Soil quality assessment of paddy fields (in Northern Iran) with different productivities: establishing the critical limits of minimum data set indicators.

The aim of this study was to assess soil quality and identify main indicators and their critical limits as a function of relative rice yield in northern Iran. In present study, 60 topsoil (0-30 cm) samples were collected and 18 physical, chemical, and biological soil attributes were measured and analyzed. Based on the mean rice yield obtained from sampling sites, paddy fields were divided into fields with low ([Formula: see text] 4.5 t ha-1) and high ([Formula: see text] 4.5 t ha-1) productivity. Using the principal component analysis (PCA), among 18 soil indicators, 4 indicators were selected as the minimum dataset (MDS) including soil organic carbon (OC), urease activity, bulk density (BD), and available Zn (AZn). The upper and lower limits of MDS indicators and soil quality index (SQI) were defined using scatterplot. The results showed that the mean SQI of high productivity fields (0.95) was significantly higher than that in low productivity fields (0.77). The upper and lower limits for soil OC were 3.5 and 1.0 (g 100 g-1), urease activity 84 and 43 (µg NH4 g soil-1 2 h-1), BD 1.84 and 1.60 (g cm-3), and AZn 2.0 and 0.6 (mg kg-1), respectively. The soil quality assessment using SQI accounted for 52% of the rice yield variation. Thus, management practices and mitigation of soil limiting factors should be comprehensively investigated to ensure sustainable rice production in the paddy fields of northern Iran.

Meta-analysis of QTLs and candidate genes associated with seed germination in rice (Oryza sativa L.).

Seed germination is one of the critical stages of plant life, and many quantitative trait loci (QTLs) control this complex trait. Meta-analysis of QTLs is a powerful computational technique for estimating the most stable QTLs regardless of the population's genetic background. Besides, this analysis effectively narrows down the confidence interval (CI) to identify candidate genes (CGs) and marker development. In the current study, a comprehensive genome-wide meta-analysis was performed on QTLs associated with germination in rice. This analysis was conducted based on the data reported over the last two decades. In this case, various analyses were performed, including seed germination rate, plumule length, radicle length, germination percentage, coleoptile length, coleorhiza length, radicle fresh weight, germination potential, and germination index. A total of 67 QTLs were projected onto a reference map for these traits and then integrated into 32 meta-QTLs (MQTLs) to provide a genetic framework for seed germination. The average CI of MQTLs was considerably reduced from 15.125 to 8.73 cM compared to the initial QTLs. This situation identified 728 well-known functionally characterized genes and novel putative CGs for investigated traits. The fold change calculation demonstrated that 155 CGs had significant changes in expression analysis. In this case, 112 and 43 CGs were up-regulated and down-regulated during germination, respectively. This study provides an overview and compares genetic loci controlling traits related to seed germination in rice. The findings can bridge the gap between QTLs and CGs for seed germination. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-022-01232-1.

Application of image processing and soft computing strategies for non-destructive estimation of plum leaf area.

Plant leaf area (LA) is a key metric in plant monitoring programs. Machine learning methods were used in this study to estimate the LA of four plum genotypes, including three greengage genotypes (Prunus domestica [subsp. italica var. claudiana.]) and a single myrobalan plum (prunus ceracifera), using leaf length (L) and width (W) values. To develop reliable models, 5548 leaves were subjected to experiments in two different years, 2019 and 2021. Image processing technique was used to extract dimensional leaf features, which were then fed into Linear Multivariate Regression (LMR), Support Vector Regression (SVR), Artificial Neural Networks (ANN), and the Adaptive Neuro-Fuzzy Inference System (ANFIS). Model evaluation on 2019 data revealed that the LMR structure LA = 0.007+0.687 L×W was the most accurate among the various LMR structures, with R2 = 0.9955 and Root Mean Squared Error (RMSE) = 0.404. In this case, the linear kernel-based SVR yielded an R2 of 0.9955 and an RMSE of 0.4871. The ANN (R2 = 0.9969; RMSE = 0.3420) and ANFIS (R2 = 0.9971; RMSE = 0.3240) models demonstrated greater accuracy than the LMR and SVR models. Evaluating the models mentioned above on data from various genotypes in 2021 proved their applicability for estimating LA with high accuracy in subsequent years. In another research segment, LA prediction models were developed using data from 2021, and evaluations demonstrated the superior performance of ANN and ANFIS compared to LMR and SVR models. ANFIS, ANN, LMR, and SVR exhibited R2 values of 0.9971, 0.9969, 0.9950, and 0.9948, respectively. It was concluded that by combining image analysis and modeling through ANFIS, a highly accurate smart non-destructive LA measurement system could be developed.

High genetic diversity in Aegilops tauschii Coss. accessions from North Iran as revealed by IRAP and REMAP markers.

