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Direct seeded aerobic rice (DSR) is an emerging production system in Asia due to declining water availability and labor scarcity. Iron (Fe) deficiency is a severe problem in DSR as Fe2+oxidized to Fe3+and become unavailable to plants. Seed treatment is one of the emerging approaches to deal with Fe deficiency and content in rice crop to compensate this issue. Hence, pot experiment was planned in randomized block design to study the effect of Fe seed priming through different sources, i.e., iron sulfate (FeSO4.7H2O), Chelated iron (Fe-EDTA) and nano iron (FeONPs) and their levels on yield and Fe content in direct seeded aerobic rice (variety PR 126) under sandy loam and silt loam soils with three replications. On an average, seed priming with FeSO4.7H2O solution (1.0% Fe) showed the highest increase in grain yield (12.7%) over the control. On the other hand, increasing dose of Fe from 0.5 to 1.0% through Fe-EDTA showed adverse effects on rice yield due to higher residual effects. The plant height and chlorophyll content in rice plants varied from 26.1 to 42.2 cm and from 30.9 to 35.1 as SPAD value with maximum content in treatment having FeSO4.7H2O (0.5%Fe) in both the soils. The total and ferrous Fe content in rice plants ranged from 42.7 to 62.2 mg kg−1and from 35.8 to 41.0 in harvested grains with the highest content in treatment having Fe-EDTA (0.5%Fe) followed by treatment FeSO4.7H2O (1.0%Fe) and treatment Fe-EDTA (0.25%Fe), respectively. Thus, seed priming of rice with 1.0%Fe solution using FeSO4.7H2O can be used for further studies to reduce Fe malnutrition in global population.

The burgeoning population has forced farmers to grow wheat on light-textured low-zinc (Zn) soils which are otherwise not suitable for wheat cultivation. Growing Zn efficient wheat cultivars under such conditions along with Zn application is a sustainable approach to achieve higher Zn content and crop yield. Hence, screening of Zn efficient bread, durum and triticale wheat genotypes is necessary for their differential response toward foliar Zn application owing to their variable genetic characteristics. A field experiment was conducted on 16 (bread, durum and triticale) wheat genotypes with foliar application of Zn at different physiological stages for two years. Zinc application resulted in a maximum increase of grain and straw yield for the triticale genotype-TL2942 (48.2%) and bread genotype-PBW343U (68.4%) over the control. The grain and straw concentration of Zn increased to a maximum in the durum genotype-HD2967 (68.5%) and bread genotype-PBW 621 (51.2%) over the control. With respect to grain yield efficiency index (GYEI) and grain Zn accumulation efficiency index (ZAEI), PBWZn1 (95.8) and TL2969 (127.9), respectively, responded better to the Zn application. Based on GYEI and ZAEI, the genotypes TL2969, PDW291 were categorized as efficient and responsive, PBWZn1, HD2967, PBW621, PDW274, PBW343U efficient and non-responsive, PDW233, PDW314, PBW677, WHD943, TL2908, PBW725 inefficient and responsive as well as PBW550U, PBW550, TL2942 inefficient and non-responsive. The TL2969, PDW291 genotypes of wheat are most desirable for economical production due to higher yield and more Zn accumulation in low-Zn soil.

Systematic management in the early stage of development helps the software firms to develop a qualitative software product. One of the crucial tasks in the software design phase of software development life cycle is to assign reliabilities to modules based on the overall reliability goal. AHP has been extensively used to allocate reliability among modules on the basis of preferences given by the decision-maker, who can be an industry expert or senior level IT personnel. Their opinions are obtained in linguistic terms and later converted to crisp values for comparison at various levels. This approach incorporates vague decisions, incomplete information and uncertain preferences during decision-making. In this paper, we discuss an allocation method where preferences are assigned in terms of Pythagorean fuzzy numbers based on a hierarchy that relates the users, software engineers and programmer expectations for the software system. The methodology and concepts used have been discussed in detail. The proposed approach has been implemented through an example problem.

It is a challenge for developers to attain the desirable reliability for a software system considering the users and development team's requirements simultaneously. In our present work, we have incorporated intuitionistic fuzzy (IF) set theory with analytical hierarchical process (AHP) for reliability allocation using structured hierarchy for development of multi-software system. The structure shows the interaction between users and experts expectations for a multi-software system that includes software, functions, programs, and modules at different levels. IF-AHP approach avoids any kind of vague or ambiguous decision due to the subjective behaviour of humans and incomplete information. IF numbers has a membership and non-membership function having sum less than 1 along with the hesitancy function. The proposed methodology briefly describes the steps involved in assigning IF priorities and allocating corresponding reliabilities to software, functions, programs and modules respectively. An illustrative example describes the method step-by-step to achieve the set reliability goal.

In the last few decades, a plenty of software reliability growth models with diverse parameters have been formulated and proposed to assess software trustworthiness. Fault reduction factor (FRF) is one such significant factor which has been incorporated in numerous reliability modelling researches in past and results have proved its importance on reliability growth phenomenon. To keep pace with rising demands of the market, software development firms keep upgrading their products in terms of new features and by providing rectification of previously reported defects. In this paper, an SRGM based on NHPP integrating imperfect debugging and time-variable FRF is proposed for multi-release software systems. The model is then tested on the failure datasets of multiple releases of Tandem Computers and Firefox OSS. The experimental results for each release are compared with their corresponding perfect debugging model. Results illustrate that the proposed model fits the failure data well, outperforming perfect debugging model.