Determination of Adaptability of Advanced Bread Wheat (Triticum aestivum L.) Lines under Rainfed Conditions

Wheat (Triticum L.), a member of the Poaceae family, is an annual plant species that grows, develops and can be harvested in a short period. In general, it can be cultivated in almost every part of the world (Okhan, 2022). Due to its high adaptability, it has spread over vast areas worldwide. It can be easily cultivated in regions where there are no extreme temperatures or excessive rainfall. Moreover, breeding studies have made it possible to grow wheat in areas with various soil structures (Okhan, 2022; Kumar and Brar, 2021; Ghedabna et al., 2023).
       
In addition to the negative impact of decreasing agricultural lands and the rapidly increasing population, the rapidly changing climate conditions lead to restrictions on demanded food products. In this regard, high-yield varieties developed to meet these challenges are of great importance (Güngör  et al., 2022). Therefore, yield studies compatible with changing climate conditions continue. The impact of the environment on wheat genotypes is closely related to its yield and quality traits. Since many characteristics such as tillering (fertile tillers), spike yield values and 1000 kernel weight are directly associated with yield (Li et al., (2020); Wato (2021); Joy et al., (2021)), any adverse environmental conditions and stress factors will lead to significant losses.
 
The main objectives of this study are as follows
 
The bread wheat lines used in this study already have characteristics that allow them to adapt to rainfed conditions. In the first phase, the aim is to determine the adaptation abilities of these lines, collected from different climatic regions of the world, specifically to the ecological conditions of Ordu in the Central Black Sea Region. Later, they can be evaluated as research materials for different and similar regions, thus gradually improving their adaptation abilities. Globally, regions with excessive rainfall or humidity pose a risk for bread wheat cultivation. These risks result in yield losses and economic losses for farmers. This study also aims to reduce the risks associated with bread wheat cultivation in agricultural areas located in humid or rainy regions of the world. For this purpose, this study has been established to determine the adaptation characteristics of bread wheat lines and varieties under the ecological conditions of Ordu.

Plant material and experimental design
 
This study was conducted during the 2021-2022 and 2022-2023 wheat production seasons at the experimental field of the Field Crops Department, Faculty of Agriculture, Ordu University. The experimental site is referred to as the Ordu Organized Industrial Zone. This region is located in the Altýnordu district of Ordu province, on the coast of the Black Sea. The area’s elevation reaches up to 10 meters above sea level. The Black Sea climate prevails in this region, characterized by mild and rainy winters and cool, rainy summers. During the experimental period, the region’s long-term average temperature was 12.68^oC. The warmest month is July, with an average temperature of 23.2^oC, while the coldest month is January, with an average temperature of 7^oC. The average precipitation for the same period is 84.81 mm, with higher precipitation occurring in the winter months. The average humidity level of the region is 76.56% (Turkish State Meteorological Service, 2023). Winds generally blow from the northeast in this region. During the study period, the average monthly temperature for the 2021-2022 season was 11.05^oC, while for the 2022-2023 season, it was 13.79^oC.
 
Lines and varieties used in the experiment
 
In the first year of the study, 99 different bread wheat lines and varieties were tested. In the second year, 29 selected lines and varieties from the first year were included in the trial, along with the Dimenit bread wheat variety. The study material was obtained through the International Winter Wheat Improvement Program (IWWIP) in collaboration with the International Maize and Wheat Improvement Center (CIMMYT).
 
Experimental design, sowing, maintenance and harvesting procedures
 
Since the number of materials exceeded 50, the experiment was conducted according to the Augmented experimental design in the first year. Based on this design, 99 plots were prepared, with each plot containing three rows of 1-meter length. The row spacing was set at 20 cm  (plot size: 100 × 60 cm) and seeds were sown in straight lines. A 1-meter distance was maintained between the plots.
       
In the second year of the experiment, 29 selected lines from the first year and one local variety (Dimenit) were included, making a total of 30 lines and varieties. This year, the study was conducted using the Randomized Complete Block Design (RCBD) with three replications. Accordingly, 90 plots were prepared, with each plot containing five rows of 1-meter length and a 20 cm row spacing (plot size: 100 × 80 cm).
 
