Distance-based clustering methods categorize samples by optimizing a global criterion, finding ellipsoid clusters with roughly equal sizes. In contrast, DENSITY-based clustering techniques form clusters with arbitrary shapes and sizes by optimizing a local criterion. Most of these methods have several hyper-parameters, and their performance is highly dependent on the hyper-parameter setup. Recently, a Gaussian DENSITY Distance (GDD) approach was proposed to optimize local criteria in terms of distance and DENSITY properties of samples. GDD can find clusters with different shapes and sizes without any free parameters. However, it may fail to discover the appropriate clusters due to the interfering of clustered samples in estimating the DENSITY and distance properties of remaining unclustered samples. Here, we introduce Adaptive GDD (AGDD), which eliminates the inappropriate effect of clustered samples by adaptively updating the parameters during clustering. It is stable and can identify clusters with various shapes, sizes, and densities without adding extra parameters. The distance metrics calculating the dissimilarity between samples can affect the clustering performance. The effect of different distance measurements is also analyzed on the method. The experimental results conducted on several well-known datasets show the effectiveness of the proposed AGDD method compared to the other well-known clustering methods.

An experiment was conducted as a split - split plot in form of a randomized block design with four replications in Cilakhor region of Iran in 2004. The main factor was the seed PLANTING date with three levels (5, 12 and 25 April), sub factor was the crop DENSITY with two levels (160,000 and 250,000 pI/ha) and sub-sub factor was the crop arrangement with two levels (equidistant and non-equidistant). Delaying the PLANTING date caused the increase of biological yield and decrease of harvest index. Increasing the crop DENSITY caused the increase of the number of fertile heads per square meter, biological yield, grain yield, and decrease of the number of fertile tillers, the number of grains per head, dry weight of above-ground organs per hill, yield of each hill (P<0.05) and the plant height, the number of grains per head was decreased.

The normalized water productivity parameter is one of the AquaCrop model’ s input, upon which the crop biomass yield is simulated on a daily basis. The necessitate of this research is that the amount of normalized water productivity for spinach has not been determined so far. This research was carried out at the Abourihan Campus farm of the University of Tehran which is located in Pakdasht. The experiments were performed during cultivation year of 2017-2018 with six PLANTING densities of 12, 16, 17, 22, 25 and 33 plants per square meter and four replications with full irrigation. The biomass yield was measured seven times during the cultivation season. Considering the measured data of biomass and relative transpiration, the normalized water productivity was obtained for five treatments. The highest amount of normalized water productivity (12. 4 g/m 2 ) was related to 25 plants per square meter DENSITY. A relationship function was found using normalized water productivity and PLANTING DENSITY data. This function was tested using the remaining treatment and placing the normalized water productivity in the Aqua Crop model. The mean root square error and the mean bias error between the measured and simulated data were 20. 9 and 6. 6 g/m 2 at the test step. The results of this study showed that the PLANTING DENSITY affects normalized water productivity and it is increased by increasing PLANTING DENSITY (optimum DENSITY) and then it is decreased. Finally, this study suggests that the normalized water productivity regarding to PLANTING DENSITY is entered to the AquaCrop model.

