Castor bean (Ricinus communis L.) locally known as “arind” or “arindi” is non- edible oilseed crop with enormous significance having almost 700 uses. Keeping in view the potential of castor as a cash crop, a study was carried out to investigate germination rate index (GRI) of different cultivars, optimum sowing date and appropriate seed source for adaptability, stand establishment and suitability under diverse environmental conditions of Pothowar (Pakistan). For the purpose, a hypothesis was developed “Castor bean can be economically beneficial cop of Pothwar region” To evaluate this hypothesis, three types of experiments including in vitro experiments, sowing date and seed source trials were conducted. In vitro experiments were of two types. In the first experiment, the seed of four castor bean cultivars (DS-30, PR-7/1, PR-101, Local) was conditioned to different moisture levels i.e. 0, -700 and - 1400 kPa under different temperature levels (10, 15, 20, 25, 30 and 35°C) in growth chamber to determine germination rate index. The results showed that GRI of cultivars differed significantly on the basis of temperature and moisture levels. The cultivar DS- 30 showed the highest GRI value followed by PR-101 and minimum value for Local cultivar. All the cultivars showed a downward trend for germination at 10°C and 15°C at -1400 kPa osmotic pressure. In the second experiment, seed of commercial cultivar, DS-30 was collected from three different locations of Bahawalpur, Faisalabad and Tandojam and tested under same temperature and moisture levels as in first experiment. Germination rate index differed significantly with respect to seed sources as well as temperature regimes. Maximum germination rate index was observed in the Faisalabad seed source followed by the Tandojam seed source, while the Bahawalpur seed source xxishowed the lowest germination rate index value. As regards moisture levels, the highest GRI value was noted in 0 kPa (control) while minimum at -1400kPa. Regarding field trials, the same four cultivars as used in in vitro trial, were sown in July and August during 2004 and 2005 with four sowing dates (15 th July, 30 th July, 15 th August, 30 th August) at three locations (Islamabad, Attock, Chakwal). The cultivar DS-30 had greater emergence percentage, plant height, seed yield, number of capsules plant -1 , seed weight plant -1 , 100-seed weight and yield ha -1 than the other cultivars. Similarly the crop planted in July gave significantly better results compared to August sowing. The cultivar DS-30 had higher oil content, oil yield, palmitic acid and linoleic acid, whereas ricinoleic acid was comparable to other cultivars. The highest value for ricinoleic was found in Local cultivar. To determine the better seed source for Pothowar Plateau, DS-30 seed produced under different temperature and rainfall patterns (Faisalabad, Tandojam, Bahawalpur) was tested in the second field trial at same three locations as used in sowing date trial. Faisalabad seed source performed better regarding most of the growth parameters as compared to others. Tandojam seed source crop produced higher oil content and protein percentages compared to the rest of seed sources. However, seed source has a nominal effect on oil content, protein percent and fatty acid profile. As castor been cultivation in Pakistan has been on a regular decline since 1979, its cultivation is now restricted to marginal areas of the country and Pothwar region of Punjab. In order to revive its cultivation, it was imperative to conduct an ex ante economic analysis with other competing crops of the area to examine its diffusion potential in Pothwar region. Moreover, the relative success of castor bean cultivation in different parts of the region was also carried out to assess its potential at different xxiirainfall zones of the area. Our findings show that castor bean cultivation can be a profitable option for farmers as a kharif crop provided it is planted at optimum time (July) along with high yielding cultivar (DS-30). Stability analysis of four castor bean cultivars over three locations revealed that PR-101 is the stable cultivar at all three locations of Pothowar although its yield was comparatively lower than DS-30. However, DS-30 can also be appropriate cultivar for all the locations especially Islamabad and Attock as its yield was highest among the cultivars.
لسانیات اورمعاشرتی روابط Language is fundamental to any society. It is through language that we can communicate our thoughts to others. The more a language is used, the more it will develop. There are many types of languages including mother tongue, regional language, religious language, official language, business language, national language, international language and so on. When speaking, language and ascent are not taken into consideration, but there is a need to be careful while writing. People who cannot speak a language use specific gestures or symbols to convey their point of view to others. Therefore, we can say that the use of language began as soon as man came into this world.
Biological sequences consist of A C G and T in a DNA structure and contain vital information of living organisms. The development of computing technologies, especially NGS technologies have increased genomic data at a rapid rate. The increase in genomic data presents significant research challenges in bioinformatics, such as sequence alignment, short-reads error correction, phylogenetic inference, etc. Next-generation high-throughput sequencing technologies have opened new and thought-provoking research opportunities. In particular, Next-generation sequencers produce a massive amount of short-reads data in a single run. However, these large amounts of short-reads data produced are highly susceptible to errors, as compared to shotgun sequencing. Therefore, there is a peremptory demand to design fast and more accurate statistical and computational tools to analyze these data. This research presents a novel and robust algorithm called HaShRECA for genome sequence short reads error correction. The developed algorithm is based on a probabilistic model that analyzes the potential errors in reads and utilizes the Hadoop-MapReduce framework to speed up the computation processes. Experimental results show that HaShRECA is more accurate, as well as time and space efficient as compared to previous algorithms.