Data collection and measurement methods
 
quality analyses
 
Zeleny sedimentation value and delayed sedimentation were determined using a 3.2 g sample (adjusted to 14% moisture) and bromophenol blue solution, with shaking and resting steps performed in a Zeleny sedimentation device (Erkaya Zeleny 120, Turkey). For delayed sedimentation, an additional incubation at 37^oC for 2 hours was included. Wet gluten content was measured using a gluten washing device (Erkaya GI2030, Turkey) by forming dough with 2% NaCl solution and calculating the remaining gluten after washing. Gluten index was determined by centrifuging wet gluten at 6000 rpm (Erkaya GW2200, Turkey), where the percentage of gluten retained on the sieve indicated gluten strength. Grain protein content was analyzed following AACC Method 39-10, using the PERTEN IM 9500 device and Kjeldahl method with a nitrogen-to-protein conversion factor of 5.7.
 
Pigment, proline, lipid peroxidation and enzyme analyses
 
Total chlorophyll and carotenoid contents were determined spectrophotometrically according to Arnon (1949) by measuring absorbance at 645, 663 and 470 nm. Proline content was analyzed using the method of Bates (1973), with absorbance measured at 520 nm and results expressed as µmol/g fresh weight. Lipid peroxidation (MDA) was assessed following the method of Çakmak and Horst (1991) by measuring absorbance at 532 and 600 nm and expressed as nmol/g. Ascorbate peroxidase (APX) and catalase enzyme activities were determined using the methods of Nakano and Asada (1981) and Cho et al., (2000), respectively, based on absorbance readings at 290 nm and 240 nm and expressed as EU/mg protein.
 
Statistical analysis
 
The first-year data were analyzed using the R project program and evaluated through biplot analysis. Principal component analysis was used to interpret the results (Tables 2, 3 and Fig 1, 2, 3, 4, 5). The second-year data were analyzed using Minitab V14 and IBM SPSS V23 software. The normality of the data distribution was tested using the Shapiro-Wilk test. Normally distributed data by lines and blocks were compared using Generalized Linear Models (GLM), with multiple comparisons conducted via the Duncan and Games-Howell tests. For non-normally distributed data, the Kruskal-Wallis test was applied and multiple comparisons were made using Dunn’s test.



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Plant height showed statistically significant variation among lines (p<0.001), ranging from 66.51 cm (line 85) to 100.94 cm (line 5), which is consistent with the findings of Mut et al.  (2017). Flag leaf length ranged from 10.74 cm (line 73) to 24.04 cm (line 67), in line with the values reported by Sengün  (2006). Flag leaf width differed significantly (p<0.001), varying between 0.87 cm (line 41) and 2.3 cm (line 36) and aligns with the results of Cekiç (2008). Flag leaf area ranged from 9.53 cm² (line 41) to 33.6 cm² (line 33), which corresponds with the data presented by Mucuk (2022). Number of spikes per square meter varied significantly among lines (p<0.001), with values between 144.58 (line 16) and 565.83 (line 82), supporting the findings of Sakin et al., (2015). Spike length ranged from 4.79 cm (line 87) to 9.66 cm (line 33). Grain weight per spike showed significant variation, ranging from 0.67 g (line 71) to 1.63 g (line 33), similar to the values reported by Yiğit (2019). Number of grains per spike significantly differed among lines, ranging from 14.69 (line 87) to 40.45 (line 33), aligning with the findings of Güngör  et al. (2019). (Table 1, 2).




       
In this study, significant differences (p<0.001) were observed among lines and varieties in terms of catalase (CAT) activity, proline content, total antioxidant and phenolic compounds, as well as technological quality parameters.
 
Catalase activity (CAT)
 
The highest mean CAT activity was recorded in line 93 (35.39 EU/mg protein) and the lowest in line 36 (3.28 EU/mg protein).Oğuz (2019)  reported that CAT activity in Karahan-99 and Kınacı-97  wheat seedlings increased by 95.19% and 72.09% respectively under salt stress, while the addition of jasmonic acid (JA) reduced these increases to 69.02% and 43.25%. These findings suggest that JA suppresses CAT activity. In line with this, our study revealed variety-dependent variations in stress response, emphasizing the importance of genetic diversity in antioxidant enzyme regulation.
 
