African Journal of
Food Science

  • Abbreviation: Afr. J. Food Sci.
  • Language: English
  • ISSN: 1996-0794
  • DOI: 10.5897/AJFS
  • Start Year: 2007
  • Published Articles: 812

Full Length Research Paper

Effect of tree age on nutritional, anti-nutritional and proximate composition of Moringa stenopetala leaves in South west Ethiopia

Fikremariam H. Desalegne
  • Fikremariam H. Desalegne
  • Wood Technology Research Center, Ethiopian Environment and Forest Research Institute, P. O. Box 2322, Addis Ababa, Ethiopia.
  • Google Scholar
Zewdu Y. Ayele
  • Zewdu Y. Ayele
  • Central Ethiopia Environment and Forest Research Center, P. O. Box 30708, Addis Ababa, Ethiopia.
  • Google Scholar
Abeje E. Wasse
  • Abeje E. Wasse
  • Central Ethiopia Environment and Forest Research Center, P. O. Box 30708, Addis Ababa, Ethiopia.
  • Google Scholar


  •  Received: 06 August 2018
  •  Accepted: 25 March 2019
  •  Published: 31 July 2019

 ABSTRACT

Moringa stenopetala is one of the indigenous agro-forestry tree species cultivated in multi-storey inter-cropping system in the southern dry land areas of Ethiopia. It is an economically important tree species in which most parts of the plant are used for different purposes. Leaves of the plant collected from age classes of the tree are edible after processing. Despite its wider usage in the southern parts of the country, little is known about the nutritional composition of the leaves at different age classes of the tree. We investigated the effect of tree age on nutritional, ant-nutritional and proximate composition of M. stenopetala leaves and determined the moisture content, ash content, crude fiber, crude protein, fat, tannin content, phytate content, iron, calcium, phosphorus and potassium in the leaves. Authentic representative M. stenopetala leave samples were collected from 3, 4, 5, 6 and 7 years old tree in Derashe area, southern part of Ethiopia. The collected leaf samples were dried and subjected to physico-chemical analysis following standard methods of analysis. The laboratory results were analyzed using SAS Statistical software. The analysis indicated a significant difference in the main effect of all nutrition and anti- nutritional parameters between the five classes at 1% significant level. However, there was no significant difference in the cationic composition of iron and zinc among age classes of the tree. This study suggests that plant age has an influence on nutrition, anti-nutritional composition and most of the proximate elements. M. stenopetala trees that grew up well and reached age of five had better nutritional, anti-nutritional and proximate composition implying that leaf collection should to be done on trees that are established and grown well and reached at least five years of age.

 

Key words:  Moringa stenopetala, nutritional, anti-nutritional, proximate composition.


 INTRODUCTION

The Eastern Africa region is predominantly a dry land with about 60% of the total land area classified as arid  or semi-arid (Funk et al., 2008). The rural economy is dominated by subsistence agriculture or pastoralists that are dependent on the available natural resources. Drought poses the greatest challenge to the livelihoods ofcommunities in this region, a problem that is compounded by over-reliance on traditional farming/ pastoral activities, which cannot cope with adversity brought about by drought. Moringa stenopetala is widely cultivated in Southern Ethiopia especially in Gamu-Gofa, Sidama, Konso and the adjoining provinces Abuye et al. (2003). Moringa is a drought tolerant fast growing indigenous tree mainly planted and maintained for its nutritional value (Assefa et al., 2015). Literature shows that Moringa leaves are rich sources of minerals and amino acids (Anjorin et al., 2010; Wakil and Kazeem, 2012).
 
Related to the above mentioned points, the country gives great attention to the most important local survival strategies and intensifies the agricultural system to overcome the reaped climatic shocks that hamper agricultural production leading to food shortage (Guinad and Lemessa, 2000). Strategies to overcome climatic shocks and reduce agricultural production include strengthening the households’ resources base (Erhabor and Emokaro, 2007; Ibrahim et al., 2009) and diversifying alternate food sources (Ghosh et al., 2011). This study focused on determining the appropriate age of Moringa stenopetala for better nutritional composition. We investigated impact of different age classes on nutritional value of M. stenopetala leaves.

