Applied Agricultural Research
Year:2020 | Volume:33 | Issue:3 (128)|Papers Count:7

Increasing crop production to meet the food demands of the world`s buregioing population is of paramount importance (Barea, 2015). Intensive agriculture is characterized by a large use of inputs (chemical fertilizers and pesticides), causing a large pressure on the environment. Today, due to the limited arable lands and ever growing need to feed human communities, the adoption of intensive farming has resulted in an unbalanced use of chemical fertilizers (Scotti et al., 2015). The consumption of the chemical fertilizers: nitrogen (N), phosphate (P2O5), potash (K2O) across the world was 85. 5, 32. 2 and 20. 4 (kg of nutrients per ha) in the year 2014, respectively. While in the year 2000, the respective values for these fertilizers were 64. 9, 25. 9 and 18. 2 (kg of nutrients per ha), exhiniting a 31. 7, 28. 1 and 12 % increase in their use in fourteen years’ time, respectively (FAO, 2015). Unbalanced and inconsiderate use of chemical inputs cause instability in agricultural ecosystems and irreparable economic and environmental damages. long term and to reduce or eliminate chemical inputs in agricultural production. Biological fertilizers contain preservatives with a dense population of beneficial soil microorganisms, which can improve soil fertility and provide an appropriate supply of nutrients needed by plants. The incorporation of beneficial microorganisms into sustainable farming systems can enhance food quality and quantity. Materials and Methods: This experiment was conducted as a factorial layout based on a randomized complete block design with four replications during the growing season of 2016 at the experimental field of Beiran Shahr town of Khorramabad in Lorestan Province, Iran (48° 31’ E, 33° 40’ N and 1653m above the sea level). Before conducting the experiment, to determine the physical and chemical properties of the soil, samples were collected from 0-30 and 30-60 cm depth of the soil. During this experiment, the effects of three factors were studied: 1. inoculation with Arbuscular mycorrhizal M (Glomus etunicatum, G. intraradices, G. mossea) in two levels (M1= inoculation, M2= no inoculation), 2. inoculation with Azotobacter chroococcum (strain 15) A, in two levels (A1= inoculation, A2= no inoculation) and 3. the response of three different cultivars of red bean (Phaseolus vulgaris L. ) (V1: landrace beiran shahr, V2: Akhtar and V3: Goli varieties). Chlorophyll content of the leaf was estimated by using chlorophyll meter SPAD-502 Plus, Konica Minolta. The protein percentage determined by Macro– Kjeldahl method and to measure root colonization, the gridline intersect methods was employed. Results and Discussion: The results showed that the main effect of the biological fertilizer on leaf number, SPAD chlorophyll content, root colonization, seed protein percent, seed yield and straw yield was significant. Moreover, the two-way interaction effects of mycorrhiza and Azotobacter on root colonization were statistically significant. Based on the variance analysis, the effects of triple interactions between azotobacter×mycorrh iza×cultivars were found to be significant for seed economic yield (P≤ 0. 05). The seed yield for landrace Beiran Shahr, Akhtar and Goli varieties increased by 56. 5, 19. 1 and 43. 2 percent as compared to non-inoculation treatment, respectively. The combined effect of azotobacter×mycorrhizal produced the highest seed yield in Goli variety (2981 kg. ha-1), which is a bean plant of indeterminate growth type. Conclusions: The results of this experiment showed that the studied traits of the red bean cultivars were influenced by the application of biological fertilizer. It seems that the use of biological fertilizers (mycorrhiza and azotobacter) results in a better root and shoot growth, a balanced vegetative and reproductive development and improvement of leaf number, SPAD chlorophyll content and root colonization, which ultimately contributes to a significant increase in the plant economic performance. Generally, the application of these microorganisms provided the conditions necessary for the improvement of the key characteristics associated with the growth and qualitative performance of bean plants, which is in line with the objectives of sustainable production of this plant, as well as with the reduced use of chemical fertilizers in sustainable ecosystems.

