جستجوی مقالات مرتبط با کلیدواژه "stability" در نشریات گروه "کشاورزی"

Genotype × environment interaction is one of the complex issues in plant breeding programs to introduce high yielding and stable genotypes, which is evaluated using multi-regional experiments before the release of new cultivars. The presence of genotype × environment interaction causes the yield of cultivars to be affected by the environment and leads to differences in the yield of cultivars in different environments. AMMI and GGE-Biplot models are very important among the multivariate methods and have high resolution in identifying high yielding and stable genotypes. The objective of this study was to evaluate the stability of promising bread wheat genotypes and to identify high yielding and stable genotypes in the cold climate of the Iran.

Fourtheen wheat genotypes with winter and intermediate (facultative) growth type along with Mihan, Heydari, Zarrineh and Zare varieties as controls (a total of 18 genotypes) were investigated in randomized complete block design with three replications in research stations of Karaj, Hamadan, Mashhad, Jalgarokh, Miandoab, Ardabil, Arak, Eqlid, Tabriz and Qazvin. To analyze the data, first analysis of variance was seprately done in each year and location, and then combined analysis of variance was performed for grain yield after confirming the homogeneity of the variances of experimental errors. AMMI and GGE-Biplot methods were used to investigate the stability of the studied genotypes. AMMI stability parameters and simultaneous selection indices were also calculated based on these parameters.

The results of combined analysis of variance showed that the main effect of environment and genotype and the interaction of genotype × environment accounted for 47.2, 9.8 and 28.3 percent of the total sum of squares, respectively. Genotypes G7, G8, G12, G2 and G1 had the highest grain yield and genotypes G15, G18, G10, G13, G14 and G16 had the lowest grain yield among the studied genotypes respectively. The results of AMMI analysis showed the existence of significant differences between environments, genotypes and their interactions. The first 12 significant principal components of AMMI analysis explained 98% of the genotype × environment interaction variance, and the first and second principal components explained a total of 46.27% of this variance. Based on the AMMI1 biplot, genotypes G8, G3, G1 and G4 and environments E9 and E5 with the higher grain yield than average grain yield and the lowest value of the first principal component were recognized as the most stable genotypes and environments. AMMI2 biplot did not identify a specific genotype as the genotype with general compatibility, however, G3 and G4 genotypes showed somewhat better general compatibility than the others. The simultaneous selection indices based on AMMI parameters identified G8, G12, G1, G4, and G3 genotypes with the lowest total rank as the stable and high yielding genotypes, respectively. The results of GGE-Biplot method based on biplot of the average yield and stability, introduced G8, G4, G3 genotypes followed by G1 as the most stable genotypes, due to grain yield higher than the average of the studied genotypes. Which-won-where biplot pattern divided the studied genotypes and environments into five and three groups, respectively, so that G12, G11, G3 and G4 genotypes in Karaj and Miandoab and G5, G7 and G8 genotypes in Jalgerokh and Mashhad showed better adaptation in both years. According to the biplot of the ranking of genotypes, there was no ideal genotype, but G8, G3, G5, G7 and G4 genotypes with the smallest distance from the hypothetical ideal genotype were identified as the best genotypes.

The results of this study showed that there is a little difference between AMMI and GGE-Biplot analyzes and both methods presented the same genotypes as superior genotypes. However, it is more logical to select genotypes using simultaneous selection indices based on AMMI analysis parameters, because all significant components are included in the calculation of these parameters. Therefore, based on simultaneous selection indices, genotypes G8, G12, G1, G4 and G3 with the lowest total rank are introduced as stable and high yielding genotypes.

The phenomenon of desertification has always been considered as one of the most important challenges facing Iran, which has been aggravated by human and climatic factors in recent years. Therefore, it is necessary to implement anti-desertification plans and projects set through the Development planning to curb desertification and restore and improve degraded lands. In this regard, the severity of the phenomenon can be decreased by applying appropriate management solutions and methods and preventing its expansion and progress. Implementing anti-desertification management and rehabilitation projects according to the ecological conditions of each region improves the condition of the vegetation, strengthens the soil stability, and protects the soil from the risks of water and wind erosion. Therefore, analyzing different aspects of the anti-desertification projects which are planned and carried out by the government is required for improving management in the natural resources sector. One such measure can be the restoration of desert pastures with regard to unfavorable climatic conditions. Thus, this study set out to investigate the influence of anti-desertification management and restoration projects in improving soil stability indicators and vegetation characteristics.

This study was conducted in four sites located in the Yazd-Ardakan plain, including the seedling site, the water weed management site, the mulched site, and the enclosure site. The main species investigated in each of these sites was Haloxylon aphyllum. To this end, four transects were placed in the site at regular intervals. It should be noted that the transects were placed parallel and perpendicular to each other in flat and sloping areas, respectively. The number of plots on each transect was 15 and the area of the plots was 210 cm. Moreover, the index Plant characteristics such as canopy percentage, density, reproduction, and freshness of Haloxylon aphyllum species were measured. Finally, after collecting the required data, statistical analysis was performed using the SPSS software.

