جستجوی مقالات مرتبط با کلیدواژه « تجزیه رگرسیون » در نشریات گروه « زراعت »

The aim of this study was to investigate the interaction between planting date and the nitrogen application rate on the growth and yield of winter wheat in Torbat-e-Jam, Khorasan Razavi province. The field experiment was conducted in a randomized block design with split plot arrangements and three replications in Torbat-e-Jam, in the 2019-2020. Experimental treatments included three planting dates: 1 October, 17 October and 2 November as the main plot, and nitrogen fertilizer at levels 0 (as a control), 100, 125, 150, 175 and 200 kg nitrogen ha-1 as a subplot. Pishtaz cultivar was planted in experimental plots which included 7 planting lines with a row spacing of 15 cm and a length of 8 m. The results of the analysis of variance showed that planting date and nitrogen fertilizer application and their interaction had a significant effect on all measured traits. The results showed that the yield and yield components were the highest on 1 October, and the values of most of these traits showed a significant decrease in planting on 12 November compared to 10 October. The highest grain yield was obtained from a nitrogen application rate of 200 kg ha-1 on 1 October and 16 October, while the maximum yield was obtained with an application rate of 175 kg ha-1 on 2 November. The growth and yield response of wheat to the rate of nitrogen application decreased with a delay in planting date, and the option of planting date must be considered in order to recommend efficient fertilizer usage.

Legumes are the most economically important food source for humans due to their protein richness, especially in developing and underdeveloped countries. Chickpea yield in spring-planting under dryland cropping decreases due to increasing temperature and day length and the occurrence of end-season drought and exposure to important pest's activity. In autumn-planting, early flowering, escaping from pests and optimal use of annual rainfall help to significantly increase in grain yield. Increasing the growth period during autumn planting has been found to result in taller plant height, making mechanical harvesting more feasible. The success of a plant breeding program relies on implementing a suitable selection design that takes into account both correlated and non-correlated relationships. Recently, a significant positive correlation has been observed between grain yield and several traits such as the number of pods, number of seeds, 100-kernel weight, and harvest index in chickpea. These traits were also found to have a direct and significant effect on chickpea grain yield. Additionally, there was a high direct effect observed for pod number, number of seeds, 100-kernel weight, and single-seed weight on chickpea grain yield.

This research was conducted on 112 chickpea genotypes in dryland spring-planting (non-cold stress condition) and autumn-planting (cold stress) based on augmented design in Dryland Agricultural Research Institute located in Maragheh. Total pods number, number of empty pods, number of tow-seed pods, plant height, first pod height from soil level, number of pods with one seed, days to maturity initiation, days to 90% maturity, 100-kernel weight, pod diameter, pod length, biomass, harvest index, fertility percent and single-plant yield were meassured. The correlation analysis, stepwise regression and path analysis, and principal component analysis were used for identifying the relationships among agro-morphological traits.

In autumn-planting condition grain yield positively correlated with all traits except days to 90% maturity, but in spring-planting condition the correlation between grain yield and first pod height, days to maturity initiation, days to 90% maturity, 100-kernel weight, pod diameter and pod length were not significant. In spring-planting, 100-kernel weight and total pods number were negatively correlated. In both spring and autumn-planting, the 100-kernel weight showed a significant positive correlation with pod diameter and pod length. This indicates that genotypes with larger pods also tend to have larger seeds. Furthermore, in autumn-planting, there was a significant positive correlation between pod diameter, pod length, and grain yield. However, these correlations were not significant in spring-planting. Stepwise regression analysis was performed to assess the factors influencing grain yield in both planting conditions. In spring-planting, the number of total pods, 100-kernel weight, fertility percent, and the number of two-seed pods were found to have direct and significant effects on grain yield. On the other hand, in autumn-planting, the number of total pods, pod length, number of empty pods, 100-kernel weight, and the number of two-seed pods were included in the final model as predictors of grain yield. These results suggest that these factors play a crucial role in determining grain yield in their respective planting conditions. In spring-planting, the genotypes 108, 63, 65 and 99 had the highest number of total pods, number of single pods, biomass and plant yield and genotypes 55, 76, 81, 82, 84, 85 and 88 had the highest weight of 100-kernel, pod length and pod diameter. In autumn-planting, the genotypes 87 and 22 had higher biomass and grain yield, genotypes 45 and 65 had higher total pods and number of single pods, genotype 89 had higher total pods and biomass and genotype 94 had higher total pods, number of single pods, biomass and yield.

