Q-Learning Induced Artificial Bee Colony for Noisy Optimization

The paper proposes a novel approach to adaptive selection of sample size for a trial solution of an evolutionary algorithm when noise of unknown distribution contaminates the objective surface. The sample size of a solution here is adapted based on the noisy fitness profile in the local surrounding of the given solution. The fitness estimate and the fitness variance of a sub-population surrounding the given solution are jointly used to signify the degree of noise contamination in its local neighborhood (LN). The adaptation of sample size based on the characteristics of the fitness landscape in the LN of a solution is realized here with the temporal difference Q-learning (TDQL). The merit of the present work lies in utilizing the reward-penalty based reinforcement learning mechanism of TDQL for sample size adaptation. This sidesteps the prerequisite setting of any specific functional form of relationship between the sample size requirement of a solution and the noisy fitness profile in its LN. Experiments undertaken reveal that the proposed algorithms, realized with artificial bee colony, significantly outperform the existing counterparts and the state-of-the-art algorithms

Migration in Multi-Population Differential Evolution for Many Objective Optimization

The paper proposes a novel extension of many objective optimization using differential evolution (MaODE). MaODE solves a many objective optimization (MaOO) problem by parallel optimization of individual objectives. MaODE involves N populations, each created for an objective to be optimized using MaODE. The only mode of knowledge transfer among populations in MaODE is the modified version of mutation policy of DE, where every member of the population during mutation is influenced by the best members of all the populations under consideration. The present work aims at further increasing the communication between the members of the population by communicating between a superior and an inferior population, using a novel migration strategy. The proposed migration policy enables poor members of an inferior population to evolve with a superior population. Simultaneously, members from the superior population are also transferred to the inferior one to help it improving its performance. Experiments undertaken reveal that the proposed extended version of MaODE significantly outperforms its counterpart and the state-of-the-art techniques

Effect of super-optimal levels of fertilizers on soil enzymatic activities during growth stages of wheat crop on an Inceptisol

A field experiment was conducted during 2010-2011 and 2011-2012 to investigate the effect of optimal (100% NPK) to super-optimal doses (200% NPK) of mineral fertilizers on soil enzymes such as dehydrogenase (DHA), acid phosphatase (Ac-PA), alkaline phosphatase (Alk-PA), fluorescien diacetate hydrolysis (FDA), urease and nitrate reductase (NRA) at three physiological stages (CRI, anthesis and maturity) of wheat crop on an Inceptisol. Dehydrogenase activity was reduced by 28-37% when fertilizer application was at super-optimal dose (200% NPK), whereas, urease and NRA responded positively in the range of 43-44% and 213-231% respectively. Alk-PAwas 7.3-7.9% higher in treatments receiving 125% NPK as compared to control (100% NPK); whereas, Ac-PA declines in the plots receiving 175 and 200% of recommended dose of fertilizer (RDF) as compared to 150% NPK levels. Addition of 175% RDF increased the FDA to the tune of 46-53% as compared to 100% NPK. A significant (P?0.05) positive interaction between fertilizer treatments and physiological stages of wheat growth was observed on soil enzyme activities (except urease and NRA) being highest at the anthesis stage of wheat. Correlation matrix analysis showed that DHA was correlated with the studied enzyme activities except Ac-PA and FDA; whereas, strong correlation was observed between urease and NRA (r=0.981, P=0.01). This study provides theoretical and practical base for avoiding super optimal application of fertilisers which hinders the enzyme activities and vis-a-vis sustainable nutrient enrichment under rhizosphere

Biochemical estimation of phytic acid and inorganic phosphate in diverse maize germplasm to identify potential donor for low phytic acid (LPA) trait in tropical genetic background