BACKGROUND: Aegilops tauschii Coss. as a donor of wheat D genome has an important role in wheat breeding programs. Genetic and phylogeographic diversity of 79 Ae. tauschii accessions collected from north and northwest of Iran were analyzed based on retroelement insertional polymorphisms using inter-retrotransposon amplified polymorphism (IRAP) and retrotransposon-microsatellite amplified polymorphism (REMAP) markers. RESULTS: In total, 306 and 151 polymorphic bands were amplified in IRAP and REMAP analyses, respectively. As a result, a high level of polymorphism was observed among the studied accessions as revealed by an average of 25.5 bands per primer/primer combination and mean PIC value of 0.47 in IRAP and an average of 25.16 bands per primer combination and mean PIC value of 0.47 in REMAP. Genetic relationships of the accessions were analyzed using distance- and model-based cluster analyses. CONCLUSION: The result showed that genetic distance did not seem to be related to geographic distribution, and the accessions could be divided into three groups, which was further supported by principal coordinate analysis. These results on genetic diversity and population structure of Ae. tauschii in Iran should provide important knowledge on genetic resources and their applications in wheat breeding programs.

Screening of rice drought-tolerant lines by introducing a new composite selection index and competitive with multivariate methods.

Selection and breeding for drought tolerance in rice have always been one of the leading objectives for rice breeders in water-deficient farming areas. In the present study, we applied the potential of recombinant inbred lines (RILs) population, which were derived from cross Shahpasand (Iranian landrace) and IR28, for the development of drought-tolerant rice lines. One hundred fifty-two lines along with five check varieties were investigated from 2017 to 2019 under non-stress and drought stress conditions. The yield reduction caused by drought based on overall mean during 2017, 2018, and 2019 were estimated to be 89.40, 57.95, and 35.31%, respectively. Using different statistical methods, certain lines, including L33, L90, and L109, which are considered as the best lines in most environments, were found to be promising for being utilized to increase rice drought tolerance. The averages of grain yield of the above-mentioned lines were respectively 6.45, 5.80, and 5.70 t ha-1 under non-stress condition, and respectively 2.77, 2.66, and 2.59 t ha-1 under drought stress condition. The yield reduction of the selected lines were significantly lower than that of others indicating the significant transgressive segregation. The results revealed using the combination of the best identified tolerance and susceptibility indices and GT-biplot are effective methods for screening superior lines. However, their utilization is not easy and requires specialized packages. For the first time, we introduced a new composite index as a combination of significant indices (CSI). CSI is in the form of a linear function of indices which effectiveness is determined by their correlation coefficient with grain yield. According to our results, using CSI, the identified rice drought-tolerant lines were in high agreement with those obtained by other methods, demonstrating that CSI is a simple but reliable composite index.

Exogenous 5-azaCitidine accelerates flowering and external GA3 increases ornamental value in Iranian Anemone accessions.

The Anemone genus is a tuberous geophyte which undergoes a dormancy period during unfavorable environmental conditions for growth. Five species of the Anemone genus naturally grow in several regions of Iran. The diverse uses of Anemone in gardens for landscaping, cut flowers, and potted plants indicate its high ornamental potential. Its dormancy and flowering are influenced by various factors. The present paper was conducted to explore the flowering behavior of Anemone accessions in response to different pre-treatments. For this purpose, tubers of 18 Anemone accessions (A. coronaria and A. biflora) were collected from natural regions of six provinces in Iran. These tubers were subjected to different conditions of non-chilling (20 °C, 90 days), chilling (4 °C, 90 days), GA3 (150 mgL-1; 24 h), and 5-azaCitidine (5-azaC; 40 µM; 24 h) prior to the cultivation. Most of the accessions were able to enter the flowering stage without chilling. The shortest period for the sprouting of tubers (16.89 ± 7.83 days) belonged to 5-azaC pre-treatment. In addition, this treatment accelerated the flowering time (about 30 days earlier) and diameter of the stem, bud, and flower. Morphological characteristics, such as stem height, number of leaves, bud, and petal and the longevity of flowers on the plant were significantly affected by GA3 pre-treatment. Our results indicated a positive correlation between flower length, stem height, and stem diameter with flower longevity under different pre-treatment conditions. The present study demonstrated that accessions Anm3, Anm12, and Anm18 had ornamental values higher than the population mean across four conditions.

Cellular and physiological responses to drought stress in Aegilops tauschii genotypes.

Drought stress is one of the most important limiting factors in crop yield through impact on the cellular and physiological functions of the plant. Therefore, the study of physiological responses of plants can help to better understanding the drought tolerance mechanisms. In this experiment, 125 wild diploid wheat genotypes of Aegilops tauschii were evaluated for the physiological responses under rainfed and supplemental irrigation conditions. The physiological characteristics such as leaf relative water content (RWC), excised leaf water retention (ELWR), relative water loss (RWL), chlorophyll a, chlorophyll b, total chlorophyll, carotenoids, ion leakage, membrane stability index (MSI) and proline content were measured. The results showed that the higher proline content, lower chlorophyll degradation rate and low amount of the membrane stability index (MSI) may inhibit the grain yield reduction under rainfed conditions. It was also found that the lower ion leakage due to the low cell membrane damage may led to the higher yield under rain-fed conditions. The results of regression analysis in both rainfed and supplemental irrigation conditions showed that proline content and total chlorophyll were introduced into the model, and explained the most variation in the grain yield. So, considering the above traits, the genotypes 16, 22, 43, 66 and 106 seems to be more drought tolerant and could be exploited in wheat breeding programs after further assessments.