Correlation analysis results showed that in non cold stress condition (spring-planting), due to the short growth period, the significant relationship of most important agronomic traits with grain yield were not revealed and important components such as 100-kernel weight did not have enough opportunity to significantly affect grain yield. In spring-planting, total pods number had a high direct effect and correlation coefficient with grain yield, but the indirect effect of this trait through 100-kernel weight on grain yield was negative because increasing the number of total pods causes decreasing the kernel weight. In autumn-planting, despite the high direct effect of total pods number on grain yield, due to the indirect negative effect through the number of empty pods, the correlation coefficient of total pod number with grain yield was not very high. Finally in order to increase grain yield in chickpea genotypes in breeding programs it is recommended that under cold stress and non-stress conditions, selection should be based on the number of total pods per plant, which is a visible trait and easy to measure.

Considering the development of cultivation and production of legumes and the importance of genetic studies in plant breeding, identifying the genetic potential of these plants is very important. Knowledge of genetic diversity and relationships between genotypes is important for understanding available genetic variability and the potential to use it in breeding programs. According to previous studies on lentils, it was found that improving the yield potential per unit area can be one of the important criteria for increasing the production of this plant. Increasing the yield per unit area is possible mainly by modifying and creating high-yielding cultivars, improving the characteristics and increasing the quantitative and qualitative potentials. Breeders and plant physiologists believe that in order to be more productive in improving compatible cultivars in areas with limited water resources, recognizing the agronomic traits affecting grain yield under stress conditions will be of great importance; Therefore, indirect selection based on physiological traits has been proposed as a complement to the selection of cultivars with high yield potential. Considering the different reactions of photosynthetic indices under stress conditions, it is important to know the genotypic diversity of photosynthetic indices under culture conditions and their relationship with grain yield. Despite numerous studies on the role of physiological traits in drought tolerance in crops, recent studies on lentils, especially in Iran, are limited. This study was designed and carried out with the aim of determining genotypes with desirable physiological and yield traits and the relationship between these traits and photosynthesis under rainfed conditions.

In order to study the photosynthetic and yield parameters of lentil plant in rainfed conditions, selected advanced lentil lines with control cultivars were studied in a randomized complete block design with 3 replications in Khodabandeh dryland research station in Zanjan Province in two cropping seasons 2018 to 2020. Physiological traits included photosynthesis per unit leaf area, stomatal conductance, transpiration rate, photosynthetic activated radiation, sub stumatal CO2, leaf temperature, photosynthetic water use efficiency, mesophilic conductivity and water use efficiency. Plant height, 100-seed weight, number of pods and yield (kg/ha) were also measured for each genotype in each plot. Analysis of variance and comparison of means were performed using Duncan's test at 5% probability level. Finally, correlation analysis and stepwise regression analysis were performed with the variables of photosynthesis rate and total yield.

The results showed that there was a significant difference in photosynthetic active radiation, leaf temperature, photosynthetic water use efficiency, mesophilic conductivity, water use efficiency, 100-grain weight and yield between two years of experiment. The studied genotypes showed significant differences in leaf temperature, photosynthesis, plant height, 100-seed weight and yield, which indicated the high genetic diversity of these genotypes in terms of these traits. The interaction effect of genotype per year was not significant in all studied traits, which shows that the trend of changes in these traits between genotypes during the two years was the same. Among the studied genotypes, G5 genotype is a genotype with superior agronomic characteristics that can be recommended as a cultivar with high yield potential. Photosynthesis rate showed a significant negative correlation with leaf temperature and significant positive correlation with transpiration rate, stomatal conductance, mesophilic conductivity, water use efficiency and 100-grain weight. 100-seed weight showed a significant negative correlation with leaf temperature and a significant positive correlation with stomatal conductance, photosynthesis, mesophilic conductivity and water use efficiency. These results show that drought and lack of water in the soil have the greatest effect on reducing photosynthesis and plant yield at different phenological stages (seedling, flowering and podding) of the plant. Finally, regression analysis showed that stomatal conductance and sub stumatal CO2 explained the changes in photosynthesis.