Given the performance and the desirable qualitative characteristics of the fruit in the promising line D7, the introduction of this line as a new variety of eggplant could be very well justified and will certainly contribute to a much higher economic income and improved livelihood for the farmers and growers. In addition, the new release of Brilliant Eggplant is a very strong domestic competitor to foreign cultivars, which is completely in line with the goals of the Resistance Economic Program and is certainly a step towards preventing the outflow of foreign currency and helping to boost domestic employment. Therefore, the promising line D7 was introduced in 1397 as a new variety of bright eggplant. Materials and Methods: In the project “ Selection of Lines from Five Indigenous Masses of Eggplant in Iran” , 5 indigenous masses of eggplant in the country were collected and subjected to a pure line selection/correction program. Selected lines along with Varamin Ghalami as a check were compared for one year in three regions of Karaj, Varamin and Dezful under the project “ Investigation of selected lines of native eggplants in advanced experiments” in a completely randomized block design with 3 replications. The stability performance of the genotypes was evaluated using the relative superiority coefficient method. The selected lines of the advanced performance experiments in five regions of Karaj, Jiroft, Urmia, Dezful and Mazandaran were studied for two years. The experimental treatments included 4 advanced lines of sweet and semi-sweet eggplant and three checks (local Borazjan, Qasri Dezful and Black Beauty). Finally, an experiment was carried out on the field of farmers in Dusari city, located in the south of Kerman province, using the promising lines BJ30, D7, D1 and non-hybrid eggplants Results and Discussion: At the end of the first year of the project (2006) and due to quantitative and qualitative traits and with special emphasis on fruit traits, the top single plants were selected and their fruits were sown. In the second year of the project (2007), which was performed in an augmented layout, the top lines were selected, and the line D7 was opted as one of the selected lines with a difference of 10. 3 tons per hectare as compared to the mother control (Dezful Qasri Mass). At the end of the third year of the project, which was carried out in a completely randomized block design and according to the means comparisons, the selected lines were selected and introduced for advanced experiments. As a result of these studies, the line D7 was selected with a yield of 39 tons per hectare and a difference of about 10 tons per hectare with the check Varamin Ghalami, which had given the highest yield among the selected lines from Dezful region. In the advanced yield tests (2010) in Karaj, Varamin and Dezful regions, the line D7 with a yield of 37. 1 tons per hectare and with appropriate quality characteristics was selected as a top line. The compatibility and sustainability studies for this line during the years from 2011 to 2013 resulted in an average yield of 31. 4 tons per hectare, which exhibited a high degree of sustainability. Consequently, the line D7 was introduced as Derakhshan variety due to its high yield, consistency and good fruit quality. Conclusion: The new Derakhshan eggplant (D7 line) was selected, evaluated and introduced by the method of pure line selection (single plant selection) during the years 2006-2018 from Qasri Dezful eggplant landrace. This line has always been selected as one of the top lines under the all experimental designs and conditons such as augment, preliminary, advanced and compatibility and stability

The findings of the previous investigations show that the best density to achieve high yields with most of the beans (Phaseolus vulgaris L. ), including the local Khomein cultivar, stands roughly at 40 plants m2 (Mehrpooyan et al., 2010). There is no comprehensive information available on bean yield performance under drip tape irrigation. Common bean is widely cultivated in Chaharmahal and Bakhtiari province, however, given its high water consumption and due to drought spells in the region in recent years, its production has sharply declined. While common bean requires 7000 to 8000 m3 of water per hectare during the growing season (Alizadeh, 2003), farmers use more than 15000 m3 of water per hectare for beans throughout the growing season. The use of drip tape irrigation can reduce water consumption in beans. The use of this irrigation method requires changing the planting method and proper arrangement of cropping systems. The objective of the present study was to determine optimum plant arrangement in common bean varieties under drip tape irrigation conditions. Materials and Methods: In this study, a factorial experiment was conducted in a randomized complete block design with three replications in spring and summer of 2016 and 2017 at Chahartakhte Research Station in Shahrekord region. The first factor was cultivar (Koosha chitti bean, Yaghut red bean and Dorsa white bean), and the second factor was the planting arrangement (row spacing of 75 cm with 2, 3 and 4 planting lines per row, and the row spacing of 60 cm with 2 planting lines on each row). Different traits at vegetative and reproductive stages of bean plants were recorded and at the end of the growing season, yield and yield components of the cultivars and water productivity were determined. The experimental data were analyzed by using SAS statistical program and the means were compared by Tukey test (p<0. 