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Influence of irradiation (0.05-0.20 kGy) and germination (24-120 hours) in distilled and tap water on phytate, protein and amino acids of soybean, was studied. Phytate values significantly decreased with increasing germination period and irradiation dose (P less than 0.01). Irradiation independently decreased the original phytate (212.0 mg/100 g) to a range value of 205.0-190.0 mg/100 g depending upon dose level. Germination of unirradiated seeds for 120 hours in distilled and tap water lowered the phytate to 55.0 and 94.9 mg/100 g (74.1 and 55.2% reduction) respectively. Maximum destruction of phytate to levels of 20.5 and 50.9 mg/100 g (90.3 and 76.0% reduction) occurred during germination of 0.20 kGy samples for 120 hours in distilled and tap water respectively. Total protein content significantly increased during germination (P less than 0.05) and the increase was more in tap than distilled water. Germination for 120 hours of untreated seeds in tap water increased the essential and decreased non-essential amino acids while in the 0.10 kGy sample, increases in both cases were observed.

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An experiment was conducted to study the effect of different concentrations of gibberellic acid, spacing and nutrient sprays on vegetative and floral parameters of snapdragon (Antirrhinum majus cv. Rocket Pink) at Urban Technological Park, Habak, Srinagar, J&K, India during two successive years in 2017and 2018. Eighteen different treatments with 3 concentrations of gibberellic acid (0 ppm, 100 ppm and 200 ppm), 2 spacings (15 cm x 15 cm and 15 cm x 20 cm) and nutrient sprays (3 sprays, 4 sprays and 5 sprays) were replicated thrice in Completely Randomized Block Design. Original Research Article

Search-based software testing (SBST) is now a mature area, with numerous techniques developed to tackle the challenging task of software testing. SBST techniques have shown promising results and have been successfully applied in the industry to automatically generate test cases for large and complex software systems. Their effectiveness, however, has been shown to be problem dependent. In this paper, we revisit the problem of objective performance evaluation of SBST techniques in light of recent methodological advances -in the form of Instance Space Analysis (ISA) -enabling the strengths and weaknesses of SBST techniques to be visualised and assessed across the broadest possible space of problem instances (software classes) from common benchmark datasets. We identify features of SBST problems that explain why a particular instance is hard for an SBST technique, reveal areas of hard and easy problems in the instance space of existing benchmark datasets, and identify the strengths and weaknesses of state-of-the-art SBST techniques. In addition, we examine the diversity and quality of common benchmark datasets used in experimental evaluations.

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