The results showed that for lentils, two traits of stomatal conductance and sub stumatal CO2 concentration may explain the changes in photosynthesis. Genetic diversity is very important for crop breeding and higher diversity of genotypes provides a better chance of producing a variety of desirable cultivars. The observed genetic diversity in traits can help select superior genotypes based on phenotypic expression and can be used in breeding programs to improve economically important traits. Finally, among the studied genotypes, G5 genotype was found to be a genotype with superior agronomic characteristics that could be recommended to the farmers to improve lentil yield.

In order to study of genetic diversity and classify barley cultivars under optimal and limited irrigation conditions an experiment was evaluated on 138 barley cultivars using alpha latis design with two replications at research field of Tehran University. Result of analysis of variance showed that there are highly significant differences among cultivars in studied traits which reveal high genetic variation among the cultivars. According to stepwise regression and path analysis, under optimal irrigation condition, seed number per plant and biological yield, and under limited irrigation condition biological yield and harvest index were the most important traits affecting grain yield. Factor analysis showed that in both optimal and limited irrigation conditions four factors were selected, which explained 80.33 and 79.93% of the changes, respectively. In both cases, the first factor was named as the performance factor explanation the most data changes. According to the biplot diagram, in optimal condition, cultivars 54, 57, 37, 103, 31, 30, 2 and 29 , and in limited irrigation, cultivars 130, 127, 124, 97, 122, 99, 29 and 55 which were at a high level in terms of the first and second factors, were selected as superior cultivars. Cluster analysis in n under optimal and limited irrigation conditions grouped cultivars into four and five clusters respectively. Which the results of cluster analysis confirmed grouping cultivars based on biplot diagram.

Oilseed crops have an effective role in nutrition and industry. Flax (Linum usitatissimum) seeds contain approximately 30 to 40 percent of oil rich in unsaturated fatty acids, especially linolenic acid. Previous studies in flax had showed significant positive correlation of seed yield with number of branches per plant, number of capsules per plant and 100 seed weight. It had reported that the number of capsules per plant is the most important selection criteria for genetic improvement of seed yield in flax. The present study was conducted to investigate relationship between seed yield and its related traits in breeding lines derived from KO37× SE65 cross using correlation, regression and path analysis to determine the best indirect selection criteria for genetic improvement of seed yield in flax.

In order to study the relationships between traits, 112 breeding lines along with six genotypes as control (including parental genotypes) were evaluated in augmented experiment design. Genotypes were planted in a randomized complete block design with 3 replications. Morphological, phonological and agronomic traits such as number of days to 50% flowering, end of flowering, period of flowering, number of branches per plant, number of capsule per plant, biological yield, and seed yield per plant were measured and analyzed using SAS software(Version, 9.1).

Number of capsule per plant, number of branches per plant, seed weight per capsule and biological yield per plant were positively correlated with seed yield per plant. Based on the results of stepwise regression analysis, number of capsule per plant could enter to the model in the first step and accounted 78% of the total variation. Seed weight per capsule and the number of branches per plant were entered in the subsequent steps and could explain the 86.87% of total variation. Path analysis results indicated that number of capsule per plant had the most direct effect on seed yield per plant, whereas, number of branches per plant had the most indirect effect through number of capsule per plant. Number of capsule per plant was recognized as the most important component explaining seed yield variation in the studied population. Four factors explained the most of variation of studied traits and could explain more than 68% of the total variation.

According to the results, number of capsule per plant had the most impact on seed yield variation and also there was no significant negative correlation between this trait and other seed yield components. Therefore, number of capsule per plant can be used as an indirect selection criteria for genetic improvement of seed yield in flax.