05). Results and Discussion: The combined analysis of variance showed that plant height, number of seeds per pod, number of pods per plant, 100 seed weight, grain yield and water productivity were affected by bean cultivars and planting arrangement. The interaction effect of cultivar and planting arrangement was significant on 100 seed weight, grain yield and water productivity. The grain yield components were significantly different among different cultivars. The highest number of pods, seeds per pod, 100-seed weight and grain yield were respectively recorded with Yaghut red bean, Koosha chitti bean, Koosha chitti bean, and Koosha chitti bean. The traits such as number of pods and weight of 100 seeds are controlled and affected by genetic and nongenetic factors such as environment. The number of seeds per pod is the most stable trait of beans and is mostly influenced by genotype (Salehi, 2015). The cultivars studied in this experiment exhibited differences in p lant height, grain yield components, grain yield, and water use efficiency. Among crops, bean has the highest diversity in growth habit, seed size and maturity. There are a wide variety of genetic variations in bean pool genus. Therefore, due to genetic differences, under the same climatic conditions, the occurrence of different phenotypes (grain yield, number of pods per plant, 100 seed weight, etc. ) is inevitable, and the difference between them is the result of genetic differences and their different response to the environment. Drip tape irrigation produced the highest water use efficiency when three or four lines of beans were planted on a 75 cm row, while plant density was constant for all treatments. The highest water use efficiency was obtained from Koosha chitti bean, which can be explained by the highest grain yield. Conclusion: The highest grain yield and water productivity were obtained from Koosha chitti bean cultivar. Although the four lines per row arrangement on the 75 cm row gave the highest seed yield and water productivity, it did not differ significantly with the three lines per row on the 75 cm row. Therefore, if the goal is to reduce water consumption and increase water productivity, planting three or four lines per row can be considered on 75 cm row, but because of the ease of planting three lines per row on 75 cm row, it can be recommended to farmers.

Fenugreek (Trigonella foenum-graecum L. ) is an annual plant of the legume family that originates in Iran and is used as a medicinal plant. Fenugreek seeds contain alkaloids called trigonilins, mucilaginous compounds, proteins and oils (Omidbeigi, 2011). This plant has many pharmaceultical applications such as soothing effects, alleviating skin irritation, revitalizing, regeneration of lost body parts, and treatment of pediatric bone tuberculosis and anorexa. One of the important factors in achieving maximum yields in medicinal plants is the choice of planting date and the supply of optimum plant nutrition. Selecting a desirable planting date in any crop can provide conditions for better use of time, light, temperature, rainfall and other factors (Sadeghi et al., 2015). Also, determination of level of intake to meet the plant nutrient requirements, especially nitrogen and phosphorus can result in optimum growth and proper yield, preventing the use of chemical fertilizers and mitigating their harmful environmental impacts (Srivastava et al., 2015). Materials and Methods: In order to study the effect of planting date and nitrogen and phosphorus rates on morphological traits, yield and yield components of fenugreek, a split-split-plot experiment based on randomized complete block design with three replications was conducted in Darmian, Iran in 2016. In this research, the main plots were planting date (30 March and 30 April), the sub-plots were nitrogen rates (0, 70 and 140 kg N ha-1) and the sub-sub-plots were phosphorus rates (0, 60 and 120 kg P2O5 ha-1). In this research, the traits such as plant height, number of main branches per plant, pod length, chlorophyll index, number of pods per square meter, number of seeds per pod, 1000 seed weight, grain yield, biological yield and harvest index were measured. For data analysis, MSTATC software was used. The comparison of the means was done using Duncan’ s multiple range test at 5% probability level. Results and Discussion: The results showed that delay in planting caused a decrease in pod length (8. 31%), chlorophyll index (7. 02%), 1000-grain weight (26. 1%) and grain yield (35. 47%). The grain yield reduction was due to the delayed planting, decreased harvest index, pod length and 1000-grain weight. Increasing nitrogen consumption increased all the studied traits (except plant height). So that increase in nitrogen consumption from zero to 140 kg. ha-1 increased grain yield by 50. 51%. With increasing nitrogen, yield components such as number of pods per square meter, number of seeds per pod and 1000-grain weight increased and eventually raised the grain yield. Also, increasing rates of phosphorus enchanced the chlorophyll index, number of pods per square meter, number of seeds per pod, 1000-grain weight, grain yield and harvest index. Increasing phosphorous consumption from zero to 120 kg. ha-1 raised grain yield by 24. 