Superior adaptation of aerobic rice under drought stress in Iran and validation test of linked SSR markers to major QTLs by MLM analysis across two years.

Drought is one of the biggest challenges for rice (Oryza sativa L.) production in rainfed areas. Developing "aerobic rice" cultivars could be a valuable alternative to irrigated/rainfed areas. During 2010-2013, 115 rice genotypes, including non-local cultivars and aerobic rice genotypes, were evaluated and 31 rice genotypes were screened, while 21 Iranian lowland rice cultivars (52 genotypes) were investigated under non-stress and drought conditions at the University of Guilan, Rasht, Iran, in 2014 and 2017. The results revealed the superiority of high yielding genotypes, namely Neda (6.202 t ha- 1), IR82639-B-B-140-1 (6.020 t ha- 1), and IR82635-B-B-82-2 (5.75 t ha- 1) under non-stress, Panda (4.512 t ha- 1), and IR82639-B-B-140-1 (4.08 t ha- 1), under drought stress conditions. Based on the molecular markers evaluation using identified SSR markers linked to major QTLs different important traits specially drought stress, IR 82639-B-B-140-1 showed the highest genetic distance with high-quality Iranian lowland cultivars, which could be considered as a donor for the development of new cultivars. Moreover, the assignment of rice genotypes based on Jaccard distance clustering was in agreement with the grouping of structure analysis. The validation test using MLM analysis in this natural population revealed the most important significant associations that were identified under drought conditions. These are: the associations between RM306, RM319, RM511, RM28166, and RM11943 with different grain yield (GY)-related traits simultaneously and stable across both years. These markers, which were verified in a natural population across 2 years, could be considered as the potential markers for use in marker-assisted breeding and to improve the grain yield of rice.

Association analysis, genetic diversity and structure analysis of tobacco based on AFLP markers.

Knowledge in the area of genetic diversity could aid in providing useful information in the selection of material for breeding such as hybridization programs and quantitative trait loci mapping. To this end, 50 Nicotiana tabacum genotypes were genotyped with 21 primer combination of amplified fragment length polymorphism (AFLP). A total of 480 unambiguous DNA fragments and 373 polymorphic bands were produced with an average of 17.76 per primer combination. Also, the results revealed high polymorphic rate varing from 52.63 to 92.59%, demonstrating that AFLP technique utilized in this research can be a powerful and valuable tool in the breeding program of N. tabacum. Cluster analysis based on complete linkage method using Jaccard's genetic distance, grouped the 50 tobacco genotypes into eight clusters including three relatively big clusters, one cluster including Golden gift, Burly 7022 and Burly Kreuzung, one cluster consisting of two individuals (Pereg234, R9) and three single-member clusters (Pennbel69, Coker176 and Budisher Burley E), Recent genotypes showed high genetic distance from other genotypes belonging to cluster I and II. Association analysis between seven important traits and AFLP markers were performed using four statistical models. The results revealed the model containing both the factors, population structure (Q) and general similarity in genetic background arising from shared kinship (K), reduces false positive associations between markers and phenotype. According to the results nine markers were determined that could be considered to be the most interesting candidates for further studies.

Mapping QTLs for traits related to salinity tolerance at seedling stage of rice (Oryza sativa L.): an agrigenomics study of an Iranian rice population.

Rice (Oryza sativa L.) is one of the most important food crops in the world, especially in Asian countries, and salinity is a major constraint to the sustainability and expansion of rice cultivation. Genetically improving salt tolerance of rice is a highly important objective of rice breeding programs. Traits such as salt tolerance are quantitatively inherited. Hence, mapping quantitative trait loci (QTL) with molecular markers can be very helpful to plant breeders in the field of agricultural genomics (AgriGenomics). In this investigation, QTL analysis of physiological traits related to salt tolerance was carried out using F2:4 population of rice derived from a cross between a salt-tolerant variety, Gharib (indica), and a salt-sensitive variety, Sepidroud (indica). A linkage map based on 148 F2 individuals was constructed with 131 SSR markers and 105 AFLP markers, covering 2475.7 cM of rice genome with an average distance of 10.48 cM between flanking markers. A total of 41 QTLs for twelve physiological traits under salinity stress were detected distributed on all rice chromosomes, some of them being reported for the first time. Also, overlapping of QTLs related to salt tolerance were observed in this study. Some of the identified QTLs on specific chromosomal regions explaining high phenotypic variance could be used for marker-assisted selection (MAS) programs. New QTLs retrieved in this study play an important role in growth of rice at seedling stage in an Iranian local population under high salinity conditions.