To determine the relationship between some physiological and yield traits under salinity stress conditions and screening quantitative indices of salinity tolerance, 28 sugar beet (Beta vulgaris L.) genotypes derived from the cross between full-sib 8001 with moltigerm male-sterile single cross C2 and male-sterile monogerm 231×261 with two control varieties were tested in a randomized complete block design with three replications under salinity and normal conditions at Miandoab Agricultural and Natural Resources Research Station. Relationships between traits with root and sugar yield were investigated using correlation, regression and path analysis. Under normal conditions, root yield showed positive correlation with pure sugar yield and negative correlation with sugar content and potassium to sodium ratio. Under salinity stress conditions, positive correlation was observed between root yield and sugar yield, pure sugar yield, potassium to sodium ratio and relative water content of leaves and negative correlation with sodium content and molasses sugar. Changes in environmental conditions caused change in the relationship between root yield and some traits. The results of regression and path analysis showed that under normal conditions if root yield was variable, sugar content and white sugar yield traits justified the changes, thus, in path analysis white sugar yield had the most positive and direct effect and sugar content had the most direct and negative effect on root yield. However, when sugar yield was variable, the traits potassium content, the relative amount of water loss, and nitrogen content justified the changes and among these traits, nitrogen content had the most positive direct effect and the other two traits had the most negative direct effect on sugar yield. On the contrary, under saline condition, if root yield was variable, sugar yield, white sugar yield, syrup purity, and sugar content explained the changes and white sugar yield had the most positive direct effect and sugar yield had the most negative direct effect on root yield. But, when sugar yield is variable, pure sugar yield and syrup purity justify the changes and white sugar yield had the most positive direct effect on sugar yield.

Rice milling parameters consist of milling recovery, broken grain percent, chalkiness and whiteness due to the effect on waste, price, marketing and final income of production. Reducing in rice grain milling parameters due to climate change and global temperature increase is one of the most important challenges in many of the world's rice planting regions, including our country, and the changes in milling recovery, regardless of agronomic management, depend on the environmental conditions of each region, especially the air temperature on grain filling stage. Therefore, the present study was conducted to investigate the effect of different local climates on milling parameters (MP) of two rice cultivars (cvs. ‘Tarom-Hashemi’ and ‘Shiroudi’) and also to estimate the relationships between MP and average air temperatures (AAT) during the grain filling stage of rice (from anthesis stage (50% of flowers opened) to harvesting time) in Babolsar, Amol and Polesefid regions in Mazandaran province.

Three field experiments were conducted separately based on the randomized complete blocks design with four replications in Babolsar (-21 m sea level, asl), Amol (+24 m asl) and Polesefid (+625 m asl) in the north of Iran on two rice cultivars ‘Tarom-Hashemi’ and ‘Shiroudi’ in 2014. All agronomic managements were done based on local recommendations in each region. Moreover, all studied traits were measured in the grain quality laboratory of Rice Research Institute of Iran, Deputy of Mazandaran (Amol) in three months after harvesting.

The results indicated that the effects of different local climates were statistically significant on percentage of milling recovery, head and broken grain and chalkiness (P < 0.01). All studied traits in Polesefid were better than them in both Amol and Babolsar which can be due to lower temperature during the grain filling stage of rice. In general, milling recovery (1.46 and 1.03 %, respectively), amount of head grain (3.58 and 3.11 mm, respectively) and whiteness (1.25 and 1.42, respectively) increased linearly per unit increase in AAT in both ‘Tarom-Hashemi’ and ‘Shiroudi’, respectively. Inversely, broken grain of rice (2.63 and 2.51%) and chalkiness content (1.65 and 4.24%) increased linearly per unit increase in temperature for ‘Tarom-Hashemi’ and ‘Shiroudi’, respectively. Milling economic benefit also decreased 8000,000 and 12,000,000 Rial ha-1 per unit increase in temperature for ‘Tarom-Hashemi’ and ‘Shiroudi’, respectively.

