ارزیابی و تعیین وضعیت تغذیه‌ای باغات پرتقال رقم والنسیا در جنوب استان فارس

نوع مقاله : مقالات پژوهشی

نویسندگان

1 موسسه تحقیقات خاک و آب

2 مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان فارس

3 دانشگاه تهران

چکیده

با استفاده از روش‌های تشخیص چندگانه4 و تجزیه آماری چند متغیره5 وضعیت تغذیه‌ای باغات پرتقال رقم والنسیا در جنوب فارس مطالعه شد. برای این منظور تعداد 80 باغ پرتقال رقم والنسیا انتخاب و 30 درخت از هر باغ انتخاب ونشانه‌گذاری شدند. در فصل مناسب با انجام نمونه‌برداری از درخت‌های انتخاب شده، غلظت عناصر در نمونه‌های گیاهی تعیین و در فصل برداشت، میانگین عملکرد هر باغ اندازه‌گیری شد. نتایج نشان داد که 11 باغ جزء گروه عملکرد زیاد و 69 باغ دارای عملکرد کم بودند و میانگین عملکرد‌های مطلوب، 113 کیلوگرم بر درخت، به عنوان عملکرد هدف تعیین شد. از میانگین اعداد بدست آمده‌ی عناصر غذایی برای جامعه‌ی با عملکرد بالا، غلظت‌های مطلوب 10 عنصر مورد بررسی به دست آمد که شامل نیتروژن 18/0± 00/3 درصد، فسفر01/0± 17/ 0 درصد، پتاسیم12/0± 37/1 درصد، کلسیم 78/0±32/3 درصد، منیزیم07/0± 36/0 درصد، منگنز 35/3 ± 0/23 میلی‌گرم در کیلوگرم، روی3/2 ± 3/17 میلی‌گرم در کیلوگرم، آهن 3/7± 75 میلی‌گرم در کیلوگرم، مس 44/1± 81/7 میلی‌گرم در کیلوگرم و بور 4/19±76 میلی‌گرم در کیلوگرم بود. با مقایسه با اعداد مرجع به دست‌آمده برای باغات با عملکرد مطلوب، بیش از 50 درصد باغات مورد ارزیابی مقادیر نیتروژن، کلسیم و منگنز آنها کمتر از عدد مرجع به‌دست‌آمده بود و غلظت بور در گروه باغات با عملکرد بالا بیش از 50 درصد کمتر از باغات با عملکرد پایین بود که نشان‌دهنده محدودیت این عنصر در گیاه برای عملکرد است. همچنین، نتایج تجزیه آماری چندمتغیره و تجزیه به مولفه-های اصلی6 نشان داد که عناصر نیتروژن، کلسیم، آهن و روی به ترتیب بیشترین اثر را بر تغییرات عملکرد داشتند.

کلیدواژه‌ها


عنوان مقاله [English]

Evaluationand Determinationthe Nutritional Status of Valencia Orange Orchards in South of Fars Province

نویسندگان [English]

  • Majid Basirat 1
  • Hassan Haghighatnia 2
  • Seyed Majid Mousavi 3
1 Soil and Water Researchs Institute
2 Fars Agricultural and Natural Resources Research and Education Center
3 University of Tehran
چکیده [English]