 


 MATERIALS AND METHODS

Site description
 
The plant leaves for the experiment were collected from the Derashe woreda of the South Nations and Nationalities Peoples Region (SNNPR). Derashe woreda is one the best potential sites for growing and production of M. stenopetala trees. It is located in the Great Rift Valley Region at 630 Km South west of Addis Ababa in Ethiopia, at 7°4°N latitude and 38°31°E longitude. The Woreda has an altitudinal range from 1300 up to 2545 m above sea level and average annual rain fall of 952.1 mm. The mean temperature ranges between 12 and 27°C.
 
Sample preparation
 
M. stenopetala tree ages of 3, 4, 5, 6 and 7 were randomly selected from farmers’ field/garden. The fresh leaf samples were collected in the morning by hand from the crowns of each selected tree in four directions (North, South, West and East) to capture possible variations in the leaf characteristics. Composite leaf samples per tree were taken for further analysis. The sample leaves were transported to the Wood Technology Research Center in Addis Ababa in plastic bags. The leaves were spread on thin canvas sheet placed in a greenhouse and dried in the open air until the leaves were dried uniformly. The dried leaves were hand-crushed and further grounded using mortar and pestle to 2 mm size. The crushed leave samples were then put in the paper bag and kept at room temperature   until  the  laboratory  analysis  was  carried  out.
 
Nutritional and proximate composition analysis
 
Analysis on the nutritional and proximate composition of M. stenopetala leaves was done in the nutritional laboratories of Ethiopian Health Institute. The nutritional aspects/characteristics of the Moringa leaves included moisture content, ash content, crude fiber, nitrogen content, crude protein and mineral contents.
 
Determination of moisture content
 
Three replicates of ground Moringa leaves that weigh accurately 2 g from each tree age was weighed and dried at 105°C for 5 h using Oven (Memert Germany ALC-210.4 model). Oven dry weight was recorded after allowing the samples to cool in a desiccator before reweighing. Moisture content was expressed as a percentage of the weight loss from the original weight (Yebeyen et al., 2009; Nilsen SS 2010.
 
Determination of ash
 
Three replicates of grounded Moringa leaves that weigh accurately 2 grams from each tree age were first heated on a burner in air to remove its smoke. Then each leaf sample was burned in a furnace at 550°C for 1.30 h. The ash content was expressed as a percentage ratio of the weight of the ash to the oven dry weight (Nielsen SS 2010).
 
Determination of total nitrogen and crude protein
 
Exactly 0.5 g of each Moringa leave sample, in three replicate for each tree age, was weighed and transferred into 2300 Kjeldahl digestion tube plus one Kjeldahl tablet, copper sulfate-potassium sulfate catalyst. Then 10 ml of concentrated, nitrogen free and sulfuric acid was added. The tube was then mounted in the digestion heating system which was previously set to 240°C and capped with an aerated manifold. The solution was then heated at the above temperature until a clear pale yellowish-green color was observed. This indicates the completion of the digestion. The tubes were then allowed to cool at room temperature. Their content was quantitatively transferred to Kjeldahl distillation apparatus followed by addition of distilled water and 30% (w/v) sodium hydroxide. Steam distillation was then started and the released ammonia was absorbed in 25 ml of 2% boric acid. Back titration of the generated borate was then carried out versus 0.02 M Hydrochloric acid using methyl red as an indicator. Blank titration was carried out in the same way. The percentage of nitrogen content was then calculated (AOAC, 1990).The protein content was calculated using the nitrogen conversion factor of 6.25 as proposed by Greenfield and Southgate, 2003).
 
