Diagnosis of Nutrient Imbalance in Wheat Plant by DRIS and PCA Approaches
(ندگان)پدیدآور
Geiklooi, AbolfazlReyhanitabar, AdelNajafi, NosratollahHomei, Hajir
نوع مدرک
TextResearch Paper
زبان مدرک
Englishچکیده
The foliar diagnosis can be considered as a useful tool to assess the nutritional status of plants. The diagnosis and recommendation integrated system (DRIS) has been developed for this purpose. In this study DRIS norms were determined for wheat plant (Triticum aestivum L.) in the Moghan region, northwest of Iran. A data bank created from nutrients concentrations of flag leaf and yield was used to subdivide data into low and high yielding subgroups based on average yield ± SD. Calculated DRIS indices showed the nutrients requirement order as fallow: Zn>Mn=Fe=Cu>N=P>B>K>Ca>Mg. Based on nutrient application potential response (NAPR) method, N, P, K, Ca, Mg and B were placed in the negative response class and Fe, Zn, Cu and Mn were placed in the positive response class. The result of principal component analysis revealed that nutrient concentration in the low and high yielding subgroups and whole data set explained 54.88%, 68.65% and 63.03% of the total variance, respectively. The involvement of several nutrients in a single PC indicated that the diagnosis of any nutrient imbalance is not possible in isolation. This study showed that in this region, macronutrients and micronutrients are in the adequate status (positive DRIS indices) and deficiency state (negative DRIS indices), respectively. Furthermore, NAPR method indicated the positive response of crops if micronutrients were added to the soil.Mn=Fe=Cu>N=P>B>K>Ca>Mg. Based on nutrient application potential response (NAPR) method, N, P, K, Ca, Mg and B were placed in the negative response class and Fe, Zn, Cu and Mn were placed in the positive response class. The result of principal component analysis revealed that nutrient concentration in the low and high yielding subgroups and whole data set explained 54.88%, 68.65% and 63.03% of the total variance, respectively. The involvement of several nutrients in a single PC indicated that the diagnosis of any nutrient imbalance is not possible in isolation. This study showed that in this region, macronutrients and micronutrients are in the adequate status (positive DRIS indices) and deficiency state (negative DRIS indices), respectively. Furthermore, NAPR method indicated the positive response of crops if micronutrients were added to the soil.N=P>B>K>Ca>Mg. Based on nutrient application potential response (NAPR) method, N, P, K, Ca, Mg and B were placed in the negative response class and Fe, Zn, Cu and Mn were placed in the positive response class. The result of principal component analysis revealed that nutrient concentration in the low and high yielding subgroups and whole data set explained 54.88%, 68.65% and 63.03% of the total variance, respectively. The involvement of several nutrients in a single PC indicated that the diagnosis of any nutrient imbalance is not possible in isolation. This study showed that in this region, macronutrients and micronutrients are in the adequate status (positive DRIS indices) and deficiency state (negative DRIS indices), respectively. Furthermore, NAPR method indicated the positive response of crops if micronutrients were added to the soil.B>K>Ca>Mg. Based on nutrient application potential response (NAPR) method, N, P, K, Ca, Mg and B were placed in the negative response class and Fe, Zn, Cu and Mn were placed in the positive response class. The result of principal component analysis revealed that nutrient concentration in the low and high yielding subgroups and whole data set explained 54.88%, 68.65% and 63.03% of the total variance, respectively. The involvement of several nutrients in a single PC indicated that the diagnosis of any nutrient imbalance is not possible in isolation. This study showed that in this region, macronutrients and micronutrients are in the adequate status (positive DRIS indices) and deficiency state (negative DRIS indices), respectively. Furthermore, NAPR method indicated the positive response of crops if micronutrients were added to the soil.K>Ca>Mg. Based on nutrient application potential response (NAPR) method, N, P, K, Ca, Mg and B were placed in the negative response class and Fe, Zn, Cu and Mn were placed in the positive response class. The result of principal component analysis revealed that nutrient concentration in the low and high yielding subgroups and whole data set explained 54.88%, 68.65% and 63.03% of the total variance, respectively. The involvement of several nutrients in a single PC indicated that the diagnosis of any nutrient imbalance is not possible in isolation. This study showed that in this region, macronutrients and micronutrients are in the adequate status (positive DRIS indices) and deficiency state (negative DRIS indices), respectively. Furthermore, NAPR method indicated the positive response of crops if micronutrients were added to the soil.Ca>Mg. Based on nutrient application potential response (NAPR) method, N, P, K, Ca, Mg and B were placed in the negative response class and Fe, Zn, Cu and Mn were placed in the positive response class. The result of principal component analysis revealed that nutrient concentration in the low and high yielding subgroups and whole data set explained 54.88%, 68.65% and 63.03% of the total variance, respectively. The involvement of several nutrients in a single PC indicated that the diagnosis of any nutrient imbalance is not possible in isolation. This study showed that in this region, macronutrients and micronutrients are in the adequate status (positive DRIS indices) and deficiency state (negative DRIS indices), respectively. Furthermore, NAPR method indicated the positive response of crops if micronutrients were added to the soil.Mg. Based on nutrient application potential response (NAPR) method, N, P, K, Ca, Mg and B were placed in the negative response class and Fe, Zn, Cu and Mn were placed in the positive response class. The result of principal component analysis revealed that nutrient concentration in the low and high yielding subgroups and whole data set explained 54.88%, 68.65% and 63.03% of the total variance, respectively. The involvement of several nutrients in a single PC indicated that the diagnosis of any nutrient imbalance is not possible in isolation. This study showed that in this region, macronutrients and micronutrients are in the adequate status (positive DRIS indices) and deficiency state (negative DRIS indices), respectively. Furthermore, NAPR method indicated the positive response of crops if micronutrients were added to the soil.
کلید واژگان
Diagnosis and Recommendation Integrated System (DRIS)Nutrient Application Potential Response (NAPR)
Nutrient imbalance
Principal Component Analysis (PCA)
شماره نشریه
2تاریخ نشر
2017-12-011396-09-10
ناشر
دانشگاه تبریزدانشگاه تبریز
سازمان پدید آورنده
Department of Soil Science, Faculty of Agriculture, University of Tabriz, Tabriz, IranDepartment of Soil Science, Faculty of Agriculture, University of Tabriz, Tabriz, Iran
Department of Soil Science, Faculty of Agriculture, University of Tabriz, Tabriz, Iran
Department of Statistics, Faculty of Mathematical Sciences, University of Tabriz