Introduction: Fertilizer recommendation in orchards based on soil testing is not accurate because findings showed that there is not significant correlation between nutrients concentration in the soil and plant. Therefore, studying the nutritional status in orchards is usually based on the plant testing. In order to evaluate the nutritional status ofplants, different methods, such as Compositional Nutrients Diagnosis (CND), Diagnosis and Recommendation Integrated System (DRIS), Deviation from Optimum Percentage (DOP), Critical Value Approach (CVA) and Sufficiency Range Approach (SRA) were used. In the CND method, a determination coefficient measured which is considered as the relative superiority of this method to the others. Generally, through the CND method, a correct perception on nutritional status of plantsmay be obtained.
Materials and Methods: The nutritional status of orange orchards, Valencia cultivar, in south of Fars province (Darab town) was studiedusing the compositional nutrient diagnosis and multivariate statistical analysis methods. For this, 80 orange orchards, Valencia cultivar were selected and 30 trees in each orchard were signed. Plant samples were taken from the selected trees in the proper session and concentration of N, P, K, Ca, Mg, Mn, Zn, Fe, Cu and B weremeasured using the standard methods. Then the average yield was measured atharvest. Based on the CND method, total concentration of the nutrients in the plant was considered as a variable (Sd) plus a residual portion (Rd) that "d" is defined as the number of nutrients in the equation and Rd is defined as the residual value. Which sum of the equation equals 100 and it is based on percent. The residual/un measured nutrients and estimated by using the equation of " Rd = 100- (N+P+K+…)". Thereafter, by using the standard equations, which they were perfectly explained and presented in the material and methods section, the geometric mean of nutrients, nutrients index, nutrient balance index, and average yield and finally the reference norms were determined. In addition to the CND method, by using the Multivariate Statistical Analysis and PrincipalComponent Analysis methods, the effective and important nutrients in the yield were determined and also, ability of the CND method was evaluated. The SPSS software was used for variance analysis the data.
Compositional nutrient diagnosis (CND) analysis and multivariate analysis methods are used to study the nutritional diagnosis of Valencia orange orchards in south of Fars province. 80 valencia orange orchards were selected in the region and in each of them, 30 uniform trees were marked and sampled were taken in proper time and referenced method. Leaf elemental compositions and mean yield also were measured from selected trees for each orchard. Data analysis divided all orchards into two low and high yield groups.
Results and Discussion: The results showed that 11 orchards were as high yielding group and 69 orchards were as low yielding group and the average of optimum yields, 113 Kg tree-1, was determined as the yield goal. By using the average of measured nutrients norms for the high yielding community the concentration of the 10 studied elements was obtained which comprised: N 3.00± 0.18; P 0.17± 0.01; K 1.37± 0.12; Ca 3.32± 0.78; Mg 0.36±0.07; Mn 23± 3.35; Zn 17.3± 2.3; Fe 75± 7.3; Cu 7.81± 1.44; B 76± 19.4. Through comparison with the obtained reference norms of optimum yielding orchards, more than 50% of the studied orchards had lower N, Ca and Mn content than the obtained norm and B concentration in the high yielding group was more than 50% less than the low yielding group. Generally, the results of Multivariate Statistical Analysis and PrincipalComponent Analysis showed that N, Ca, Fe and Zn had the highest effect in changes of yield.
Conclusion: Resultsof this work showed that 13% of the studied orchards were in the high yielding group and 86% of themwere in thelow yielding group which shows the imbalance nutritional condition in the studied region. The positive effect of N and Ca on the yield may be due to the dilution effect which these nutrients can reduce the B toxicity. Abundance of Mn deficiency in the studied orchards may be due to the high concentration of Zn and Fe in the plants and antagonistic relations may be considered as the main reason. Multivariate statistical analysis methods may be used as an important tool to study the nutritional conditions of plants. Dominant percentage of the studied orchards showed low yield which may be due to the B toxicity which probably N and Ca application may be alleviated the negative effect of this element.

کلیدواژه‌ها [English]