Not AvailablePhytic acid (PA), an anti-nutritional factor in maize (Zea mays L.) grains form various salts by chelating essential vital mineral elements namely, Fe3+, Zn2+, Mg2+, etc. affecting their bioavailability. Low phytic acid (LPA) maize can play a vital role as an important food and feed crop to diversify the existing food basket to address micronutrient malnutrition. Globally efforts to identify LPA maize genotypes in the existing germplasm are limited. Keeping this in view, the present experiment was designed using the diverse set of maize germplasm including landraces, composites, inbred lines and hybrids of field corn and also some genotypes of quality protein maize and sweet corn to explore the extent of variability for PA in the existing germplasm and to identify the LPA maize genotypes. The mean PA content across 104 genotypes excluding LPA mutants varied from 1.7 mg/g (CML150) to 4.5 mg/g (VMH45) whereas inorganic phosphate (Pi) varied from 0.07 mg/g (LM16) to 0.95 mg/g (PMH9). The correlation coefficient between PA and Pi across genotypes was negative but moderate (-0.35) (P = 0.00024). The present study has identified two inbred lines namely, CML150 (1.7 mg/g) and CML176 (1.8 mg/g) which do not differ significantly with either of the two LPA mutants namely, LPA1 (1.3 mg/g) and LPA2 (1.7 mg/g). The study further indicated that PA content is generally low in white kernel colour germplasm as compared to other kernel colours. The identified genotypes could be potential donor for developing LPA maize genotypes and also their utilization in the breeding for development of LPA maize cultivars.Not Availabl

Is Urban Economic Growth Inclusive in India?

This paper measures the overall inclusive growth of a city by considering changing trends in the key economic variables based on ‘Borda ranking’ and establishes a relationship between city economic growth and overall city inclusive growth. By using data of 52 large cities in India, this paper finds that higher urban economic growth is associated with an increase in urban inequality, a reduction in urban poverty, and a lower level of overall inclusive growth of a city

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Not AvailableMaize is an important cereal crop after wheat and rice. It is grown on a wide range of environments across the world. Genotype × environment interaction affects the relationship between phenotype and genotype of in breeding programmes, particularly for quantitative traits. So multi environment trials (MET) are used for evaluation and identification of stable genotypes across the environments. So, to assess the differential performance of the 18 genotypes, an experiment was conducted under three different locations and different environments viz., Ludhiana, Godhra and Varanasi under irrigated, rainfed and drought condition, respectively during kharif 2017. Randomized completely block design (RCBD) along with two replications was used. Data was recorded for grain yield and then subjected to additive main effects and multiplicative interaction (AMMI) analysis to understand the interactions between genotypes and environment and identify the stable genotypes. In AMMI1 biplot the PC1 explained 65.07 percent of the variation. Genotypes ZH 161434 and ZH 161311 with high mean yield and wider adaptability were found stable across the environments. Genotypes ZH 161038 and ZH 161083 were best performing genotypes under irrigated environment at Ludhiana, whereas under rainfed conditions at Godhra, ZH 161434 and ZH 161093 revealed good grain yield. Genotype ZH 161063 was specifically adapted under drought conditions at Varanasi. The best selected genotypes having wider adaptability across the environments can be used further in the breeding programmes.MTA

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Not AvailableMaize is considered as ‘Queen’ of cereals, however it is deficient in two essential amino acids i.e. lysine and tryptophan. Quality Protein Maize (QPM) has double the amount of tryptophan and lysine content as compared to normal maize. The QPM germplasm has narrow genetic base thereby difficult to improve for high grain yield. The QPM germplasm needs to be diversified through different means like Mass Assisted Selection (MAS) and Multi parent Advanced Generation Inter cross (MAGIC) approach. The present study was conducted keeping in mind the diversification of QPM germplasm using MAGIC approach. A set of 48 inbred lines (24 QPM and 24 normal lines) were selected on the basis of perse performance and these lines were crossed with two diverse testers i.e. LM 13 & LM 14 to generate the information on heterotic grouping and simultaneously diversity studies were also carried out using SSR markers. The dendogram clearly showed that the QPM and normal germplasm is falling in different clusters. Based on heterotic grouping data and diversity analysis the lines were selected for making cross combinations within heterotic groups. The normal lines of one group were crossed with QPM lines of the same group and vice versa. Four crosses were made in similar fashion viz., for heterotic group A, DML 2052 DQL 2111 and DML 1837 DQL 2303and for heterotic group B, DML 1596 DQL 2180 and DML 1812 DQL 2290. The two crosses made for group A will again be crossed among themselves similarly in case of group A and then new lines will be synthesize. Desirable QPM lines will be advanced to next generation based on the biochemical data and these lines after reaching S6 S7 stage, will be tested for per se performance and then best lines will be used for crossing programme for development of new hybridsMTA