Estimation of OPTIMUM fertilizer rates is needed because of growing economic and environmental concerns. OPTIMUM fertilizer rates can be determined by fitting statistical models to yield data collected from N fertilizer experiments. The main goal of this research was to compare and evaluate quadratic, square root, Mitscherlich, rectangular hyperbola, linear plus plateau and quadratic plus plateau models for describing the response of sugar beet to N fertilizer. Data used were obtained from a furrow irrigation system experiment with five N fertilizer rates: zero (control), 60, 120, 180, and 240 N kgha-1 with three replications in Ekbatan Research Station, Hamedan, Iran, during 2003 and 2004. Economic OPTIMUM N fertilizer rates were obtained based on fertilizer and sugar beet price during 2003 and 2004. Economic, OPTIMUM N fertilizer rates varied depending on the fertilizer to crop price ratio and models used. Results of this research showed the quadratic model described the yield responses and economic, OPTIMUM N fertilizer rate in sugar beet cultivation better than the other models. Economic, OPTIMUM N fertilizer rates due to this model were 235.8 and 248.9 kgha-1 in 2001 and 2002, respectively. Economic OPTIMUM N fertilizer rates based on N fertilizer subsidy and non-subsidy prices were 234.7 and 225.1 kgha-1 for 2003 model, and 247.9 and 240.8 kgha-1 for 2004 model, respectively.

ABSTRACT Today, climate change and its obvious negative effects on ecosystems have caused concern. This research seeks to test whether vegetation changes are sensitive to climate shocks and also how the ecosystem recovery process is through this index. In this regard, by using the GEE platform, Java coding, GIS and statistical analysis, vegetation and Palmer indices were calculated and based on time series climate data, vegetation and climate changes were presented. The results of Palmer's drought index show that during the statistical period (1985-2020) the study area is facing drought or is moving towards drought. Also, the results indicate the longest period of drought in the region from 2013 to 2020. Totaly from 420 evaluated months, the NDVI index is below the change threshold in 70 months. Among these, 31 months of the study period is below the acceptable threshold in green and non-reservoir seasons, which is ecologically worrying. The distribution of the vegetation index based on hexagons in 1985 and 2005 had a normal and almost normal distribution; But in 2020, the graph deviated from the normal state and skewed towards the vegetation cover index under stress or even thin covers. According to the analysis of the indicators, it is predicted that the Gorgan region is on the border of such ecological developments and the historical ecosystem of the region is moving towards new ecosystems or being in a new equilibrium state with climatic conditions and human disturbances Extended Abstract Introduction Today, climate change and its obvious negative effects on terrestrial ecosystems have caused great concern to humans. These changes are effective on vegetation performance, plant distribution patterns, and have economic and environmental consequences. Therefore, it is important to know the behavioral pattern of vegetation changes against climate changes. Reviewing the studies of scientists in the world shows many researchers have used the NDVI index to study temporal and spatial changes in vegetation and its relationship with the climatic index of precipitation in different parts of the world. Studies have shown that NDVI follows precipitation with different time scales. Surveys showed that there are very few studies on determining the threshold of changes in the vegetation cover index in the face of climate shocks. Determining these thresholds can provide a suitable solution for evaluating the state of the ecosystem, the consequences of climate shocks and the reversibility or disturbance in the ecosystem. This study was conducted with the aim of improving our understanding of the dynamics of vegetation in the forest city of Gorgan during 1985-2020 against climatic stresses.   Methodology The current research is a comparative and monitoring research and seeks to test whether changes in vegetation cover are sensitive to climate shocks and also how the ecosystem recovery process is through this index. To achieve the gole, first, NDVI index was selected among the optimal vegetation indices and its calculation process was done as a time series in the GEE system. In parallel with those climate shocks, the main elements including temperature, precipitation and storm were calculated during the historical process of 35 years and the average and standard deviation statistical indicators were calculated for them and the trend of changes in the thresholds was determined. The results of climate plots and climate changes show that in the years before 1985, 2005 and 2020, drastic changes have occurred in climatic elements and climatic factors. Therefore, these years can be considered as the periods when the climate shock happened.. Next, the region was divided into 436 hexagons and the NDVI index for each of the hexagons was calculated and modeled for the years 1985, 2005 and 2020 as selected years affected by climate shocks. In conclusion, to analyze the trend of changes in the time series of the vegetation index and compare the behavior of its changes with climatic indices, the Palmer index was calculated.   Results and discussion The results of climate change monitoring based on the Palmer index showed that during the statistical period the study area is facing drought in most years. The most severe climatic fluctuations and drought in the region were recorded in 2018 and in the months of October to December. The longest period of drought has also prevailed in the region from 2013 to 2020. During this period, rainfall, temperature and storm fluctuations have the most changes. The results of drought monitoring show that in 270 months, the region is facing climatic drought stress, 57 months of the study period, the region is facing severe and very severe drought stress. The results of the time series of the NDVI vegetation index showed that, out of the 420 evaluated months, 70 months of the year the NDVI index is below the change threshold, 31 of which are in the green and non-accumulating seasons, the seasons when the vegetation is expected to be at its maximum. Placing below the acceptable range means crossing the ecological thresholds and challenges the recovery and restoration of the ecosystem, also the ecological performance will be affected at this point. Based on the assessment of the Palmer index, from 2014 to 2019, the situation of the Palmer index is in the extreme drought range. Also, since 2015, i.e. with a one-year time delay, NDVI index has experienced the lower limit of the equilibrium threshold of vegetation cover. These conditions are also valid for the years 2008, 2009, 2002 and 1997. In general, it can be said that the vegetation cover index is dependent on climatic changes and fluctuations and shows high sensitivity to changes. The important point in this section is that in the years when the NDVI index changes are at the lower limit of the threshold, we witness the most climate shocks and temperature changes, the occurrence of severe storms and precipitation fluctuations. The distribution of the vegetation index based on hexagons in 1985 and 2005 have a normal distribution; but in 2020, the graph has deviated from the normal state and skewed towards the vegetation cover index under stress or even thin covers. The visual interpretation done on the vegetation cover index in 1985 confirms the condition of the vegetation cover in the southern and western limits of the region in a state with suitable dense and pasture vegetation and forest cover on the edges. However, in 2005 and 2020, this cover has been changed and mainly turned into agricultural land and poor rangeland. In such a way that in 2020, the situation of the region has revealed the critical state of vegetation. The vegetation cover index in the central areas of the city has also reached from a relatively favorable situation in 1985 to a critical situation with almost no dense and stress-free vegetation cover in 2020. The results of the present studies are consistent with the studies of Visentr Serrano et al. in 2013 and confirm the relationship between NDVI vegetation and climate change. In addition, the results of the studies are consistent with the studies of Alwesabi 2012, Xiai & Moody, 2005 and Yan et al. 2001. In such a way that the present study and the aforementioned studies all confirm the influence of the vegetation index on climate fluctuations and precipitation with a one-year time difference.       Conclusion In general, the threshold is defined as a border with different conditions. After crossing the thresholds, the stability and positioning of the NDVI in the equilibrium range is often difficult, and the ecosystem is constantly spending energy to restore itself or to position itself in a new stability state. The result of the mentioned disorders is the reduction of resilience and resistance in the region, which leads the ecosystem to alternative states or crossing the threshold or being in a new equilibrium state. The results showed that the areas where green vegetation is concentrated and denser are less affected by climatic stresses and show more resilience. However, the areas that have become spots and islands due to destruction in the urban areas are more affected by climatic stress and destruction and show less tolerance against the destruction factors. The results help managers to focus their management plans for the preservation and maintenance of urban green spaces as well as forest and pasture ecotones on the edge of the city by knowing the thresholds.   Funding There is no funding support.   Authors’ Contribution Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.   Conflict of Interest Authors declared no conflict of interest.   Acknowledgments  We are grateful to all the scientific consultants of this paper.

