Evaluation of Nutritional Status of Hamedan Province Grape Fields by Compositional Nutrient Diagnosis Method

آب و خاک

Article 4, Volume 36, Issue 3 - Serial Number 83, July and August 2022, Pages 365-375   

Document Type: Research Article

DOI: 10.22067/jsw.2022.74703.1137

Author

R. Motalebifard^*

Soil and Water Research Department, East Azerbaijan Agricultural and Natural Resources Research and Education Center, AREEO, Tabriz, Iran.

Abstract

Introduction
 Grape is one of the most important horticultural products in the world and Iran which has been noticed due to its cultivation area, high economic and nutritional values. Annually, about 68 million tons of grape are produced in the world. Iran, with 309,000 ha cultivation area and about 3.3 million tons share of production, is the 11^th largest producer of this fruit in the world. Recent studies have shown that plant nutrition and soil fertility have significant effect in the reduced yield quality in the grape fields of our country. Plant nutrition as an influential factor is a function of the interaction of nutrients and environmental conditions. Assessing the nutritional status of plants is necessary to achieve the relationship between nutrients availability in the soil, the amount of elements in the plant and yield. Plant analysis method is used to optimize fertilizer application and diagnose plant nutrition disorders. The plant analysis method is useful for evaluating plant nutrition if an appropriate method to be used to diagnose and interpret the results. Tissue nutrient status can be diagnosed by the Critical Value Approach (CVA), the Diagnosis and Recommendation Integrated System (DRIS), and Compositional Nutrient Diagnosis (CND). Only DRIS and CND provide nutrient imbalance indexes, although no threshold value has been validated yet for diagnostic purposes. CND method expresses interactions by considering the ratio of one element to all elements. In this method, high and low functional groups are separated with great accuracy with the help of mathematical and statistical methods and the application of the cumulative function of variance ratio of nutrients and chi-square distribution function. A critical CND imbalance index was derived from the chi-square distribution function. Due to the importance of grape production in the country and the lack of required nutritional norms, this study was conducted to investigate the nutritional status of grape fields using the CND method.
Materials and Methods
In order to evaluate the nutritional status of grape fields in the Hamedan province, this study was conducted in the cropping years of 2017-2020. Every year, 40 different orchards were selected in each of the regions. The orchards were selected in such a way that they had different ranges of yield and soil properties. A database containing laboratory and field data was created for each grape field. The geographical location was recorded for the orchards. In each orchard, plant (leaf) samples were prepared and analyzed based on suitable laboratory methods. At the end of the season, the yield and its components were determined by visiting each orchard. Concentrations of nitrogen, phosphorus, potassium, calcium, magnesium, iron, zinc, manganese, and copper were measured in grape leaves. The project database was completed and CND indices were calculated for each nutrient element. The selected grape fields were divided into two groups with high and low yield based on yield. The CND norms and indexes were computed according to computation steps of Parent and Dafir. The Cate–Nelson ANOVA procedure was used to partition yield data between two groups by maximizing the between-groups sums of squares to determine the threshold values for CND indexes required to compute the critical CND r² value. We used 83 observations for developing the nutrient norms.
Results and Discussion
 The results of the indices calculated by the method of CND showed that the grape fields were deficient in nitrogen and potassium among the macronutrients and iron and manganese among the micronutrient elements. There was a correlation (0.25) between nutritional balance index and yield that was significant at 1 percent probability level. Potassium index was negative in 83% of low yield orchards. After potassium, nitrogen had a negative index in 58% of medium and low yield orchards. Phosphorus had the most positive index among macronutrients and was positive in most orchards. Among the micronutrients, manganese, iron, and zinc indices were negative in 59%, 49% and 73% of the orchards, respectively. The presence of calcareous conditions in the soils of the region can be the reason for this deficiency. The boron index was positive in some orchards and negative in some other orchards. Furthermore, in total, the index of unknown factors was negative in 41% of grape fields in Hamadan province.
Conclusion
 The results indicated that management of evaluated orchards was not suitable and application of chemical fertilizers was unbalanced. The results of this study can be used in grape fields to increase yield and product quality. Therefore, it is recommended to use deficient elements in the fertilization program to improve yield.