24% of. With an increase in phosphorus rates, the plant yield components including number of pods per square meter, number of seeds per pod and thousand seed weight increased, which eventually contributed to increased grain yield. The interaction between sowing date and nitrogen was significant on number of pods per plant and 1000-seed weight. Means comparison for the triple interaction of planting date, nitrogen and phosphorus showed that the treatment of planting date of April 10 together with the application of 140 kg N. ha-1 and 120 kg P2O5. . ha-1 gave the highest grain yield (2024. 1 kg. ha-1). It seems that in the absence of nitrogen application, unlike the first planting date, at the second planting date, due to the shortened plant growth period and insufficient opportunity to absorb phosphorus, the use of phosphorus did not lead to a significant increase in the grain yield of fenugreek. Also, the application of phosphorus (140 kg N. ha-1) in the first sowing date caused the highest increase in grain yield of fenugreek, but the application of phosphorus (140 kg N. ha-1) in the second sowing date had no significant effect on increasing grain yield. Conclusion: Based on the results of this study, in order to achieve maximum grain yield in fenugreek in Darmian area, the sowing date of April 10 and the application of 140 kg. ha-1 nitrogen and 120 kg. ha-1 phosphorus are recommended.

Garlic (Allium sativum L. ) belongs to the Liliaceae family and has more than 800 species around the world (Fritsch et al., 2010). This plant after onion is the second amost consumed alium genus, which has high nutritional value due to its minerals. Asexual propagation of garlic during the centuries may have resulted in a genetic restriction. However, the study of ecotypes shows that phenotypic variation is significant in size, color, leaf length, growth habits and agronomic traits such as stress and drought tolerance. Iran was one of the most important exporting countries of garlic in the world in the past, which makes the study of ecotypes to meet the demands of domestic markets as well as the export of this product a necessity. Due to the fact that diverse garlic ecotypes are grown in the south of Kerman province, incompatibility among some of the ecotypes has caused a lot of problems to the farmers of the region. On the other hand, since different planting dates (from September to December) are used in the region to cultiave garlic, de terming the best ecotypes and planting dates is of a great importance to the farmers of the region, which can lead to achieving higher yields. Material and Methods: In order to determine the best ecotypes and planting dates, as well as to estimate the genetic diversity and heritability of traits, an experiment was carried out for two years at the Agricultural Research Center of Kerman Province. The experiment was a factorial based on randomized complete blocks design with three replications. Five planting dates and six garlic ecotypes were included as the experimental factors. The traits including flowering percentage, number of coating layers, number of cloves, clove weight, onion weight, onion diameter; dry matter content and yield were measured during the growing season. The analysis of variance and mean comparison were carried out using SAS software. Correlation matrix and cluster analysis based on Ward’ s method were conducted using SPSS software. Finally, the ranking of the ecotypes based on the all measured traits was done by the method of Arunachalam and Bandyopadhyay (1984). Results and Discussion: The results of compound analysis indicated that different planting dates differed in terms of most of the traits studied including dry matter and number of coating layers. Moreover, it was determined that the effect of ecotype on all the traits was significant, so that the ecotypes of Mazandaran and Guilan gave the highest yield. Sandhu et al. (2015) reported a significant difference between ecotypes in terms of agronomic traits. Our study found that the percentage of flowering, number of clove, clove weight, onion weight and yield were affected by the interaction of planting date and ecotype so that the highest yield was achieved with Jiroft and Shahdad ecotypes at the planting date of September 15. Among the ecotypes studied in this experiment, Gilan and Mazandaran ecotypes produced zero flower. Flowering is a genetic trait, which varies among ecotypes. A desirable characteristic of garlic ecotypes for the south of Iran is non-flowering, which shows the superiority of these ecotypes relative to the ecotypes of Gilan and Ma zandaran, though the ecotypes of Gilan and Mazandaran were superior in terms of yield. High broad-sense heritability, high genetic and phenotypic coefficients of variation for flowering percentage, number of cloves, clove weight and onion weight were observed in this study, indicating that these traits are more influenced by genetics and the probability that they would be passed to the next generation while preserving their quality is higher. The cluster analysis divided the ecotypes into three groups. This indicates the genetic similartiy of each group ecotype. Conclusion Ultimately, the ranking based on Arunachalam and Bandyopadhyay method showed that the most suitable ecotype among the studied ecotypes was Jiroft ecotype. Therefore, Jiroft ecotype is recommended to be grown in this area in September.