  According to the results of statistical analysis performed via independent t-test, a statistically significant difference was found in the percentage of vegetation and density at the error level of 1% in all investigated sites. Duncan's multiple range test revealed significant differences in mean values among treatments. The treatment associated with herbaz exhibited the highest mean values for vegetation cover (72.5%), plant density (75.4), regeneration (542.0), and vigor (33.61). Conversely, the treatment subjected to enclosure showed the lowest mean values for vegetation cover (68.1%), plant density (2.0), regeneration (111.0), and vigor (24.12).

Compared to the control area, the percentage of vegetation and density of the effective area was significant in the seedling site (where the seedling project is based on seedling irrigation), which is due to the lack of suitable conditions and rainfall in the seed establishment. The wastewater management site demonstrated increased vegetation cover and density due to enhanced water infiltration and readily available moisture, which facilitated plant establishment and growth. Similarly, the mulched site exhibited higher vegetation cover and density compared to the control, attributable to the creation of a subsurface moisture layer beneath the mulch, providing a favorable environment for seed germination and plant development In the enclosure site which is less affected by human changes, the amount of soil erosion and ecosystem destruction is lower than other sites in all dimensions, leading to the higher percentage of vegetation and plant density. The establishment and expansion of vegetation cover through various methods have been implemented in recent decades as a means to combat desertification and mitigate the damages caused by dust storms in arid regions. However, water scarcity poses a significant constraint. Consequently, it is recommended that, in the context of desertification management and rehabilitation projects in the Yazd-Ardakan plain, the most effective approaches be prioritized as follows: runoff water management, mulching, afforestation, and enclosure.

Doogh is one of the native drinks of Iran and some other nations including Eastern Europe, the Middle East, Asia (Afghanistan, Azerbaijan, Armenia, Iraq, Syria, Georgia, and Turkey), and the Balkan Islands, whose consumption is It has a lot of history. According to the definition of Iran's national standard, simple doogh is a lactic drink obtained from milk fermentation, the dry matter of which is adjusted by diluting yogurt or milk in the doogh-making process. And due to the low pH, doogh is susceptible to contamination by molds and yeasts, and some bacteria, which causes the quality of doogh to decrease and its shelf life to decrease. Among the nutritional properties of doogh, we can mention the increase of vitamins and nutritious metabolites, the improvement of calcium absorption, and the digestibility compared to raw milk. Rheological behavior in macro and micro scales is one of the properties influencing the quality of food. Food flow behavior for a number of purposes such as quality control, as well as the final properties of the product such as stability, texture, and appearance, directly depends on the food microstructure. One of the major problems is the biphasic of doogh during storage, which is due to its low viscosity, low pH, and their effect on the precipitation of proteins. Types of stabilizers are used to increase the stability of the doogh product, which has satisfactory results. Hydrocolloids are widely used to create tissue stability in acid fermentation products. One of the significant issues in doogh is its consistency, which plays a very important role in its marketability. On the other hand, today, the desire of consumers to use natural antimicrobial substances such as chia seeds, which are considered a rich source of protein and dietary fiber, instead of chemical preservatives, has increased. Hydrocolloids are widely used to create texture stability in acid fermentation products. Chia seed with the scientific name Salvia hispanica L. is an annual summer plant belonging to the mint family. Chia seeds are considered as a rich source of protein (18-25%) and dietary fiber (20-37%). Also, chia seeds contain (21 to 33%) oil, of which (60 to 63%) is related to the essential fatty acid alpha-linolenic acid. These seeds also contain significant concentrations of natural antioxidants such as chlorogenic acid, caffeic acid, myristin, quercetin and kaempferol. Chia seeds contain large amounts of phytosterols that help prevent cardiovascular diseases and have anti-cancer, antioxidant, bactericidal and antifungal effects, which are excellent nutritional properties. The technological advantages of chia have led to its innovative use in food products. The concentration of mucilage, the amount of viscosity increases, and the highest and lowest levels of stability were observed in the samples containing 0.05% of mucilage (85%) and the control sample (52%), respectively.

An optimization method was used to extract the mucilage of chia seeds. After dissolving the mucilage in deionized water, salt was added so that the amount of salt in the final product was 7%. In the next step, 40% of the doogh formulation was added to the stabilizer and salt mixture to prepare the doogh samples. Then, the effect of chia seed mucilage on the stability of doogh during 28 days of storage at 5°C refrigerator temperature was investigated. Chia seed mucilage was considered in a completely randomized design with treatments including concentrations of 0.01, 0.1, 0.3, 0.5% added to doogh and doogh without gum as a control sample. Then viscosity, zeta potential value, stability, sensory and chemical properties of doogh were measured. In this research, analysis and analysis of the results were done in the form of a completely random design and all the tests were done in 3 repetitions. To compare the mean of the treatments, Duncan's test was used using one-way analysis of variance (ANOVA) and SPSS version 16 software at a significance level of 0.05, and graphs were drawn using Excel software version 2016.

