) model has been applied to analysis the assessment of soil erosion uncertainty using open source DEMs (SRTM, ASTER and CARTOSAT) and their increasing grid space (pixel size) from the actual. The study area is a part of the Narmada river basin in Madhya Pradesh state, which is located in the central part of India and the area covered 20,558 km2. The actual resolution of DEMs is 30 m and their increasing grid spaces are taken as 90, 150, 210, 270 and 330 m for this study. Vertical accuracy of DEMs has been assessed using actual heights of the sample points that have been taken considering planimetric survey based map (toposheet). Elevations of DEMs are converted to the same vertical datum from WGS 84 to MSL (Mean Sea Level), before the accuracy assessment and modelling. Results indicate that the accuracy of the SRTM DEM with the RMSE of 13.31, 14.51, and 18.19 m in 30, 150 and 330 m resolution respectively, is better than the ASTER and the CARTOSAT DEMs. When the grid space of the DEMs increases, the accuracy of the elevation and calculated soil erosion decreases. This study presents a potential uncertainty introduced by open source high resolution DEMs in the accuracy of the soil erosion assessment models. The research provides an analysis of errors in selecting DEMs using the original and increased grid space for soil erosion modelling

Flood monitoring using microwave remote sensing in a part of Nuna river basin, Odisha, India

Floods adversely affect the life of people and property in the coastal districts. It is important to delineate the flood extent and pattern which helps in the vulnerability assessment and also to find out the intensity of damages to facilitate future planning and management. The study area is a part of the Nuna river basin, which suffers from the flood disasters frequently. The present study applies microwave remote sensing (RADARSAT-1 images) to monitor extent, depth and duration of 2003 and 2008 floods in the Kendrapara district of Odisha, India. RADARSAT-1 images of 4, 11, 13 and 20 September of 2003 and 18, 20, 22 and 24 September of 2008 were used to monitor the flood extent, duration and depth. The threshold method was used to delineate flood extent which was used for calculating flood duration and depth. Further, vulnerability assessment of the paddy crop was done to obtain intensity of damage in the area from the 2003 and 2008 floods. Field survey was done to verify and assess the generated results. Areas affected by more than 15 days of flood duration and depth of more than 3 m faced maximum loss. Both the years witnessed major floods in this area with an estimated damage of around INR 174 million ($3.6 million) in 2003 and INR 75 million ($1.6 million) in 2008