Evaluation of Nutritional Status of Sugar Beet Plant by Deviation from Optimum Percentage (DOP) Method in Semnan Province (Shahroud): Results of a Two-Year Study

Extended Abstract
 
Background and Objectives
Sugar beet plays a key role as one of the important crops in the world's agricultural economy. After wheat and forage corn, sugar beet has the highest agricultural production in Iran. Understanding the nutritional status of plants is essential for enhancing both the quantity and quality of agricultural produce. In some cases, the soil test alone cannot show the problem of nutrient deficiency or nutritional imbalance. In such cases, analyzing plant tissue can provide clear insights into specific deficiencies. Several methods have been developed to determine the nutritional balance using the optimal concentration of nutrients as reference numbers (norms). One of the simple and effective methods for assessing the nutritional status of plants is the Deviation from Optimal Percentage (DOP) method. Various factors such as climatic conditions, variety, and nutrient management influence on the optimal concentration of nutrients. Therefore, for a more accurate understanding of the nutritional status of plants in each region, it is better to use appropriate norms for that region instead of using the optimal concentrations given in the literatures. In other words, the amount of nutrients in the high-yielding community can be used as the optimal limit of these elements in fertilizer recommendations, which is more favorable than those obtained for conditions different from the current ones. The DOP method serves as an essential and effective tool for evaluating the nutritional status of plants by using the ratio of different nutrients concentration compared to the reference concentration (C_ref), rather than relying on the absolute concentrations of nutrients. In this approach, the DOP index for each nutrient is calculated as the deviation percentage of its concentration from its optimal level in the plant. Due to its capability to accurately identify nutritional disorders, the DOP method is recognized as an effective tool in managing plant nutrition. This method enables farmers and researchers to assess the nutritional status of plants and determine appropriate fertilization patterns and optimize nutritional compositions. Thus, this research was conducted to evaluate the nutritional status of sugar beet and its optimal management using the DOP method over a two-year period in Semnan Province fields (Shahroud County), Iran.
 
Materials and Methods
This study was conducted on the sugar beet crop for two years (2018 and 2019) in Shahroud county, Semnan province, Iran. In each year, 30 fields with a range of different soil characteristics were selected. After selecting the fields, prior to planting and fertilizing the sugar beet, a composite soil sample was taken from each field, covering an area of one hectare and a depth of 0-30 cm. The physical and chemical properties of these samples were measured in the laboratory. Following the sugar beet planting in the first and second years, leaf sampling was performed to determine the concentration of nutrients. This sampling occurred approximately 90 to 120 days after planting, taking young, fully developed, and healthy leaves (between the youngest leaves at the center of the plant and older leaves). The leaf samples were washed with the distilled water, dried in an oven at 70 degrees Celsius for 48 hours, and then ground using an electric mill to measure their nutrients concentration. To determine the DOP index at harvest time (from the mid-October to the end of the November), field visits were conducted to record the yield, and the fields were classified into two groups: high-yield and low-yield. The fields with high-yield were utilized as references for establishing norms (C_ref). In this study, the high-yield group in the sugar beet fields was differentiated using the DOP method through mathematical, statistical analysis and the application of cumulative distribution functions.
 
Results
The results of the soil analysis from the selected fields indicated a wide range of physical and chemical characteristics. The findings in this province revealed that 83.3% and 45% of the soils were deficient in phosphorus and potassium, respectively. Out of the 60 fields studied, 10 were categorized as high-yield and 50 as low-yield. The average yield across all fields was calculated to be 61.1 tons/ha, with a standard deviation of 20.61 tons/ha. The average yield of the high-yield fields was 86.9 tons/ha, while in the low-yield group, it was 39.1 tons/ha. Also, the differences between the yields of these communities were statistically significant (p ≤ 0.05). Among the macronutrients in sugar beet, nitrogen (N) showed the highest deficiency (56%), followed by potassium (K) (52%) and phosphorus (P) (40%). Among the micronutrients, iron (Fe) (58%) and manganese (Mn) (56%) were the most deficient for the low-yield fields in comparison to their critical levels in the soil, followed by copper (Cu) (54%), zinc (Zn) (52%), and boron (B) (42%). The nutritional Balance Index (NBI) for sugar beet fields in, calculated from the absolute values of the DOP indices indicated a relative imbalance among the nutrients absorbed by this crop. This situation points to inadequate management of irrigation and fertilization in these fields.
 
Conclusion
The results indicated that one of the main reasons for the low-yield of sugar beet in the studied area of Semnan province is related to nutritional issues. The DOP method is well-suited for the unbalanced use of chemical fertilizers in Semnan province and can be utilized to assess nutrients status, diagnose nutritional disorders, improve fertilization recommendations, and enhance the quality of sugar beet in a practical manner in this province. According to the DOP method, to increase yield of sugar beet in Semnan province (Shahroud), special attention should be given to the application of nitrogen, phosphorus, iron, manganese, copper and zinc fertilizers.
Author Contributions
Conceptualization, J.Gh.; methodology, J.Gh. and Sh.F.; software, J.Gh.  and K.Kh; validation, J.Gh., Sh.F., and K.Kh.; formal analysis, J.Gh and A.A.; investigation, J.Gh., Sh.F., A.A., and K.Kh.; resources, J.Gh.; data curation, J.Gh. and Sh.F.; writing—original draft preparation, K.Kh.; writing–review and editing, J.Gh., Sh.F., and A.A.; visualization, J.Gh., Sh.F., and A.A.; supervision, J.Gh.; project administration, J.Gh.; funding acquisition, J.Gh. All authors have read and agreed to the published version of the manuscript.
Data Availability Statement
Data is available on reasonable request from the authors.
 
Acknowledgements
The authors are thankful to the Agricultural Research, Education and Extension Organization (AREEO) of Iran for financial supports.
 
Conflict of interest
The authors declare no conflict of interest.
 
Ethical considerations
The authors avoided data fabrication, falsification, plagiarism, and misconduct.