Acidity and pH are one of the most important chemical factors in the stability and taste of doogh. The statistical analysis of the chemical analysis of doogh mixed with chia seed mucilage in comparison with the control sample after the preparation process shows that the Regarding the findings of this research, the acidity and pH of chia seed mucilage were investigated in the values of (0, 0.01, 0.1, 0.3 and 0.5 percent), the results show that the acidity of doogh samples is reduced with chia seed mucilage. But pH changes were not significant. The sample containing 0.5% chia mucilage had a higher apparent viscosity at low cutting rates than the control sample (without mucilage) and other samples. Also, this figure shows that the apparent viscosity of the doogh samples decreases with the increase of the shear speed, which in fact indicates non-Newtonian behavior (shear thinning). And in addition, it can be found that the degree of stability increased with the increase in mucilage concentration. Also, The evaluation of the obtained results does not show a significant difference between the sensory attributes of smell, taste, texture and mouthfeel (tenderness, uniformity or homogeneity, oral viscosity and mouth coating) and overall acceptance. The present study showed that in evaluating the mouth feel of doogh samples, no significant difference was observed between the samples and the control, because in addition to the oral viscosity, the uniformity and homogeneity of the samples were also considered. Therefore, it can be concluded that adding more than the appropriate amount of gum causes the samples to become undesired viscous and makes it unpleasant from the point of view of the consumer, because the presence of high amounts of hydrocolloid from the sample's psyche, which is one of the characteristics of desirability It reduces. In similar researches, the use of high amounts of hydrocolloids have been introduced as reducing the desirability and reported that depending on the type of hydrocolloid used, its appropriate amount to increase the consistency is different. The results also show that by increasing the concentration of chia seed gum compared to the control sample, the desirability of the consistency of the samples increases, but this effect decreases at a concentration of 0.5%. The results of the present study show that adding hydrocolloids to doogh causes the zeta potential of the doogh sample to become negative. Due to its anionic nature, chia seed gum has a negative zeta potential. Probably, chia seed mucilage as an anionic hydrocolloid has been absorbed on the surface of caseins and as a result, spatial and electrostatic repulsion has prevented the particles from approaching each other. Colloids containing particles with a low zeta potential (positive or negative), in the absence of other inhibiting factors such as high viscosity and spatial hindrance, will have a great ability to clot and aggregate. The larger numerical value of the zeta potential in the formulation containing gum means the presence of more repulsive force between the droplets and their less tendency to stick together, which in this case repels each other and makes the system stable. Therefore, by increasing the concentration of gum in the samples, the intensity of the charged ions of the samples increased. As a result, the spatial and electrostatic repulsion forces of these samples have shown an important role in stabilization. It could be obtained by increasing the concentration of mucilage, the amount of stability increased, so that there was a significant difference (P<0.05) between the samples and the control sample (without chia seed mucilage). The samples containing 0.3% and 0.5% concentration of chia seed mucilage resulted in 100% stability and the least stability (30%) related to the control treatment at the end of the 28th day. Our findings results are probably due to the polyelectrolyte nature of chia seed gum in 0.5% weight-volume solution; Because the chia seed gum polymer consists of carbohydrates with carboxyl and hydroxyl functional groups. It should also be added that chia seed mucilage did not change much in dry matter, fat and doogh protein content. And as the apparent viscosity of doogh samples containing chia seed mucilage shows, the sample containing 0.5% chia mucilage had a higher apparent viscosity than other samples, and the apparent viscosity of doogh samples decreased with increasing shear rate.

The results showed that the addition of chia seed mucilage up to a concentration of 0.1% on the 28th day of storage time resulted in a remarkable increase in the stability of doogh samples (62%), and concentrations of 0.3% and 0.5% resulted in complete stability of the samples. became The highest apparent viscosity in the samples containing chia seed mucilage is related to the concentration of 0.5 and then 0.3%. Since the highest consistency score in the sensory evaluation of doogh samples and its complete stability compared to the control sample was observed in the sample containing 0.3% chia seed mucilage, this concentration is suggested as the optimal concentration.

To study the adaptability and yield stability of 19 selected potato clones along with four cultivars, Agria, Marfona, Savalan and Khavaran a field experiment was carried out in randomized complete block design with three replications in five locations; Karaj, Ardabil, Hamadan, Esfahan and Mashhad, in 2015 and 2016. GGE Biplot based on environment scaling showed that Isfahan, Ardabil and Hamadan, respectively, were closer to the ideal location and KSG23, KSG82, KSG31, KSG64 and KSG300 clones with mean tuber yield of 30.71, 29.76, 29.38, 27 and 26.68 kg plot-1 (nine square meters), respectively, were more suitable for being grown in ideal areas. The relative superiority coefficient of KSG23, KSG302, KSG81 and KSG107 clones were 2.87, 6.98, 7.81 and 12.49, respectively, and they had relatively good tuber yield stability. The relative superiority coefficient of KSG31, KSG82 and KSG64 clones were 18.07, 15.76 and 13.67, respectively, and almost similar to the Agria control (17.22) and they were superior to the Agria (control) for tuber yield. AMMI analysis revealed that the genotypes reacted differently in different environments and the sum of squares of the genotype × environment interaction was 4.8 times larger than that of the genotypes. KSG81, KSG64, KSG300 and KSG107 clones, and cv. Agria (control) had reasonable tuber yield stability. Based on the adaptability and tuber yield stability, KSG302, KSG82 and KSG31 clones were identified suitable for spring planting in different regions of Iran, KSG23 and KSG57 for Khorasan, KSG64 and KSG48 for Hamadan and Ardabil, respectively, KSG81 for Isfahan and Ardabil.