The objective of this study was to determine the allowed and desired limits for heavy soils of texture (clay loom), as it has operational capability (friability), These limits were 6.34 mm for planting and 10.62 mm for harvesting in each raining or irrigation episode. We determined some factors that affect soil wetness and water content as follow: the amount and severity of rain, the condition of soil’s drainage, the percent of air moisture, evapotranspiration, the amount of runoff, the amount and severity of sunlight, the ambient temperature, the condition of vegetation and, the soil texture. The time needed for dryness and removal of soil moisture as evapotranspiration in each over- desired and allowed capacity rains are 5-7 days. Also, because of higher evaporation in planting time (late April and early May) than in harvesting time (November), and also higher surface temperature in spring, both result in moving the vapor from deeper layers of soil to surface. Therefore, as our result showed, the time needed for readiness of soil for machinery operation at time of planting are 5 days for planting (late April and early May) and 7 days for harvesting time (November). According to our calculation, 19.5% of rains at planting time and 7.5% at harvest time changed to run- off; and with taking this amount of run- off in account at allowed- limit calculation, and also because of texture of the studied soil, the maximum allowed rain in which the soil remains in proper condition for machinery planting and harvesting activities exceeded 7.6 and 11.41 mm in each rainy day. As a result, according to limiting factor of well doing of operations and also factors affecting these restricting factors, the number of working days for mechanized planting operation was found to be about 19.69 days and also 21.98 days for harvesting operations in farms with heavy soil with 98% of probability.

