Drought is one of the most damaging abiotic stress factors commonly experienced by plants, resulting in a significant loss of crop yield worldwide. The aim of the study was to assess drought tolerance of sunflower (Helianthus annuus) hybrids and find out potentially underlying photobiological traits. Experiment was conducted in the agricultural field of Eastern Mediterranean Agricultural Research Institute in Adana. To evaluate the drought tolerance of twenty-six sunflower hybrids polyphasic chlorophyll fluorescence measurements were performed at the three growth stages named as vegetative, head formation and milky seed (stress 1, S1; stress 2, S2; stress 3, S3, respectively). The hybrids were classified from drought tolerant to drought sensitive based on their drought factor index (DFI) values calculated from photosynthetic performance index. 9444 A X 9947 R and 9444 A X 8129 R were determined as the most tolerant hybrids, whereas 2453 A X 8129 R and 7751 A X TT 135 R were determined as the most sensitive hybrids. Severe drought stress (S2) inhibited severely both the donor and the acceptor sides of photosystem II in sensitive hybrids. Photosynthetic structures of drought-tolerant hybrids were less damaged by drought stress, consequently these hybrids could maintain their photosynthetic performances (minor changes in φ Po , ψ o , δ Ro , specific and/or phenomenological energy fluxes) approximately control levels under severe drought condition. As a result, results, 9444 A X 9947 R and 9444 A X 8129 R hybrids could be recommended to be used in the breeding programs and further studies as genetic material and to be grown in drought-prone areas.

Sunflower (Helianthus annuus L.) suffers from terminal drought accompanying with high temperature stress since it grows mainly in rain fed areas. Therefore, plant breeders try to improve more drought tolerant varieties and to screen their genetic materials for drought resistance. The present study was conducted to determine drought tolerance levels of sunflower male inbred lines developed by Trakya Agricultural Research Institute (TARI), Edirne, Turkey. Inbred lines grown under controlled environmental conditions were sorted by polyphasic chlorophyll a fluorescence measurements. Drought stress applications were performed at three sunflower growth stages as R-3 (vegetative), R5-1 (head formation) and R-6 (milky seed). Based on applied different JIP-Test (analysis of O-J-I-P fluorescence transient) parameters such as Drought Factor index (-DFI)and Damage index (-DI), 70352 R, 8129 R, 0536 R and 9947 R restorer lines were found more drought tolerant than those of the other examined sunflower inbred lines, whereas TT 317 R and TT 199 R were determined as more drought sensitive than others. The drought tolerant inbred lines will be helpful to improve drought resistance in sunflower breeding programs.

The aim of the study was to screen nine inbred lines of sunflower by inducing drought for 10 d and subsequent rewatering for 5 d. Impact of drought was determined by chlorophyll fluorescence and some physiological parameters. Drought led to a decrease in the photosynthetic performance, the quantum yield, and efficiency of electron transport in sunflower lines, while it caused an increase in the absorption flux per reaction centre, dissipation of an active reaction centre, and K-band as well as L-band. Drought also decreased the total chlorophyll contents and water status of the lines, which contributed to photoinhibition. Our results suggested that drought may restrict light harvesting and electron transport in the sunflower lines at various levels. Drought did not cause irreversible membrane damage, since the lines recovered after rewatering. Considering all results, the inbred lines TT317-R and 2478-A were adversely affected by drought when compared to other lines, while 9753-2R exhibited better photosynthetic performance under drought and might be considered as the most tolerant among the lines.

Chickpea (Cicer arietinum L.) is a quite high nutrient and widespread legume that is consumed globally. Similar to many plants, chickpea is sensitive to environmental stresses. The major goal of the breeders is to achieve the most tolerant cultivars. This study aims to determine the tolerance level of chickpea cultivars against cold and drought stresses. The cultivars in the scope of this study are the ones that are officially identified and grown in Turkey. Ranking alternatives according to multiple criteria is difficult and requires a systematic approach. Thus, a coherent multi criteria decision making (MCDM) methodology is proposed in order to ease the ranking process. The methodology includes integration of intuitionistic fuzzy analytical hierarchy process (IF-AHP) with group decision making (GDM) and goal programming (GP). This integration presents a robust ranking according to criteria that are appraised by talented experts. Applying the methodology to the data, results in the order of chickpea cultivars with regard to their cumulative tolerance to cold and drought stresses. Diyar 95 spearheads this list with its utmost performance. The main contribution of this study is the proposition of the powerful MCDM approach with systematic procedure for the ranking process of cultivars. The proposed methodology has a generic structure that can be applied to various stress problems for different plants.

The new product development process (NPD) is considered to be the key factor of competition among different markets. The identification of a suitable material is an important issue in the conception and improvement of new products. Material selection is seen as an important multi-criteria decision making (MCDM) problem in engineering because of the requirement of considering multiple criteria from different dimensions. Improper material selection may negatively affect the success of a firm. The purpose of this study is to specify the importance of selection attributes, which are considered to evaluate washing liquid that meets the needs of both customers and firms. Then, it objects to choose the most appropriate alternative among various formulations. A fuzzy MCDM methodology based on quality function deployment (QFD), 2-tuple fuzzy linguistic representation, and linguistic hierarchies is presented. QFD is used to incorporate customer requirements into the evaluation process. The 2-tuple fuzzy modeling and linguistic hierarchies are employed to combine multi-granular data given by experts. Finally, the fuzzy COPRAS (Complex Proportional Assessment) method is used to choose the most suitable alternative. The implementation of the developed method is presented by a case study conducted on a detergent manufacturer located in Turkey.