The Production of high-yielding and stable cultivars is the most important objective of crop breeding programs, including wheat. Wheat is one of the key crops cultivated in Iran. The final yield of each plant is determined by the genotype potential, the environmental effect, and the interaction effect of genotype × environment. Studies on genotype × environment interactions can help determine whether a genotype is stable in performance across a wide range of environments. Various methods (univariate and multivariate methods) have been introduced to evaluate the interaction effect, each of which examines the nature of the interaction effect from a specific point of view. The results of different methods may not be the same, but the best result is obtained when a genotype with different evaluation methods shows similar results in terms of stability. Univariate methods do not provide a complete view of the complex and multidimensional nature of genotype × environment interaction, therefore, the use of multivariate methods is suggested to solve this problem. Among the multivariate methods, genotype × genotype-environment (GGE) biplot methods are more important. Therefore, this study aimed to identify promising and stable top-performing lines of bread wheat for warm and dry climates using the GGE biplot method.

The adaptability and stability of 37 promising bread wheat lines were evaluated in 10 environments, along with three checks (Chamran2, Sarang, and Mehregan). The experiment was conducted using a randomized complete block design with three replications in two cropping seasons (2020-2021 and 2021-2022) at five research stations (Darab, Ahvaz, Dezful, Khorramabad, and Zabol). In the field, each plot was planted with a density of 450 seeds/m2. Each line was planted in plots with six four-meter lines with 20 cm line spacing. At the end of the growing season, six rows of five-meter spikes from each plot were harvested and threshed by a Wintersteiger combine. The weight of the obtained grains was measured by a digital scale and reported in hectares.Grain yield was determined using combined analyses of variance. The GGE biplot statistical method (genotype effect + genotype × environment interaction) was used to study the stability of genotypes in the studied environments. SPSSv22 software was used to analyze the experimental data using the analysis of the combined experiment. The data were analyzed with GGE-Biplot software using the GGE biplot graphic method.

The Smirnov-Kolmogorov test was conducted to examine residual errors in each environment. The results for each environment separately showed that the residual data were normal in all environments. Bartlett's test results for the environments indicated the homogeneity of error variances, allowing for a combined analysis of variance, which showed the significant main effects of the environment, genotype, and genotype × environment interaction for grain yield. The significance of the interaction effects of genotypes in this study showed that the genotypes responded differently in different environments; in other words, the difference between genotypes is not the same from one environment to another, and the stability of grain yield can be evaluated in these conditions. The environment, genotype, and genotype × environment interaction effects accounted for 70.12%, 1.24% and 9.57% of the total variation, respectively. The results showed that the three PCAs explained 54% of the total agronomical variability residing in the tested wheat genotypes. The first two PCAs accounted for 29% and 25% of the total variation, respectively. The GGE biplot analysis revealed four mega-environments and five superior genotypes. The polygonal diagram obtained from the analysis showed that the genotypes GT biplot arising G31،G21 ،G29, G27, and G32, which were located at the vertices of the polygon, were the superior genotypes. The average environmental coordinate of the GGE biplot analysis showed that genotypes G29, G28, and G16 had high grain yield and stability. The biplot of the correlation among environments revealed that the environmental vectors of Ahwaz and Zabol were near 90◦, thus these locations were different environments.  Based on the results, the environment of Zabol can be introduced as a favorable environment for selecting the best bread wheat genotypes.

Given the climate change in Iran, particularly in the hot and dry regions of the south, there is always a pressing need for using sustainable varieties with high performance. This study has clearly and easily aided in the identification of stable and superior genotypes graphically. Wheat breeders worldwide consider breeding varieties specifically adapted to different geographical and climatic agricultural regions. The general adaptability of varieties to several regions was identified in this study, indicating that the Zabol environment could be introduced as a suitable environment for selecting superior genotypes of bread wheat. Finally, it is recommended to select genotypes G29, G28, and G16 for further testing and promotion after seed multiplication and selection under farm conditions, eventually introducing them as new wheat varieties. The results obtained in this study demonstrate the efficiency of the GGE biplot technique for selecting high-yielding and stable varieties.

Sugar beet cultivars, candidate to enter the Iranian trade market, must pass the value cultivation and use (VCU) test successfully. For this purpose, 29 candidate cultivars from different companies were subjected to product comparison in the form of two experiments with the same control cultivars in 2018 and 2019. The experiments were conducted in two separate experiments of 16 and 17 cultivars in four replications in the provinces of West Azarbaijan, Khorasan Razavi, Hamedan and Fars under natural infection conditions. According to the results of the tests, among the new genotypes, 7 cultivars including BTS 7715, BTS 2015 N, BTS 1930 RHC, Annamira, Annemartha, Joker and BTS 3645 RHC were introduced as superior cultivars. These cultivars had higher sugar yield and also, they had better yield stability and disease resistance compared to the other candidate cultivars.