Plant Protection Organization (PPO) has registered sixteen commercial herbicides formulations for weed control of corn in Iran (Nourbakhsh, 2016). Among these herbicides, eight herbicides contain one active ingredient and the other seven have two or three active ingredients including acetolactate synthase (ALS) enzyme inhibiting groups – auxin-analogue groups, photosynthetic inhibitors of photosystem II and inhibitors of fatty acids and cell division, which are sometimes formulated with safeners. Previous studies show that the existing weed species do not similarly respond to herbicides and therefore the percentage control of some of the weed species is lower than the other species (Hadizadeh, 2016). These hard-to control weeds are naturally resistant to herbicides. Thus, new herbicides with several active ingredients are suggested to be used to suppress such weeds. The aim of this work was to find the best chemical treatments against weeds in corn production based on using new herbicides thiencarbazone+isoxaflutol+cyprosulfamide and comparing their efficacy with the common registered herbicides in the major corn growing areas of Iran. Materials and Methods: A field study was conducted in four regions of Iran, including Mashhad, Karaj, Shiraz and Kermanshah during the 2017 growing season. The statistical layout was a completely randomized block design with four replicates. The seven chemical treatments were mesotrione+ s-metalachlor+ terbuthylazine (Lumax® 537. 5SE pre-emergence, 4 l ha-1 or post-emergence, 4. 5 l ha-1), foramsulfuron+ iodosulfuron +thiencarbazone (MaisTer Power® 4. 25%OD, 1 l ha-1), topramezone (Clio® 29. 7%SC, 150 ml ha-1) and the new herbicide thiencarbazone+isoxaflutol+ cyprosulfamide with three recommended doses (Adengo 46. 5%Sc, 330, 440 and 550 ml ha-1). A hand-weeded treatment and an unweeded treatment served as controls. Weed density and weed dry weight for each plot were measured four weeks after the last application the herbicides. Corn was harvested from 10 m2 of each plot after removing border plots. Corn grain yield was determined after adjusting the moisture level of grain to 14 %. To measure corn biological yield, the samples of 10 corn plants were taken and then were dried in an oven. Data from each region were subjected to statistical analysis using SAS/STAT statistical software and the means were separated by least significant difference (LSD) test (α =5%). Results and Discussion: The results showed a diverse spectrum of weeds (17 species) at the experimental locations. Pigweed species (Amaranthus retroflexus and A. blitoides) were dominant in the all tested locations. The next dominant weed species were Portulaca oleraceae L., Echinochloa crus-galli (L. ) P. Beauv., Convolvulus arvensis L., Chenopodium album L., Sorghum halepense (L. ) Pers., Physalis divaricate L., Glycyrrhiza glabra L., and Setaria viridis L. Across the experimental locations, thiencarbazone+isoxaflutol+cyprosulfamide was efficient at 440 and 550 ml ha-1 concentrations for weed control (75 to 88%). However, when applied at dosage of 330 ml ha-1, its weed control efficiency was lower (30 to 50%). Topramezone was inefficient in controlling weeds in all the locations, which was in agreement with the findings of some previous studies (Hadizadeh et al., 2015). Foramsulfuron+ Iodosulfuron+Thiencarbazone (1l ha-1) was efficient in weed control (70-85%) in Mashhad and Karaj. All the herbicides (except topramezone) effectively controlled P. divaricate as an invasive weed. E. crus-galli and G. glabra were identified as difficult-tocontrol weeds. None of the herbicides showed injury symptoms on corn. Conclusion: Thiencarbazone+isoxaflutol (440 and 550 ml ha-1) showed 70-85 weed control efficiency averaged in the all experimental locations and it could be recommended to be used in corn field after registration process. However, due to the environmental concerns, it should be applied at low doses. Foramsulfuron+ idosulfuron+ thiencarbazone was found to be the next efficient herbicide. Barnyard grass and licorice were difficult-to-control weed species or there were not controlled by new herbicides. We also suggest the evaluation of the herbicides for their residual effects on the succeeding crops. Acknowledgements: We wish to thank Professor Eskandar Zand, Dr. Mehdi Minbashi, Dr. Saeed Khavari and Mr. Yahya Javid-Shafiee for their very useful contribution to this project.

