Showing 2 results for M. J. Malakouti
M. Kavoosi, M. J. Malakouti,
Volume 10, Issue 3 (fall 2006)
Abstract
Potassium is one of nutritional element that has an important effect on the quantity and quality of rice plant. Knowledge about the K critical level and plant response to different application rate of K, can effectively help with the proper use of this element. Therefore, in this study potassium (K) critical level for rice (Khazar variety) and prediction equation for grain yield were determined in 21 rice fields of Guilan provience during 2001-2002. After land preparation, 6 experimental plots (4×5m) were constructed in each selected field. Nitrogen and phosphorus were applied before transplanting, based on soil test from urea and triple superphosphate, respectively. Potassium was applied in different rates including 0, 100, 200, 300, 400, and 500 kg ha-1 of K2O as muriate potassium. Khazar variety was transplanted in a space of 25×25cm, just after fertilizing of plots. Plots were harvested in 5 m2 at the end of maturity stage from the first node above the ground, and grain and straw were measured separately. Statistic analysis was done on grain weight based on 14% moisture. The results showed, that effect of different K fertilizer application in 5% and the effect of soil type in 1% were statistically significant on the grain yield. The mean increase of grain yield in responsive fields to K application was 982 kg ha-1. The results also showed that the responses of rice fields with available K less than 100 mg kg-1, 100-160, and more than 160 mg kg-1 to KCl application were high, moderate and low, respectively. Potassium critical level based on 90% relative yield was determined as 110 mg kg-1 of soil . In final relative yield, prediction equation, available potassium, potassium content of irrigation water, and rate of KCl fertilizer application entered positively in the equation, while available phosphorus showed negative effect on relative yield.
M. Nourzadeh, S. M. Hashemy, M. J. Malakouti,
Volume 15, Issue 57 (fall 2011)
Abstract
Electrical conductivity and acidity of soil are the most important chemical factors of soil for agriculture. The nature of soil is in such a way that its change has a continuous form. The method that can take into account this continuity will be able to show a better picture of change in soil characteristics. Objectives of this research are to investigate the relations between measured electrical conductivity and soil acidity of Qom plain, and clustering, compare the clustering methods, determine the optimum numbers of cluster, and to zone the clusters in the study area. Accordingly, two fuzzy clustering methods FCM and GK, were used for data mining and clustering of 465 measured data. For estimating the appropriateness and comparison of two methods, some criteria including Partition Coefficient, Classification Entropy, Partition Index, Separation Index and Xie and Beni's Index were used. Data mining results showed that the optimum number of clusters for FCM and GK method was 15 and 17, respectively. After investigating the results of clustering and based on the criteria of appropriateness, it was indicated that GK was the best clustering method. According to this method, 295 data from 465 measured samples had more than 40 percent of membership function. So, 9 clusters from 17 clusters had more than 20 members. Then salinity-alkalinity zoning based on GK method to show the clusters distribution better in the study area was prepared. This prepared fuzzy map explained that most of Northwest and west belonged to cluster 1 and eastern parts of study area include belonged to cluster 17. Based on this, salinity-alkalinity and the ensuing soil degradation in east of study area is more likely than the west of it.