Aram is a new oilseed rape cultivar, extracted from the R308 (earlness line) and RGS003 (high-yield cultivar) cross population through pedigree method in three years. To reach high-yielding and compatible lines and cultivars, preliminary and advanced investigations were carried out in Gorgan and Sari (2014-2015) and Zabol, Gorgan, Sari and Borazjan (2016-2017). The line SRL-93-12 (Aram cultivar) with a yield of 2955 kgha-1 and 2774 kgha-1 was the first in the above-mentioned tests, respectively, and the SRL-93-12 line was also recognized as the most stable genotype based on the lowest Lins and Binns superiority index and highest seed yield. Extension research project results on farmers' farms in Behbahan, Moghan, and Gorgan regions showed that the new line with 594 kgha-1 higher yield than the check cultivar was in the first rank. According to the results as well as desirable agronomic traits such as good tolerance to dormancy and uniformity in maturity, this line was released with the name Aram.

The production of peanuts (Arachis hypogaea L.) as one of the vital industrial plants is affected by the environment, genotype, and their interaction. Therefore, the environment × genotype interaction on peanut yield should be evaluated before the introduction of cultivars. Evaluation of the genotype × environment interaction provides valuable information regarding the performance of plant cultivars in different environments. It plays a crucial role in evaluating the stability of the performance of breeding materials. This experiment evaluated the stability and yield of superior peanut genotypes in three regions of Guilan province, Iran, in the 2018 and 2019 crop years.

In this study, the top 10 peanut genotypes (130, 140, 113, 115, 128, 176, 178, 192, 201, and 208 from ICRISAT) along with the NC2 variety as a control were assessed in a complete randomized block design trial with three replications across three regions Rasht, Masal, and Talash. Each plot comprised six lines, each with 5 m long, 50 cm row spacing, and 20 cm plant spacing. Upon reaching physiological ripeness, a 5-m2 area was harvested from the middle four rows of each plot after removing 0.5 m from both ends to eliminate marginal effects. The plant height (cm), average number of sub-branches per plant, number of pods per plant, and number of seeds per pod were randomly recorded and counted from 10 plants. After drying, biomass, pod, and seed yields were calculated in kg/ha. Following seed separation from the shell, five random samples of 100 seeds were taken from each plot to measure the 100 seed weight (HSW). Additionally, the length and width of peanut pods and seeds were recorded (in mm) using a digital caliper. To determine seed oil percentage, 150 g of peanut seeds were randomly selected from each plot, and their oil percentage was measured using the Soxhlet method after grinding the samples. Composite variance analysis was conducted after ensuring the uniformity of experimental error, and the mean traits were compared using the least significant difference (LSD) method. The stability of peanut genotypes was assessed using the GGE bi-plot analysis.

The variance analysis revealed that the interaction of location × genotype significantly affected the peanut plant's height, sub-branches, and pod diameter at a one percent probability level. Additionally, the year × location × genotype interaction significantly affected other traits such as pods per plant, seeds per pod, HSW, pod yield, seed yield, seed oil percentage, oil yield, shell yield, pod length, and peanut seed length and width at the 1% probability level. Notably, genotype 208 in the Rasht region exhibited the tallest average plant height (103.5 cm), which was not significantly different from line 201. Furthermore, the highest number of peanut pods (31.72 pieces) was observed for genotype 128 in the Rasht region in the first crop year, showing no significant difference with line 128 in the first and second crop years. Significant differences were also noted in the number of seeds per pod across different genotypes and regions. For instance, the second crop year in the Rasht region and genotype 113 yielded the highest peanut HSW (71.45 g), which was not significantly different from some lines in the two crop years in the Masal and Rasht regions. Furthermore, the pod yield of genotype 192 in the first crop year was superior in Rasht (5583 kg/ha), Masal (5233 kg/ha), and Talash (4166 kg/ha) regions compared to the other genotypes. Genotype 192 exhibited the highest seed yield (3777 kg/ha) in the first crop year in Rasht, representing a 133% increase compared to the control (NC2). These results underscore the significant influence of climatic conditions on peanut seed yield and the genetic potential variations among different genotypes in diverse regions. Additionally, genotype 192 in the first cropping year and Rasht region attained the highest peanut oil yield (1841 kg/ha), aligning with findings from other researchers regarding varying oil yields among different peanut lines.

Based on the findings of this study, all traits measured in peanuts were impacted by the interaction of genotype and environment. Line 192 displayed significantly superior quantitative and qualitative performance of peanut seeds to the NC2 variety, known as the Goli native variety, and the other studied lines. The increase in the number of pods per plant, seeds per pod, and the peanut HSW were important agronomic indicators in improving the performance of line 192 in the Guilan region. The results indicated that the interaction effect of genotype and environment led to changes in the yield components, resulting in changes in the yield of peanut seeds and pods per unit area, with the oil yield increasing in parallel with the grain yield. Using the GGE bi-plot method to evaluate performance stability, peanut line 192 was identified as a high-yielding line with high performance and stability in all environments. Therefore, groundnut genotype 192 is recommended for achieving the highest seed yield in the region's climatic conditions.