Monitoring the growth stages and yield of crops in agricultural areas is essential for food security and farmers’ income forecasts. Progress in remote sensing has greatly contributed to the process of monitoring of various developmental stages of agricultural crops and the evaluation of their yield (Anastasiou et al., 2018; Shi & Mo, 2011). Remote sensing (RS) and global positioning systems (GPS) can be used to evaluate the changesin crop dynamics, including its yield and spatial diversity (Dadhwall & Ray, 2000). Spectral vegetation indices (SVIs) are a combination of the spectral absorption and spatial distribution of plants in different electromagnetic spectral range and are used to measure the characteristics of a product. SVI provides a simple method for measuring spectral responses of plants throughout the season, which uses fundamental differences between soil and plants, and often as a kind of relationship is expressed between the energy of electromagnetism reflected in red and infrared wavelengths the red near (NIR). Green healthy plants exhibit relatively low reflections in the visible range of the electromagnetic spec-trum (high absorption of light for photosynthesis); however, its reflection is usually high in the near infrared region (Al-gaadiet al., 2016). Therefore, in this study, the remote sensing method spectrometric data were used to predict the yield of corn in the Moghan plant in northern Ardebil province. Materials and Methods: Landsat-8 satellite images were prepared during four growth stages of corn, and simultaneously at the dateswhen the satellite images of the study area were taken, spectroscopy of the plant samples was performed using the Field Espect-3 spectrometer. In this study, 30 corn fields were selected in the Moghan Plain to estimate the yield of corn. First, using the GPS device, the position of the farms was determined. Then, at different growth stages e. g. four-leaf stage, growth differentiation stage, flower emergence stage and physiological maturity, soil and plant samples were prepared according to standard methods and then the specimens were measured. Vegetation indices of NDVI, SAVI, MNDVI and OSAVI were calculated based on satellite data and laboratory spectrometers. Results and Discussion: The results in both cases-the use of Landsat 8 satellite images and laboratory spectrometer at flower emergence stage-showed that the correlations for coefficient of determinationfor leaf area index and yield were from 54% to 72%, which were more robust as compared to other growth stages. On the other hand, the evaluation of the indices obtained from the spectrophotometric results and the use of spectral data and the comparison between the two showed that the correlation for coefficient of determination for NDVI and SAVI was 70%, which were determined as effective indices for estimating leaf area index and yield using satellite imagery. While MNDVI and OSAVI indices were 72% and 69%, respectively, they were found to be the most suitable indicators for estimating leaf area index and yield based on the results of laboratory spectroscopy. Therefore, using satellite images, these indices are more likely to be present, while for MNDVI and OSAVI indices, particular wavelengths are studied, and given the fact that the laboratory spectrometer shows the slightest variations in each wavelength, these indicators can also be considered as robust. Conclusion: The results of the study showed that among the growth stages of the plant, flower emergence stage was the best for predicting the yield of the crop, and on the other hand, NDVI and SAVI indices resulting from Landsat 8’ s satellite imagery were found to be the most robust in predicting crop yield and MNDVI and OSAVI indices were found to be the best predictors of crop yield based on the results of spectral laboratory data.