  • Compositional nutrient diagnosis
  • Nutrients
  • Orange
  • Reference norms
ciation of official analytical chemists (AOAC). 1990. In: K. Helrich. (eds.), Official Methods of Analysis. 15th Edition. Published by the Association of Official Analytical Chemists, INC.
2- Aitchison J. 1988. Statistical analysis of compositional data. Chapman and Hall, New York.
3- Ross S.M. 1987. Introduction to probability and statistics for engineers and scientists. John Wiley & Sons, New York.
4- Basirat M. 2014. Introducing the compositional nutrient diagnosis method to determinate the nutritional status of pistachio orchards. In: Proceedings of the national congress of scientific approaches in the green gold industry, pistachio, 17-18 Dec., Islamic Azad University, Damghan Branch, NCSAPI01_107: (COI). (in Persian)
5- Basirat M., Daryashenas A., and Akhyani A. 2015. Reference norms determination for nutrients in the grape leaf (Shahroudi cultivar). Iranian journal of soil researches, 1 (1). (in Persian with English abstract)
6- Chakerolhosseini M.R., Khorasani R., Fatovat A., and Basirat M. 2015. Determining the reference norms and limitations of nutrient elements on orange by using the Compositional Nutrient Diagnosis method. Journal of soil management and sustainable production, 6(3): 161-172. (in Persian with English abstract)
7- Daryashenas A., and Pak Nejad A. 2005. Determining the DRIS standard norms for the autumn sown sugar beet in Khuzestan province. In: Proceedings of the 9th Iranian soil science congress, 28-31 Aug., University of Tehran, Karaj. (in Persian)
8- Daryashenas A., and Saghafi K. 2011. Compositional Nutrient Diagnosis (CND) for sugar beet. Iranian Journal of Soil Researches, 25(1). (in Persian with English abstract)
9- Emami A. 1996. Methods of Plant Analysis. Publications of the Soil & Water Research Institute, Karaj, Iran (in Persian).
10- Helmke P.H., and Spark D.L. 1996. Potassium, P 551-574. In: Sparks, D.L., Page, A.L., Helmke, P.A., Loppert, R.H., Soltanpour, P.N., M.A. Tabataai, C.T. Johston, and M.E. Summer. (eds.), Methods of soil analysis. SSSA, Inc. ASA, Inc. Madison, WI.
11- Kenworthy A.L. 1983. Leaf analysis as an aid in fertilizing orchards. p. 381-392 in L.M. Walsh and J.D. Beaton (eds.) Soil testing and plant analysis. Revised edition, 5th Printing, Soil Soil Science Society of America, Madison, WI.
12- 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.
13- Khiari L., Parent L.E., and Tremblay N. 2001b. The phosphorus compositional nutrient diagnosis range for potato. Agronomy Journal, 93:815–819.
14- 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.
15- Kjeldahl J. 1883. A New Method for the Determination of Nitrogen in Organic Matter. Zeitschrift für Analytische Chemie, 22, 366-382. http://dx.doi.org/10.1007/BF01338151.
16- Malakouti M.J. 2008. The comprehensive method of diagnostic and urgency of optimum fertilizers application for the sustainable agriculture. Publications of Tarbiat Modares University, Tehran, Iran. (in Persian)
17- Nelson L.A., and Anderson R.L. 1977. Partitioning of soil test-crop response probability. p. 19–38. In M. Stelly (ed.) Soil testing: Correlating and interpreting the analytical results. ASA Spec. Publ. 29. ASA, Madison.
18- Olsen S.R., Cole C.V., Watanabe F.S., and Dean L.A. 1954. Estimation of available phosphorous in soil by extraction with sodium bicarbonate. United States Department of Agriculture. United States Goverment. Print Office, Washington, D. C.
19- Parent L.E., and Dafir M. 1992. A theoretical concept of compositional nutrient diagnosis. Journal of the American Society for Horticultural Science, 117:239–242
20- 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.
21- 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.
22- Ross S.M. 1987. Introduction to probability and statistics for engineers and scientists. John Wiley & Sons. New York.
23- Rozane D., Junior D.M., Parent S., Natalei W., and Parent L.E. 2011. Compositional meta-analysis of Citrus varieties in the state of São Paulo Brazil.The 4th International workshop on compositional data analysis.
24- Samadi A., and Majidi A. 2010. Norms establishment of the diagnosis and recommendation integrated system and its comparison with the deviation from optimum percentage method in a white grape. Iranian Journal of Soil Researches, 24(2). (in Persian with English abstract)
25- Smith G.S., Asher G.J., and Clark C.J. 1997. Kiwifruit Nutrition diagnosis of nutritional disorders. Originally published 1985 ISBN 0-9597693-0-7, revised 1987, republished for HortNET 1997.
26- Soltanpour P.N., Malakouti M.J., and Ronaghi A. 1995. Comparison of diagnosis and recommendation in integrated system and nutrient sufficiency range for corn. Soil Science Society of American Journal, 59:10. 133-139.
27- Tisdale S.L, Nelson W.L., and Beaton J.D. 1993. Soil fertility and fertilizer. Macmillan USA. 648 page.
28- Turan M.A., Taban N., and Taban S. 2009. Effect of calcium on the alleviation of boron toxicity and localization of Boron and Calcium in cell wall of wheat. Notulae Botanicae Horti Agrobotanici Cluj-Napoca, 37 (2), 99-103.
29- Walworth J.L., and Sumner M.E. 1987. The Diagnosis and Recommendation Integrated System (DRIS). Advances in Soil Science, 6:149–188.
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