Determination of mineral content
 
Ash from a sample of Moringa leaves was dissolved in concentrated sulfuric acid. Then, the solution was used for the determination of the minerals studied except for phosphorus which was determined by an atomic absorption spectrometer. Appropriate standard solution was prepared for each metal and used by atomic absorption spectrometer (model AAA-6800) to prepare the graph for the determination of the amount of each metal from the test solution. Wet ash method was used for the determination of phosphorus   in   the   sample   leaves.  The  ash  was  dissolved  in
 
vanadomolybdic acid reagent in which phosphate reacts to form a yellow molybdovanadophosphoric acid. Finally, the amount of phosphorus was determined using CECL 1021 model a UV–VIS spectrometer at 400 nm in 1 cm cells, and expressed as % Na3PO4 (AOAC, 2005).
 
Phytate determination
 
This was determined using the method described by Latta and Eskin (1980). A 0.5 gm of dried Moringa stenopetala sample leaves was extracted with 10 ml of 0.2N HCl for 1 h at an ambient temperature. 2 ml of wade reagent solution was added into 3 ml of the supernatant extraction solution; the solution was homogenized and finally centrifuged for 10 min at 3000 rpm. The clear supernatant solution was taken to measure the absorbance at 500 nm using UV-VIS spectrophotometer (CECL 1021 model mad in England). The amount of Phytic acid was calculated using Phytic acid standard curve and result was expressed as Phytic acid in mg/100 gm (Burns et al., 2001).
 
Tannin determination
 
This was determined using the method described by Burns et al. (2001).One gram of dried M. stenopetala leaf sample was extracted with 10 ml of 1% HCl in methanol using mechanical shaker for 24 h at room temperature and centrifuged for 5 min. 1 ml of the clear supernatant solution was taken and mixed with 5 ml of Vanillin HCl reagent and stood for 20 min until the reaction was completed. The absorbance of the clear supernatant solution at 500 nm was measured using UV-VIS spectrophotometer (CECL 102 model mad in England). The amount of Tannin was calculated using SPSS plot’s slope; and intercept of the standard curve is as given in the mathematical equation (Latta and Eskin, 1980).
 
 
Where: As = Sample absorbance, Ab = Blank absorbance, d = Density of solution (0.791 g/ml) and   w = Weight of sample in gram.
 
Data analysis
 
The nutritional value, photochemical and anti-nutrient analysis data were subjected to one way of variance analysis (ANOVA) statistical method using Generalized Linear Models Procedure (GLM) (Gomez and Gomez, 1995).  A total of five age treatments with three replications   and    12   test   parameters   were   designed   in   the experiment. Statistical analysis of data was carried out using SAS Version 9. Means that exhibited significant differences were compared using Least Significant Difference (LSD) at (P <0.001) level.


 RESULTS AND DISCUSSION

Nutritional and anti-nutritional composition parameters
 
The analysis of variance showed that the effect of all nutrition and anti- nutritional composition parameters differed among the five tree ages at 1% significant level. Exception to this was for the cationic composition of iron and zinc that did not show any difference between tree ages (Table 1).
 
Moisture content
 
The overall mean moisture content for the M. stenopetala leaves across the age in the experiment was 8.99%.Trees at the age of four had significantly higher moisture content (10.60%), followed by trees at the age of three (9.88%). The lower moisture content of leaves was obtained at trees with the age of five (7.79%) and six (8.07%) (Table 3). In this study, the moisture contents of matured tree of 6 and 7 years M. stenopetala leaves were compared (Abinet et al., 2011). Almost similar values were observed. Similar to the situation, we have noted that  maximum  moisture content (9.88, 10.6 and 7.79%) was found in the study on tree of 3; 4 and 5 of  M. stenopetala leaves compared  to the previous results (6.43 to 6.83%)  obtained by Stevens et al. (2015 ) on proximate and anti-nutritional composition on different accession of Moringa oleifera  leaves across Nigeria.  The variation of moisture content in different studies was predictable as tree age variation, leaves collection period (harvesting time) and different system of cultivation managements used.
 
