In order to study the effect of Mycorrhiza and PSEUDMONAS on yield and yield Components of Sun flower at Various Level of phosphorus, a field experiment was conducted in research field of Islamic Azad university, Takestan branch in 2010.A Factorial in a randomized complete block design (RCBD) with four replications was used inoculation of mycorrhiza (with and without inoculation) and PSEUDMONAS (with and without inoculation) with three levels of phosphorus (0, 50, 100 kg/ha). The obtained results showed that increasing of phosphorus and inoculation of micorrhiza increased plant dry weight and yield (656.75 g, 4300 Kg/ha and 555.52 g, 4283 Kg/ha), stalk height and the weight of 100 grain had significant increasing too. The use of PSEUDMONAS increased dry weight of plant, but it did not have any significant effect on other traits. Interaction effect of phosphorus and Mycorrhiza had statistical significant difference but it did not have any significant difference on height of stalk, the 100 grain weight and dry weight of plant. Triple Interaction effect of phosphorus, Mycorrhiza and PSEUDMONAS was only significant on dry weight of plant (908.77 g), consequently micorrhiza and 100 kg/ha phosphorus application in considering had increasing effect on more traits and can introduce as successful treatment.

In order to investigate the possibility of quinoa producing in Garmsar, Iran, a factorial experiment conducted in randomized complete block design with three replications in 2018-2019 growing season at Garmsar Agricultural Research Station. The factors were planting date at three levels (March 6th, April 1st and April 6th) and the three genotypes of quinoa (Q26, Q29 and Titicaca). Results showed that the effect of planting date was significant for all studied traits except the harvest index. Also, all studied traits were significantly different in all genotypes. Titicaca planted on March 6th had the highest yield (2276 kg.ha-1).The grain yield and yield components decreased with the delaying the planting date. Compared to early plantings, Latest date, April 6th, led to reduction of all traits, especially grain yield (about 50%). The results of simple phenotypic correlation between the studied traits showed that grain yield per hectare had the highest correlation with plant yield (0.877) and then with leaf area index (0.832), panicle weight (0.815) and number of branches per plant (0.745) that was significant at the 1% probability level.

Identifying the constraining factors of production and yield gap is very important. Therefore; this research was performed to identify the production constraining factors of local rice cultivars. All management practices from nursery preparation to harvesting stages for 100 paddy fields of local rice cultivars were recorded through field studies, in Sari, from 2015-2016. In the CPA, the actual and calculated potential yield were 4495 and 5703 kg/ha, respectively and the gap was 1221 kg/ha. The yield gap caused by number of top-dressing variables was 324 kg/ha, equal to 27% of the total yield gap. The yield gap related to previous year of legumes cultivation was 218 kg ha-1, equal to 18% of the total yield variation. Among the 10 variables entered in the CPA model, the effects of top-dress fertilizer application and its application frequency and foliar application were remarkable, which could compensate a significant part of the yield gap (444 kg/ha, 37% of total) in the farmers’ fields by managing these variables. According to boundary line analysis (BLA) finding, actual yield mean on the basis of optimal limit related to 12 variables under study was 5369 kg/ha, with 881 kg/ha yield gap . Mean relative yield and relative yield gap for 12 variables (transplanting date, seedling age, number of seedlings per hill, planting density, nitrogen and phosphorous per hectare, nitrogen before transplanting, harvesting date, lodging problem, pest problem, diseases problem and weeds problem) were 83.64 and 16.35 kg/ha, respectively. Based on the finding, it can be stated that the model precision is appropriate and can be applied for both estimation of the quantity of yield gap and determining the portion of each restricting yield variables.

In recent decades, drastic land use changes in Golestan province caused to reduce a substantial amount of Hyrcanian forest. To investigate the changes, land cover maps produced using Landsat satellite imagery classification of sensors TM from 1984, 2012 and 2016 respectively used as input data in Land Change Modeler (LCM) to predict land cover changes in 2030. In order to assess the accuracy of modeling, statistics of relative performance characteristic (ROC), ratio Hits/False Alarms and figure of merit was used. In continue to investigate the role of land use changes in water yield as one of ecosystem services was discussed. The results show the accuracy of artificial neural network with the ROC equal to 0. 949, the ratio Hits/False Alarms equal to 57 percent and the figure of merit is equal to 11 percent. Land use change modeling results showed that from 1984 to 2012, The most prominent changes were related to reduction of forest cover. This process modeling using artificial neural network showed, from 2016 to 2030 forest cover will be reduced about 30361 hectares. The results of water yield study showed that runoff in the area, particularly in the East and North East area has increased. This increase in the amount of runoff occurred as a result of land use change on forest ecosystems to agriculture. Results of this study improve our understanding of hydrological consequences of land-use changes, and provide needed knowledge for effectively developing and managing land-use for sustainability and productivity in the Gorgan-rood watershed.

