Phenylalanine ammonia-lyase (PAL) is the first enzyme in the phenylpropanoid pathway and plays a vital role in adoption, growth, and development in plants but in wheat its characterization is still not very clear. Here, we report a genome-wide identification of TaPAL genes and analysis of their transcriptional expression, duplication, and phylogeny in wheat. A total of 37 TaPAL genes that cluster into three subfamilies have been identified based on phylogenetic analysis. These TaPAL genes are distributed on 1A, 1B, 1D, 2A, 2B, 2D, 4A, 5B, 6A, 6B, and 6D chromosomes. Gene structure, conserved domain analysis, and investigation of cis-regulatory elements were systematically carried out. Chromosomal rearrangements and gene loss were observed by evolutionary analysis of the orthologs among Triticum urartu, Aegilops tauschii, and Triticum aestivum during the origin of bread wheat. Gene ontology analysis revealed that PAL genes play a role in plant growth. We also identified 27 putative miRNAs targeting 37 TaPAL genes. The high expression level of PAL genes was detected in roots of drought-tolerant genotypes compared to drought-sensitive genotypes. However, very low expressions of TaPAL10, TaPAL30, TaPAL32, TaPAL3, and TaPAL28 were recorded in all wheat genotypes. Arogenate dehydratase interacts with TaPAL29 and has higher expression in roots. The analysis of all identified genes in RNA-seq data showed that they are expressed in roots and shoots under normal and abiotic stress. Our study offers valuable data on the functioning of PAL genes in wheat.

This paper examines the global competitiveness of Pakistan’s fruit exports (dates, mangoes, and oranges), using revealed comparative advantage (RCA). It also analyzes domestic consumption trends among selected fruits grown by major exporters. Our results indicate that Pakistan has a comparative advantage in fruit exports. Comparing the movement in comparative advantage indices for Pakistan with those of its main exporters/competitors demonstrates that Pakistan has a relatively high comparative and competitive advantage in the production of dates and mangoes. The increasing trend of competitiveness in Pakistan indicates that there is potential for higher growth; given that fruit exports are a potential source of higher exports earnings, there is a need to strengthen competitiveness in this sector.

The edible oil imports bill rising from Rs. 77 million in 1969-70 to Rs. 3,900 million in 2002-03 has overburdened the economy of the country. Only 30% of the total needs are met through local production, while 70% are provided by import. Major share of the domestic production of edible oil comes from cottonseed and canola, 67 and 19.6%, respectively. The remaining 13.4% are contributed mainly by sunflower. Although it is a high oil, high yielding crop that gives high returns to the farmers, no serious effort has been made to increase the local production of sunflower. Consequently, the sunflower acreage declined from 144,191 ha in 1998-99 to 107,717 ha in 2002-03 and the production from 194,544 to 128,531 t during the same period. The 1998-99 acreage was the maximum area under sunflower achieved. The big fluctuations in sunflower acreage and production are due to its price on the market. In the period of last 15 years, the sunflower acreage in Pakistan expended from 29,500 to 107,700 ha. The sunflower production rose at the annual rate of 9.9%, comprised of a 9.7% expansion in acreage and a minor improvement in productivity amounting to 0.16%. This increase was not sufficient to meet the requirements of the country. There is a big gap between the potential and actual yields of sunflowers. More than 70% of the potential have not been achieved yet. For this purpose the R 2 value was also calculated and, keeping in view the fluctuations in the time series data, second-degree equation was also measured. Logarithmic and exponential functions were also tested but the variability in the data measured by the R 2 value was best represented by seconddegree polynomial function. When the data seem to depart more or less widely from linearity in regression or time series analysis we must consider fitting some other curve instead of the straight line. The R 2 value was also improved with second-degree polynomial function for production from 43% to 58% showing a better fit of the trend line. The sum of the error terms was "0" for second-degree polynomial function but it gave a better fit due to a higher R 2 value. The higher b value for production portrays an increase in the productivity. The sum of squares for the estimated and observed values was 0. However, due to a low value of the coefficient of determination with linear trend and variation in the data, second-degree polynomial function (parabola) was estimated which gave a higher value of the coefficient of determination. With the use of

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