Xylanase is one of the critical enzymes in the food, poultry feed as well as paper industries. This research aims to provide formulation and operating conditions suitable for spray drying of xylanase enzyme while maintaining enzyme activity. For this purpose, the xylanase was produced by Bacillus subtilis D3d strain using Brewers' spent grain (BSG) and yeast extract as carbon and nitrogen source in a 14-liter fermenter. After separating biomass and solid substrate by centrifuge, the supernatant was used as an enzyme source with a xylanase activity of 350 U/ml. Among the additives, manganese ions at a concentration of 10 mM had the most significant effect on increasing enzyme activity. Among the examined carriers, mannitol and magnesium sulfate showed the slightest decrease in enzyme activity. Magnesium sulfate and malt extract were selected as carrier and binder in concentrations of 20 and 5, (w/v) respectively. In the spray drying operation with an inlet temperature of 120°C, and an inlet feed flow rate of 4 ml/min, the enzyme activity was maintained and the powder with the 4.5% of moisture content was obtained.

In order to consider the effect of different irrigation treatments on triticale and considering the probability of screening some suitable genotypes tolerant to drought stress, a two-year study (2018 and 2019) with four irrigation regimes (normal irrigation and withholding irrigation in thrre different growing stages containing flowering, milky seed, and seed filling) and nine elite genotypes (Sanabad, Paj, Javanilo, ET-92-15, ET-92-18, ET-83-20, ET-85-17, and ET-83-18) was performed. Grain yield of the triticale genotypes were measured in all treatments and used to estimate the tolerance and stability of the genotypes based on numerous number of related indices. Since, according to results of this study, no single index could be suitable for distinguishing tolerant genotypes, these indices should be applied together and extract information from all of such tolerance indices by using multivariate methods. In this study in addition to biplot based on PCA, a new method as heatmap was also applied. Furthermore, multivariate stability indices containing AMMI and GGE models applied for finding stable genotypes. According to the results of tolerance indices, genotypes ET-85-04, Sanabad, and Paj were the most tolerant genotypes in response to drought stress condition in comparison to other genotypes. Meanwhile, The results of stability analyses indicated that genotypes ET-85-04 and ET-83-20 were the genotypes with lowest variability in different environments. Therefore, ET-85-04 based on the results from both tolerance and stability indices is an suitable genotype to be used as a candidate for releasing new cultivars of triticale genotypes or applied in future breeding plans. In this study the results indicated that using stability and tolerance measuring methods together as a mixed method can be the most effective way to distinguish proper genotypes.

The south warm climate of Iran is one of the regions with the ability to grow spring oilseed rape cultivars. Cultivation of oilseed rape in this climate faces the problem of environmental stress such as terminal drought and heat stress. Therefore, in addition to yield, earliness is one of the important priorities to introducing spring oilseed rape cultivars in these areas. Asa (promising line SRL-93-4) is an early-maturing and relatively high-yielding cultivar that resulted from hybridization between R308 early-maturing spring line and Modena as a high-yielding winter cultivar. The segregated generations were conducted by pedigree method. Preliminary and adaptation trails showed that SRL-93-4 line was superior compared to check cultivars in the regions under study. In the adaptation trail, the SRL-93-4 line (with 2581 kgha-1 seed yield) showed a significant superiority over the control cultivar RGS003 (with 2155 kgha-1 seed yield). Also, it was found that the SRL-93-4 line was matured 11 days earlier than the check variety RGS003 on the average. The results of stability methods revealed that SRL-93-4 line was the high stable genotype. A field trial for Blackleg disease showed that the SRL-93-4 line had a relative tolerance to the Blackleg. Analysis of the fatty acids profile showed that SRL-93-4 seed oil had a level of erucic acid close to zero, and in terms of the composition of fatty acids, it was within the standard range, but with more oleic acid and less linolenic acid compared to the RGS003 variety. Also, the amount of glucosinolate of the meal was less than standard level. The results of the on-farm trails in Zahak and Zabol regions of the Sistan and Baluchestan province showed that SRL-93-4 line (with 2200 kgha-1 seed yield) had a non-significant difference seed yield with Dalgan check cultivar (with 2361 kgha-1 seed yield); But it was eight days earlier than the check variety. Therefore, due to the desirable characteristics such as early maturity, relative tolerance to Blackleg disease and good performance, the new promising line SRL-93-4 which released as Asa variety is recommended for cultivation in the south warm regions of the country.