These results can be used for predicting the amount of rice milling wastage and estimating the effect of temperature on economic benefit under climate conditions of Mazandaran province. Based on our findings in this study, milling parameters variation were related to temperature which can be estimated in both cultivars (‘Tarom-Hashemi’ and ‘Shiroudi’) under different local climates of Mazandaran.

To identify markers associated with drought tolerance related traits under two different moisture conditions including rainfed (drought stress) and supplementary irrigation, an experiment was conducted in two consecutive years (2013-2015). Among the AFLP primers used in this study, eight EcoRI/MseI primer combinations produced a total of 119 polymorphic bands with an average of 14.88 bands per marker. The average polymorphic information content (PIC) for all markers was calculated 0.298. Based on PIC, Shannon's index (I), expected heterozygosity (He) and effective allele (EA), the combination of E-ACT/M-CTT was identified as the best primer combination in distinguish of the studied genotypes. The relationship between agro-physiological traits as dependent variables and molecular data as independent variables was investigated using stepwise multiple regression analysis method and 76 and 98 markers associated with traits were identified under rainfed and supplementary irrigation conditions, respectively. Under supplementary irrigation conditions, the highest coefficient of determination (R2) was allocated for E-ACT/M-CTC-11 marker with more than 60% explanation of variations in peduncle weight, peduncle length, spike dry weight and grain weight per spike and E-ACT/M-CTT-8 with explanation of 62% variation of 1000 grain weight. Under rainfed conditions, the markers E-ACT/M-CTT-8 with 70%, E-ACG/M-CTG-2 with 57% and E-ACG/M-CAA-2 with 51%, explained the highest variation of 1000 grain weight, relative water lose and relative water content, respectively. The markers E-ACT/M-CTC-11 and E-ACG/M-CAA-20 explained 32% and 41% of the grain yield variance under supplemental irrigation and rainfed conditions, respectively. In this study, the marker E-ACT/M-CTT-8 explained more than 60% of the variation in 1000 grain weight under both experimental conditions. The results of this study can be useful in providing basic information for indirect selection of wheat traits using associated markers under rainfed conditions.

In order to recognize the soybean tolerant genotypes, a greenhouse as factorial experiment was conducted in form of randomized complete block design with three repetition in 2017 in Damavand. The first factor contained 15 soybean genotypes and second factor included two levels of normal irrigation and irrigation disruption in time of podding. The traits included plant height, reproductive branches no., number of leaves, chlorophyll a, chlorophyll b, chlorophyll total, carotenoids, days to flowering, days to fifty percent podding, number of  flowers, dry weight of plant leaves, main stem nodes no, nodes in the, branches no, total dry stem weight, plant dry weight, first pod height of soil, days to harves, total pod no, dry weight of pod, pods length, seed pod no, seeds per plant, harvest index, weigh one hundred seeds and yield per plant. The analysis variance results showed that the reaction of soybean genotypes to conditions of drought stress and lack of stress were different. The genotypes of 1, 4, 10, 14 and 15 represented high yield in both conditions of drought stress and normal conditions. Analysis of phenotypic correlation showed that the seed yield has a positive correlation with seeds per plant, harvest index, total  dry weight of pods, weight dry of plant. Stepwise regression analysis for seed yield showed 99 % of variation of yield, as a dependent variable justified. In the path analysis for grain yield the maximum positive direct effects were related to weight dry of plant and weigh one hundred seeds that showed important characteristics in relation to grain. Principal component analysis used to study the relationship between indices. Two first components could explain more than 85% of variations of indices. Cluster decomposition divided the genotypes into 5 groups and genotypes 1, 9, 10, 14 and 15 were set in one group. These genotypes have good yield in both environments according to the mean.