Proline (µg/mL)
 
The highest proline content was found in line 65 (91.11 µg/mL), while the lowest was in line 33 (73.76 µg/mL). Studies by Oncel, (2002) and Yakıt and Tuna (2006) reported increased proline accumulation under stress in wheat and maize, respectively. Proline functions as an osmoprotectant, stabilizing cellular structures by attracting water, particularly under salt stress. The proline increases observed in this study are consistent with its protective role in abiotic stress tolerance.
 
Total antioxidant content (%)
 
The highest antioxidant content was found in line 91 (95%) and the lowest in line 33 (80.57%). According to Yıldır (2018), antioxidants play a critical role in neutralizing free radicals and preventing cell damage, thereby enhancing stress resilience. The observed differences among genotypes may stem from genetic variation affecting antioxidant defense mechanisms.
 
Total flavonoid content
 
Flavonoids contribute to plant defense, growth and biological regulation. (Senlik and Alkan, 2021)  highlighted the importance of isoflavonoids in stress adaptation, especially in legumes and vegetables. The variation among lines in this study reflects the genetic potential for metabolite-based stress tolerance.
 
Total phenolic content (mg GAE/g)
 
The highest phenolic content was observed in line 33 (280.02 mg GAE/g) and the lowest in line 67 (131 mg GAE/g). Phenolic compounds, besides contributing to color and aroma, play a crucial role in enhancing plant resistance against environmental stressors (Senlik and Alkan 2021). Therefore, lines with high phenolic content may possess stronger stress tolerance.
 
Zeleny sedimentation value (ml)
 
Line 42 had the highest sedimentation value (62.07 ml), while line 73 had the lowest (24.07 ml). These values are consistent with those reported by Enes and Ünsal (2021), Başaran et al.  (2020)  and others, indicating alignment with previously established ranges.
 
Delayed sedimentation value (ml)
 
The highest delayed sedimentation value was recorded in line 14 (72.07 ml) and the lowest in line 16 (10 ml). These findings are in agreement with earlier studies by Balkan et al. (2008); Kurt (2012) and Kınabaş and Yağdı (2013), confirming the reliability of the results.
 
Grain protein content (%)
 
Line 11 exhibited the highest protein content (16.71%), while line 73 had the lowest (10.01%). These results are in line with values reported by Baykara  et al. (2022), which ranged between 13.96% and 11.02%.
 
Wet gluten content (%)
 
The highest wet gluten content was found in line 5 (40.07%) and the lowest in line 82 (17.67%). Our findings are supported by previous studies (Baykara et al., 2022; Enes and Ünsal (2021), which reported similar ranges, confirming the consistency of gluten-related quality parameters across genotypes (Table 1, 3).

Based on the results obtained from the study, a statistically significant difference was found among the distributions of all parameters except for grain moisture content according to the lines (p<0.001). Line selection also facilitates the acquisition of genotypes with resilience, meaning that wheat plants become more resistant to environmental factors. It is believed that conducting similar studies in different locations with the same conditions could be beneficial.

The results of the study indicate that the lines exhibit different characteristics and varying levels of resilience. Therefore, selecting lines based on the intended purpose could lead to more accurate outcomes. Similarly, including different soil structures in future studies could lead to significant variations, as a uniform soil structure might hinder the proper evaluation of certain parameters. This approach would help distinguish potential errors from the genetic characteristics of the lines. Line selection plays a crucial role in obtaining higher-yielding genotypes. Hence, the findings of this study could be valuable for future research. In addition to this study, it is recommended to examine the genetic characteristics of the lines to better determine the adaptation abilities of new varieties.

This study is derived from the doctoral thesis of Gözde Hafize Yildirim.
 
Disclaimers
 
The views and conclusions expressed in this article are solely those of the authors and do not necessarily represent the views of their affiliated institutions. The authors are responsible for the accuracy and completeness of the information provided, but do not accept any liability for any direct or indirect losses resulting from the use of this content.
 

The authors declare that there are no conflicts of interest regarding the publication of this article. No funding or sponsorship influenced the design of the study, data collection, analysis, decision to publish, or preparation of the manuscript.