The new oilseed rape cultivar Nilofar (R15), is the result of screening and purifying single plants in segregating generations derived from the cross "Symbol×Orient". During five years of consecutive cultivation, screening of single plants was continued to access pure lines using pedigree method and pure lines were selected in F4 generation. During cropping season 2008-2009, 84 pure lines were evaluated in preliminary yield trial. Results showed that Nilofar variety with a mean yield of 3352 kgha-1 had higher grain yield by 45% compared to the Okapi control variety with a mean grain yield of 1833 kgha-1. In the Value for Cultivation and Use (VCU) trial in six research stations of cold and mid cold regions of Iran including Karaj, Isfahan, Hamedan, Islam abad-e- gharb, Khoy and Arak during two cropping seasons 2009-2011, Nilofar variety with an average grain yield of 3783 kgha-1, ranked first and had 16.1% grain yield more than the Okapi. Under delayed sowing date and stopping irrigation from silique development stage in Karaj during two cropping seasons 2012-2014, Nilofar with 1986 kgha-1 and 0.62 kgm-3 in term of grain yield and water use efficiency, respectively, was superior to Okapi with 1626 kgha-1 grain yield and 0.62 kgm-3 water use efficiency. The glucosinolate content of Nilofar variety was less than 10 μmolg-1 of dry matter and the erucic acid content of the oil was less than 2%. The results of the extension research project in Kermanshah province showed that the mean grain yield of the Nilofer variety at two sites of Sarab Nilofer and Mahidasht was 4004 kgha-1, which was 14.8% higher than the Okapi control cultivar. Due to its high grain yield potential and appropriate agronomic characteristics, line R15 was released under the name of Nilofar and is recommended for cultivation in the cold and mild cold regions of Iran.

Saffar (Zabol 10b line) variety was obtained by pedigree method from Goliath×19H cross. Based on preliminary evaluation, this variety showed significant earlier maturity (13 day), in 2010-2011, compared to the other lines of canola. Based on adaptability expieriments in Zabol, Safiabad, Behbahan, Boushehr, Gorgan, Gonbad, Sari and Moghan regions in 2011-2012, its grain yield had not significant difference from control variety RGS, but had a high early maturity. The new variety had a lower rank variance which indicates the Less performance fluctuations and stability in different years and regions compared to control variety RGS. Saffar cultivar with 165 days growth period was 12 days earlier in maturity than control variety RGS in warm south and north regions. The oil content of new variety was 43.15%, which has not significant difference with control variety RGS but in terms of having higher amounts of oleic acid and lower amounts of linolenic acid, it has a better quality. The field response of new variety to stem sclerotinia disease showed good relative tolerance in the north climate, which has significant difference with control variety RGS. Based on outstanding features such as yield stability, early maturity, possibility of escaping from drought and heat in the last season, saving at least one irrigation stage and uniformity in maturity, this line was released with the name of Saffar in 2018 and recommended for late cultivation in warm areas with short growing seasons in warm south and north climate zones of the country such as the south of Kerman, Sistan and Baluchestan, Hormozgan, Khuzestan and Gorgan.

In order to study the adaptability and determine the cultivation value of new corn hybrids, 16 forage maize genotypes of local and exotic origin were evaluated along with three common genotypes (KSC704, Bolson and Massil) in four different regions (Karaj, Maghan, Jovein and Dezful) using randomized complete block design with four replications in two years (2020 and 2021). Important traits such as days to flowering, plant height, ear height, ear-to-plant ratio and wet silage yield were recorded, based on the manual of value for cultivation and use test. To evaluate the yield stability, Francis and Kannenberg's environmental coefficient of variation was used. The results of two-years mean comparison of yield showed that Egean, Sy-Lavaredo, ZP873, Zarin2 and Zarin3 hybrids had the highest forage yield with 65.4, 64.8, 64.7, 63.8 and 62.3 tons per hectare, respectively, While the average yield of check varieties was 60 tons per hectare. Sy-Andromeda, Sy-Lavaredo, Egean, Jeta poly, Zarin 1, Zarin 2, Zarin 3 and ZP873 hybrids can be introduced with general adaptability, due to their higher yield and yield stability in comparison with the check varieties. Sy-Bilbao and BT-6470 hybrids are recommended in Karaj and Jovein regions and Ajeeb and ZP600 hybrids are also recommended in Jovein region with specific adaptability. ZP707, RGT-Joxxlin, RGT-Coruxxo and Exxupery hybrids do not deserve to release as a new variety because of low forage yield and yield adaptability in comparison with the check varieties.