Introduction: Sesame (Sesamum indicum L. ) is considered as the queen of oilseeds for its high oil quality. Sesame oil is rich in micronutrients, antioxidants and essential amino acids as well as polyunsaturated fatty acids. It has been well documented that agronomic practices such as time and rate of PLANTING will have a direct effect on sesame grain yield, oil content and quality. Therefore determining the optimum plant DENSITY is very important in sesame production. Material and Methods: In the current experiment, the effect of different PLANTING densities (20, 40 and 60 Plants per m2) was investigated on agronomic traits of six sesame cultivars (Halil, Dashtestan 2, Darab 1, Oltan, Yellow White and Naz Tak Shakhe). The field experiment was carried out as factorial layout based on randomised complete block design with three replicates in research farm of Seed and Plant Improvement Institute, in 2016. Each experimental plot consisted of four adjacent rows, 5 m in length and 0. 3 m apart. To achieve the above-mentioned PLANTING densities, sesame seeds were sown 16, 8 and 5 cm apart on each row on 6th June. If required, the seedlings were thinned at 2-3 leaf stage. The crop was irrigated according to the conventional schedule for the region. Weeds were manually removed throughout the growing season. At physiological maturity stage, two middle rows of each plot were harvested for determination of yield and yield components. Data analysis was performed using SAS 9. 1 and means were compared by the Least Significant Difference (LSD) test at the 5% probability level. Results and Discussion: The results showed that all measured traits except 1000-seed weight and harvest index significantly affected by PLANTING DENSITY. Also, the interaction between PLANTING DENSITY and cultivar was significant on the number of capsules per plant, seed yield, harvest index and oil concentration. At PLANTING densities of 20 and 40 plants per m2, the maximum grain yield were related to Dashtestan 2 cultivar. At PLANTING densities of 60 plants per m2, Naz Tak Shakhe was found to be the best cultivar regarding grain yield. Although the increase in PLANTING DENSITY from 20 to 40 plants per m2, could increase grain yield in all cultivars, the highest grain yield was related to Naz Tak Shakhe cultivar. Furthermore, increase in PLANTING DENSITY up to 60 plants per m2, caused severe grain yield loss in all cultivars except Naz Tak Shakhe cultivar which showed 18% increase in grain yield. Conclusions: In general, it can be concluded that cultivars characteristics could be considered as essential parameters to determine the optimum PLANTING DENSITY. Therefore, if the plant DENSITY is adjusted in such a way that plants could be able to use the environment and agronomic inputs factors with the minimum intra-specific competition, maximum economic yield will be obtained.

This experiment was conducted, to study the effect of PLANTING time and PLANTING DENSITY on savory (Satureja sahendica Bornm.) in 2012 in Alborz Research Station, Research Institute of Forests and Rangelands, Karaj, Iran. The experiment was carried out in split plot in time in the form of a randomized complete block design with three replicates. The main plots were PLANTING times in two levels (including fall and spring PLANTING) and the sub plots were PLANTING DENSITY in four levels (including 20×20, 40×40, 60×60 and 80×80 cm). The results indicated that PLANTING time significantly affected the number of lateral branches on the main stem, the number of flowering branches, flowering shoot yield and essential oil yield, the number of tillers, plant height, single plant shoot yield and essential oil percentage. The effect of PLANTING DENSITY had also significant differencein all measured traits except the plant height. Mean comparison of PLANTING time showed that in all PLANTING densities, fall PLANTING was better than spring PLANTINGin all traits. Mean comparison of PLANTING densities indicated that the highest number of tillers (7.67), the number of flowering stems (6.5), single plant shoot yield (22.98 g/plant) and essential oil percentage (2.01%) were achieved in the lowest PLANTING DENSITY (80×80 cm). However, the highest number of lateral branches (5.67), flowering shoot yield (1587.5 kg/ha) and essential oil yield (14.53 kg/ha) were achieved in the highest PLANTING DENSITY (20×20 cm). The interaction of PLANTING time × PLANTING DENSITY significantly affected all measured traits except for the number of tillers and the number of flowering branches.The results of this experiment indicated that selection of suitable PLANTING time and PLANTING DENSITY is important to obtain high essential oil yield; fall PLANTING × the highest DENSITY (20×20 cm) could produced an acceptable yield in Karaj climatic conditions.

To evaluate the effect of seed priming on plant establishment and to determine the optimum PLANTING date and plant DENSITY of silage corn, SC 704, in summer late PLANTING, an experiment was carried out as split-split plot based on randomized complete block design with four replications in Agriculture Research Center of Gharahkeil, Qaemshahr, Mazandaran Province, Iran, during two years, 2010 and 2011. The experimental factors were including two levels (27 July and 7 August) of PLANTING dates as main plots, two levels of plant DENSITY (7 and 9 plants per m2) as sub-plots and four levels of seed priming (pure water, PEG-8000, KNO3 and control) as sub-sub-plots. Results showed that forage dry yield and ratio of ear to total dry weight were higher in 2010 than 2011. With the delayed PLANTING, forage dry yield and ratio of ear to total dry weight had decreased 31.7% and 18.2%, respectively. Furthermore, forage dry yield had increased 21.4% with the increasing of plant DENSITY. The seed priming with PEG also increased the ratio of ear to total dry weight. In total, results of this research indicated that the seed priming with PEG using late summer PLANTING in August and DENSITY of 90000 plants per ha is possible to produce the high quality forage in silage corn.