To assesse the iron and silicon effects on the yield and physiological characteristics of green pea, Wando cultivar by ASGrow Corporation was used in three levels of iron chelate (0.05, 0.1 and 0.3 gr per l-1) and silicon (0, 14 and 28 mg per l-1), as a factorial experimental in completely randomized design with three replications. In this experiment, characterisics such as fresh and dry weight of grain, the number of grain per pod, concentration of Fe, Cu, Mn, Zn and Si in leaf and grain were measured. Results showed that the interaction of Fe and Si was significant at p<0.01 on grain fresh and dry wigeht, concentratin of leaf and grain Fe, leaf Mn, leaf and grain Zn and leaf Si and the application of Fe and Si was significant separately, on other traits such as number of grain per pod, concentration of leaf and grain Cu, Mn and Si in grain.  The Mean squares showed that the application of Fe and Si significantly increased fresh and dry grain weight and Si laef concetration and decreased the concentratin of leaf and grain Fe and Mn as well as grain Mn.  The enhancement of Fe and Si application separately decreased the concentration of Mn, Cu and zinc leaf and grains, but the Si concentration of leaf and grain were increased by Si application. The concentration of Fe, Mn, Cu and Zn were decreased in leaf and grain because of antagonistic effects. It can be concluded that Si reduces the harmfull effects of high levels of iron toxicity and the application of 0.1 g/l and 25 mg/l can be recommended as the best treatments.

Recognition and understanding the genetic control of traits, combining ability and genetic structure are directly related to the success of breeding programs. For this purpose, a 7 × 7 one-way diallel design was conducted in a randomized complete block design with three replications. The measured traits were included plant height, height to the first capsule, number of days to 50% and 90% of flowering, number of capsules per plant, number of seeds per capsule, number of days to physiological ripening, number of branches, leaves number and length, 1000-seeds weight, capsule weight, length and width, chlorophyll a, b and total chlorophyll, biological andeconomic yields, harvest index, oil and protein percentage. Analysis of variance showed that there was a significant difference between genotypes and diallel analysis showed that the additive variance of all traits and dominant variance of all traits except height to the first fruit-bearing capsule were significant. The oltan cultivar was the best and Ardestan genotype was the worst genotype in terms of general combining ability. Sabzevar×TS-3 and Sirjan×Fars were the best hybrids in most traits. The general heritability was between 0.90 to 0.96 for biologic yield and number of branches, respectively and narrow heritability was between 0.36 to 0.91 for the number of branches and harvest index, respectively. The analysis of variance by Hayman method confirmed the results of Griffing analysis.

To investigate the effects of water deficit stress and bio and non-bio fertilizers on Thymus Vulgaris, a split plot experiment was conducted based on randomized complete block design with three replications in 2017 in Asgarya agricultural field in Yazd. The treatments included water tension: W1=7 (Control), W2=12 and W3=17 days irrigation intervals as the main factor and bio and non - bio fertilizers at five levels including B1= control (without fertilizer), B2= endo mycorrhiza (Glomus), B3= Azospirillum bacteria, B4= Pseudomonas bacteria and B5= chemical fertilizer (NPK) a sub – factors. Results showed that the highest flowering branches yield, a, b, and total chlorophylls and nitrogen and phosphorus elements were observed in 17 days of irrigation (W3). 12 days of irrigation treatment (W2) showed the highest potassium element rate. The highest a, b and chlorophylls and nitrogen were observed in Azospirillum treatment (B3). The highest total chlorophyll, phosphorus element, carotenoids and flavonoids were observed in Pseudomonas treatment (B4); the highest potassium element rate were obtained in mycorrhiza treatment (B2); the highest flowering branches yield were observed in NPK treatment (B5) and control (B1) treatment resulted in the highest anthocyanin

Lactation length is different in individual cows, which is generally converted to a 305-day standard using curve fitting models for genetic and management practices. Individual curves do not have a standard shape in all cases, and can deviate from the standard pattern according to factors such as individual differences, and type of fitted models. These non-standard curves, called atypical, resulted from incorrect estimated parameters of the curves; which consist of: continuously increasing or decreasing and reversed standards. This study was conducted to investigate the importance of atypical curves in estimation of 305-day milk production, by fitting two nonlinear models? Wood (empirical) and Pollott (biological), on 7659 and 6692 test-day milk yield of 977 and 776 first calving Iranian Simmental and Jersey cows, during 2007-2020, using R software. Different patterns obtained based on the combination of increasing (b) and decreasing (c) phase parameters of curves. The number of standard curves from the Pollott and Wood models were 85.5% and 62.2% for Simmental, and 83.1% and 70.6% for Jersey cows, respectively. Only continuously increasing curves were observed in both breeds in Pollott model (14.8% and 16.9%, Simmental and Jersey cows, respectively); Whereas in Wood model, all 3 groups of atypical curves were observed, which the reversed standard was the most (22.3% and 16.5%, Simmental and Jersey cows, respectively). Based on the findings, at the time of standardizing the production of dairy cows (national evaluations), not only differences between breeds, but also special attention to the production of atypical curves, should be paid (to correct or discard them).

In order to identify the correlations and relationships between different traits in the bread wheat, 30 genotypes were investigated as sub-factors under the split plot experiment in the completely randomized design in greenhouse and the randomized complete block design in the field with three replications under the normal irrigation and post-anthesis water stress conditions. The results of the canonical correlation analysis showed that at both normal and moisture stress levels, there was a significant correlation between the pair of canonical variables obtained from the phenological traits and the yield components. Under the normal conditions in the greenhouse, to increase the spike density and length, the number of days to 50% flowering can be considered as a suitable selection criterion. According to the results of canonical correlation analysis, under the stressed conditions in greenhouse, to increase the spike length, the number of days to the heading, maturity and 50% of flowering were among the important and effective factors. Under the optimum irrigation conditions in the field, the number of days to maturity was considered as one of the factors influencing the seed weight per spike. The results of canonical correlation analysis under the field stress conditions showed that to increase the 1000-seed weight, the number of days to maturity can be considered an appropriate selection criterion.