Genotype-environment interaction is one of the most important limiting factors in breeding programs. A comprehensive study of genotype-environment interaction requires powerful statistical methods. Different methods for evaluating the interaction effect of genotype-environment have been proposed by different researchers. Therefore, in the present study, the role of this phenomenon on the sugar yield of sugar beet hybrids and the identification of stable hybrids were studied based on the AMMI, GGE bi-plot, and MTSI stability index methods. For this study, a total of 20 sugar beet genotypes were utilized, comprising 15 recently developed hybrids and five control cultivars (Sina, Dena, Novodora, Modex and Loriquet). Phenotypic assessments of experimental genotypes were conducted in 2021 crop year at four agricultural research stations located in Karaj, Mashhad, Shiraz and Miandoab. These selected sites differed in terms of altitude, latitude and longitude, atmospheric temperature and precipitation, and physical and chemical characteristics of soil. The experiments at each research station were carried out using a randomized complete block design with four replications. Each genotype was planted in a separate plot, consisting of three cultivation rows with a length of eight m and a distance of 50 cm interrow. Throughout the growing season, weed control, irrigation, fertilizer application, and other field management activities were performed based on the recommendations of experts. Additionally, regular monitoring and prevention of pests and diseases specific to sugar beet were conducted at each research station. Stability analysis methods of AMMI, GGE bi-plot, and MTSI stability index were used to analyze the genotype-environment interaction. The results of a combined analysis of variance confirmed the significant effects of environment and genotype on all traits at a one percent probability level. The interaction between them was significant at one and five percent probability levels for all traits except the sugar content and white sugar content. Analysis of the multiplicative effect of the AMMI model showed that the first two components are significant at the one and five percent probability levels, respectively, and together explain 92.20 percent of the interaction variations. The bi-plot of mean yield and the first principal component of the interaction confirmed the superiority of genotype no. 20 due to its high sugar yield and stability. The results obtained from the GGE bi-plot method showed that the first and second components together explain 84.16% of the variations in total sugar yield. According to the GGE bi-plot, Karaj, Shiraz, and Miandoab had a relatively similar reaction in terms of genotype yield rank and in these environments, genotype no. 20 was stable. The reaction of the Mashhad environment was different from the other three environments and in that genotype no. 9 had suitable stability. Based on the results of the MTSI index, four genotypes of 18, 2, 20, and 17 were identified as stable genotypes. In general, the selected genotypes based on the MTSI caused a favorable selection differential in all traits. Among the traits, except root yield, other traits had good selection differential and selection gain. On the other hand, genotype no. 15 had the highest value of MTSI stability index and was unfavorable genotype in terms of studied traits. In general, among breeding hybrids, in the first the hybrid obtained from crossing of (7112 × SB36) × S1– 960132 (genotype no. 2) and then the hybrid obtained from crossing of (7112 × SB36) × S1- 970063 (genotype no. 9) can be used as promising hybrids in final evaluation programs until the introduction of new hybrids. The studied sites were not very closely correlated to be suggested that a site be abandoned to reduce costs for future research; In contrast, most of the tested environments had a high differentiation capability and could make a good distinction among genotypes in terms of sugar yield in genotype-environment interaction studies of sugar beet cultivars.

The methods used to analyze genotype-environment interaction and determine the stability and adaptability of genotypes are continuously evolving to improve the accuracy of evaluating genotypes and studying environmental interaction components. Using a combination of several methods provides a more comprehensive understanding of the genotype-environment interaction from multiple dimensions. In this study, the genotype-environment interaction was investigated using the AMMI method, along with the development of appropriate statistical techniques.

For this purpose, 25 sugar beet genotypes, consisting of 18 new hybrids and seven controls, were cultivated in seven environments: Karaj, Mashhad, Shiraz, Miandoab, Kermanshah, Hamadan, and Khoi. The experiment followed a randomized complete block design with four replications during the year 2020. After checking the uniformity of the variance of the experimental errors using Bartlett's test, the stability of the genotypes was analyzed based on the AMMI model. In this study, 12 statistics obtained from the AMMI model, including ASTAB, ASI, ASV, AVAMGE, DA, DZ, EV, FA, MASI, MASV, SIPCi, and Za, were used to identify stable genotypes. To further investigate the stability of the experimental genotypes, the SIIG index was also estimated, taking into account the criteria provided by each index based on the AMMI model.

The results obtained from Bartlett's test confirmed the homogeneity of the variance of experimental errors in experiments from different regions. Therefore, a combined variance analysis was performed based on the AMMI model. The combined analysis of variance, based on the AMMI model, indicated the significance of the additive effects of the environment and genotype, as well as the multiplicative effect of genotype-environment interaction at the 1% probability level. Analyzing the interaction effects into principal components showed that the first four components were significant at the 1% probability level and explained 93.50% of the variations related to genotype-environment interaction. According to the AMMI1 biplot, hybrids 3 and 9 were recognized as the most stable genotypes due to having a sugar yield higher than the overall average and a low value of the first interaction component. According to the AMMI2 biplot, hybrid 3 and BTS 335 with the Miandoab environment, Lexia and 4 with the Mashhad environment, Lexia with the Hamedan environment, 14 and 15 with the Kermanshah environment, 13 and 17 with the Shiraz environment, 11 with the Karaj environment, and Baloo with the Khoi environment have considerable specific adaptability. Hybrid 9, followed by 6, 2, and 8, had general adaptability. The SIIG index, calculated based on AMMI model statistics, identified 2, 9, 10, and 8 as the most stable genotypes with optimal yield.

Based on the obtained results, the environment and its interaction with the genetic structure of different genotypes have played a significant role in the phenotypic expression of white sugar yield and have caused the genotypes to provide different responses in terms of white sugar yield according to the conditions of different environments. In general, based on the results of the present study, hybrid 9 and then hybrids 6, 2, 8, 7, and 10 had high white sugar yield and yield stability. Generally, real progress in sugar beet breeding will be obtained if the genetic factors controlling the sensitivity of sugar beet genotypes to a variable environment are identified.