According to this reality that iron bulks because of having ferromagnetic minerals, they have high magnetic intensity, in mining explorations most usual geophysical method suggested to explore these resources is magnetic method. Basically in order to process and interpretation of magnetic anomaly maps several methods be used of which most of these methods are based on try and error. One of usual geophysical data refining or filtration methods is upward continuation which will be applied in this study. Upward continuation can be used to separate a regional and local magnetic anomaly from the observed magnetic. One of problems that we encounter it through this filtration is determining OPTIMUM HEIGHT of upward continuation. We use a practical method to derive an OPTIMUM HEIGHT for upward continuation. In this study magnetic data of northern anomaly of Mansoorabad region of Yazd was investigated. According to past studies in order to handle geophysical investigations for carry out magnetic investigation a region of 450x700 square meters were adapted. Data acquisitions of magnetic data in exploration grid were done via 10 meter distance for both profiles and measuring stations. Outcrops of iron in the form of hematite in Ooliti'c's limestone rocks are evident. In order to separation of regional anomaly the usual upward continuation were used firstly. Using this method a map of 35 meter HEIGHT were detected as regional anomaly. In the following in order to more accurate interpertation and process and also DETERMINATION of HEIGHT of upward continuation filter, one of practical methods of which is based on cross correlation of two successive HEIGHTs were used. With the aid of this method without any comparison of several maps related to various HEIGHTs and without any interference of a body one can obtain suitable upward continuation filter to determine regional magnetic anomaly and consequently by subtracting this magnitudes from observed overall anomaly one can estimate map of remained anomaly that could be a better evident of local anomaly in that region. Cross correlation for upward continuation of HEIGHTs from 30 meters to 40 meters by the distance of 2 meters were calculated in which the HEIGHT of 39 meters were selected as OPTIMUM HEIGHT of investigated data. The map of upward continuation which was calculated by this HEIGHT for magnetic data of Mansoorabad region showed the best fitting with regional anomaly of data based on used method. Also the map of remained data will be obtained according to this HEIGHT. In terms of geology mineralization of iron that was formed in this region is sedimentary iron type of Oolitic which were created in the time limit of Paleozoic age. Considering location of determined anomaly and geology map of region, observed that this kind of mineralization of iron in limestones by the pattern of Oolitic were created. After investigation and coincidence of magnetic anomaly in studying area, it is determined that the iron bulks were the reason of anomaly. Depth continuations of this kind of anomalies are different and are continued to the depth of 80 meters.

In the present paper OPTIMUM HEIGHT of skirt of Skirt Pontoon Floating Breakwater are reported by physical model. 54 tests on 3 types (skirt HEIGHTs : 8,16 and 24 cm) of skirt pontoon floating breakwater is conducted in the wave flume of Soil Conservative and Watershed Research Center. Hydrodynamical and geometrical parameters were analysised. In this research OPTIMUM HEIGHT of skirt to water depth ratio is determined.

HEIGHT measurement is an important part of nutritional assessment especially in children. However, in such cases as hospitalized or certain kinds of malformations or disabilities, HEIGHT cannot be measured accurately. We aimed to determine appropriate HEIGHT predictors in Iranian healthy children for further use in disabled and/or hospitalized children. A total of 730 apparently healthy children aged 7-11 years old from both sexes from Tehran, Meshed and Rasht were enrolled in a cross sectional study. HEIGHT, demispan (DS), halfspan (HS), arm length (AL) and tibia length (TL) were all measured using a measuring tape. Linear regression models were established between HEIGHT, DS, HS, AL and TL. For boys AL (R2=0.783) and TL (R2=0.837) and for girls AL (R2=0.720), TL (R2=0.765), HS (R2=0.771) and age (R2=0.775), respectively, entered the linear regression model. When HEIGHT predictors were evaluated individually for each city, only in Tehran DS also entered the regression model. Concordance of different percentiles of HEIGHT estimates based on AL with those of actual HEIGHT proposed this measure as a reliable HEIGHT proxy for this age group in clinical as well as field practice.

Producing food colors from natural sources, such as tomatoes, which could be used instead of synthetic colors, is important in relation to health and safety aspects of the consumers. In this research, solvent extracting was carried out by using three non-polar solvents, including petrolium ether (bp=55oC), n-hexane (bp=60oC) and a mixture of n-hexane: ethanol: aceton (1:1:2, bp=50oC). Also, two different temperatures (room temperature and boiling point of the solvent) and three different periods of time (2, 4 and 6 hours) of extraction were tried. Using mixture of the solvents (at boiling point) for six hours showed to be the OPTIMUM conditions for extraction and there were significant differences between this treatment and other conditions for extractions. In addition to the above results, the same volumes of the solvent and samples were found to be the best ratio in comparison with the other volumes ratios. It was significant at P £.05.. The yield of color extraction from tomatoes and tomato powder was 0.14 and 0.24% (w/w), respectively. Also, the purity of the extracted color was 82.65% lycopen. The extracted color showed a good stability in sunflower oil for three months at 4oC.