To analyze genotype × environment interactions (GEI) on yield and seed oil content of 15 safflower genotypes (including 8 breeding lines, 6 cultivars and one landrace), multi-environment trials were conducted in three sowing times (fall, entezari and spring) at four dryland agricultural research stations including Kermanshah, Maragheh, Kurdistan and Zanjan (totally 21 environments) during 2011-2013. The two models combined index (regression analysis + yield) and GGE biplot were used for stability analysis. The combined ANOVA revealed that genotype, environment, and GEI were highly significant for the two traits (P < 0.01). The sum of squares of genotype, environment, and GEI were accounted 5, 62 and 24% for yield, and 25, 45 and 22% for oil content.The result of regression analysis indicated that the regression components were significant in both traits. According to combined index, G5, G1, and G6 for yield, and G5, G3 and G4 for oil content were superior genotypes. The polygon view of the GGE biplot showed that all test environments were divided into 3 environmental groups for both traits. Two environments of Maragheh for yield and six environments of Kurdistan for oil content were favorable. Based on GGE biplot, G10 and G5 for yield and G11, G4 and G5 for oil content had a high combination of yield (or oil content) and stability. High rank correlation coefficients were obtained between regression and GGE biplot models in both traits. Based on the results of two models, G5 (Padideh) is superior in terms of yield and oil content and is recommended for all rainfed environments.

In order to investigate the relationship between agronomic and morphological traits affecting wheat yield, two genotypes of wheat (Gasspard cultivar and DN11 line), along with generations of crosses (F1, F2, F3, BC1 and BC2), were examined in a randomized complete block design with three replications in normal and water deficit conditions in two consecutive years in the field of Research Institute of Nuclear Agriculture of Karaj. Stepwise regression analysis showed that straw yield was the first trait that entered the model and alone explained 46% and 65% of grain yield per plant in normal and water deficit conditions, respectively. Following this trait, under normal conditions, number of grain per spike, 100 grain weight, number of tiller per plant and number of spikes per plant had the high effect on grain yield per plant, explained about 78% of the total variation. In water deficit condition, the number of grain per spike, number of spikes per plant, 100 grain weight and days to maturity justified 92% of the grain yield per plant. The results of path analysis showed that in normal conditions, 100 grain weight, grain number per spike, tiller number per plant, straw yield and number of spike per plant and in water deficit condition, number of spike per plant, number of grain per spike, 100 grain weight and straw yield had the most direct effect on grain yield per plant.

Salinity and drought are known as the most important abiotic stresses to reduce the growth and development of crops. To evaluate drought tolerance of lentil landrace genotypes at flowering stage, a split plot experiment based on randomized complete block design with four replications was conducted at the Agricultural Faculty of Islamic Azad University, Tabriz branch, during 2012-2013. Combined variance analysis of data showed that genotype × drought stress interaction was significant for all traits under study. This indicates different response of, genotypes to drought stress for these traits. Mean comparison of yield for genotype × drought interaction showed significant yield reduction for all genotypes under drought stress as compared to non-stress conditions. However, Shavi Varzeghan genotype under both stress and non-stress conditions, showed better response than other genotypes. To evaluate tolerance of of lentil landrace genotypes to salinity and drought stresses, a factorial experiments based on completely randomized design with three replications was conducted in 2013 at the greenhouse of Tabriz Azad University. Factors in this experiment were: drought stress at two level (control and irrigation for 50% of field capacity); two salinity levels (control and 4 ds/m salinity) and 7 lentil landrace genotypes. Analysis of variance showed that three way interactions of genotype ×drought × salinity was significant only for root length which indicates different response of genotypes for this trait for salinity and drought stresses. The effect of salinity and drought stress levels on all traits was significant which indicates reduction in traits value under salinity and drought stresses.Estimation of simple correlation among traits showed that, shoot length and number of shoot correlated pasitively with shoot dry weight and root dry weight with root length and number of lateral roots. Cluster analysis divided genotypes into two clusters. The second cluster consisted to Kaleybar, Horand and ShaviVarzeghan genotypes. These genotypes were tolerant as compared to the other genotypes during vegetative growth stage.The regression and path analysis for shoot dry weight showed number of lateral roots had the highest direct and indirect effect on shoot dry weight under drought and salinity stress. Cluster analysis of traits, divided genotypes into two clusters. The second cluster were Kaleybar, Horand and Shavi Varzeghan genotypes. These genotypes had higher mean values for the traits under study and could be tolerant genotypes for drought and salinity stresses at vegetative growth stage.