Keywords

Grape; Nutrients; Nutritional status; Optimum level

References

1. Anonymous. 2013. Agricultural statistics. First volume: Crops Jihade-Agriculture Ministry, Tehran, Iran.
2. Baldock J.O., and Schulte E.E. 1996. Plant analysis with standardized scores combined with DRIS and Sufficiency ranges approaches in corn. Agronomy Journal 88: 448-456. https://doi.org/10.2134/agronj1996.00021962008800030015x.
3. Basirat M., Akhiani A., and Daryashenas A. 2016. Estimating sufficiency norms in compositional nutrient diagnosis (CND1) method for Shahroudi table grape. Iranian Journal of Soil Research 30(1): 1-11. (In Persian with English abstract)
4. Basirat M., Hanghightnia H., and Mousavi S.M. 2018. Evaluation and determination of the nutritional status of valencia orange orchards in south of fars province. Journal of Water and Soil 32(1): 143-154. (In Persian with English abstract). https://doi.org/10.22067/jsw.v32i1.67597.
5. Chakerolhosseini M.R., Khorassani R., Fotovat A., and Basirat M. 2016. Determination of norms and limitation of nutrients for orange by the compositional nutrient diagnosis method. Journal of Soil Management and Sustainable Production 6(3): 161-172. (In Persian with English abstract)
6. 6. Ganeshamurthy A.N., Govindakrishnan P., Raghupathi H.B., and Mahendra Kumar M.B. 2019. Compositional nutrient diagnosis (CND) norms and indices for potato (Solanum tuberosum L.). Journal of Horticultural Science 14(2): 142-148. https://doi.org/10.24154/JHS.2019.v14i02.009.
7. Ghodarzi A.K. 2005. Nutritional balance evaluation of Sisakht region vineyard in Kohkiloyeh and Boyerahmad province by DOP method. Soil and Water Science 19(1): 33-34. (In Persian)
8. Jones J. 2001. Laboratory Guide for Conducting Soil Tests and Plant Analysis. CRC Press, LLC. USA.
9. Khiari L., Parent L.E., and Tremblay N. 2001a. Critical compositional nutrient indexes for sweet corn at early growth stage. Agronomy Journal 93: 809-814. https://doi.org/10.2134/agronj2001.934809x.
10. Khiari L., Parent L.E., and Tremblay N. 2001b. The Phosphorus compositional nutrient diagnosis range for potato. Agronomy Journal 93: 815-819. https://doi.org/10.2134/agronj2001.934815x.
11. Khiari L., Parent L.E., and Tremblay N. 2001c. Selecting the high-yield subpopulation for diagnosing nutrient imbalance in crops. Agronomy Journal 93: 802-808. https://doi.org/10.2134/agronj2001.934802x.
12. Majidi A., Rahnemaie R. 2015. Effects of physicochemical properties of calcareous soils on boron adsorption-desorption reactions.  Iranian Journal of Soil Research (Formerly Soil and Water Sciences) 29(3): 321-333. (In Persian with English abstract)
13. Malakouti M.J., and Riazi-Hamadani A. 1992. Soil fertility and fertilizers (Translated), University Publication Center. Ministry of Culture and Higher Education. Pub. No. 598, pp. 800.
14. 14. Parent L.E., and Dafir M. 1992. A theoretical concept of compositional nutrient diagnosis. Journal of American Society for Horticultural Science 117: 239-242. https://doi.org/10.21273/JASHS.117.2.239.
15. Parent L.E., and Khiari L. 2003. The compositional nutrient diagnosis of onions .xxxvi international horticultural congress: Toward ecologically sound fertilization strategies for field vegetable production. http://www.actahort.org.
16. Parent L.E., Cambouris A.N., and Muhawenimana A. 1994. Multivariate diagnosis of nutrient imbalance in potato crops. Soil Science Society of American Journal 58: 1432-1438. https://doi.org/10.2136/sssaj1994.03615995005800050022x.
17. Pereira B.F., Stoffella P.J., and Melfi A.J. 2011. Reclaimed wastewater: Effects on citrus nutrition. Journal of Agricultural Water Management 98: 1828-1833. https://doi.org/10.1016/j.agwat.2011.06.009.
18. Ryan J.R., Stefan G., and Rashid A. 2001. Soil and Plant Analysis Laboratory Manual (2^nd ed). ICARDA. Aleppo, Syria, PP.172.
19. Sajjadi A.S. 1992. Diagnisis and recommendation integrated system. Report number of 847. Soil and Water Research Institute, Tehran, Iran. (In Persian)
20. Samadi A., and Majidi A. 2010. Determination of DRIS indices and comparison of them with DOP method in curly white grape. Iranian Journal of Soil Research (Formerly Soil and Water Sciences) 24(2): 89-105. (In Persian eith English abstract)
21. Taheri M. 2017. Evaluation of vineyards nutritional status using nutrition indices in Khodabande region. Iranian Journal of Horticultural Science 47(4): 703-715. (In Persian with English abstract). http://dx.doi.org/10.22059/ijhs.2017.123762.764.
22. Westerman L.Z. 1990. Soil Testing and Plant Analysis. Soil Science Social America Book Sereach 5. Madison, WI, USA.