Ash content
 
The overall  mean  ash  content  for  the  M.  stenopetala samples across the age in the experiment was 11.23%. Ash content of M. stenopetala leaves from tree of 4 years showed significantly higher ash content (14.33%) than all other tree ages (Table 2). No significant difference was observed in ash content among tree of 3, 6 and 7 years. The ash content of this study compares with those previously analyzed (3.91 to 4.74%) by Steven et al. (2015) and similarly studied by Aberra et al. (2015) in which the value ranged  from 7.10 to 8.03%; it was maximum but similar to Abuye et al. (2003)’s study, which was reported to be 9.1 to 14.2%.
 
 
Crude fiber
 
The crude fiber content ranged from 35.36% (age = 6) to 32.84% (age = 3) with the overall mean crude fiber content of 32.29%. These crude fiber contents of M. stenopetala leaves were higher than the crude fiber reported by Aberra et al. (2015), ranging from  16.7, 17.2 and 18.7%.
 
Fat
 
The fat content of M. stenopetala leaves ranged from 0.35 to 0.44% with the overall mean fat content of 0.38%. Significantly higher fat content was observed at tree age of 5 (0.44%) and 4 (0.42%) than the other tree age (Table 2). The fat content of M. stenopetala leaves at Derashe differ from other studies reported by Morlu et al. (2017) (5.8% for Moringa avalifolia and 6.61% for M. oleifera),  This variation might be attributed to the difference in latitude, longitude, annual rainfall, humidity and soil type (Dechasa et al., 1995).
 
Crude protein
 
The crude protein content of M. stenopetala leaves ranged from 31.16 to 34.4% with the overall mean crude protein content of 32.29%. Significantly higher crude protein content was observed  at  tree  age  of  5  (34.4%) and 4 (32.54%) than the other tree age (Table 2). Statistically lower crude protein was recorded on leaves at tree age of 3 (31.53%) and tree age of 7 (31.16%), which is 10.40% lower crude protein content than the maximum (Table 2). The amount of protein found in this study is comparable with the previous study by Morlu et al. (2017), which ranged from 23.21 to 24.75% on different accretion of M. oleifera across Nigeria.
 
Proximate composition
 
A significant variation between tree ages was observed for Ca, P and K but not for Iron and Zinc (Table 1). The amount of phosphorus, potassium, and calcium in the M. stenopetala leaves ranged from 85.19 mg/100 g to 467.24 mg/100 g; 1420.40 mg/100 g to 1878.12 mg/100 g and 263.33 mg/100 g to 315.19 mg/100 g, respectively (Table 2). Significantly higher values of cationic composition phosphorus (467.24 mg/100 g) and potassium (1878.12 mg/100 g) were recorded on leaves from tree age of 5. A higher cationic composition of calcium was recorded on leaves from tree age of 3 (315.19 mg/100 g). The observed value of the different minerals in the present study differs from another study (Morlu et al., 2017).These variations might be attributed to differences in the varieties used by these researchers. Different ecotypes and varieties of M. stenopetala are found in Ethiopia (Eyassu et al., 2014).
 
Anti-nutritional composition
 
The results of this study showed a significant difference in values of phytate and tannin among tree ages (Table 3).  M. stenopetala leaves from tree age of 6 contain more tannin (403.94 mg/100 g) and phytate (725.60 mg/100 g). The lower tannin (163.89 mg/100 g) and phytate (544.32 mg/100 g) content was found in leaves from tree age of 5 (Table 4). The finding of the present study is comparable with another report by Ijarotimi et al. (2013)  that reported the tannin content of 347.67 mg/100 g. The tannin content reported by Ijarotimi et al. (2013) is actually 52.86% higher than  the  lowest  value  we  found from leaves of 5 years old tree. Similar anti-nutritional factors in plant foods were also reported by Habtamu and Negussie (2014).  The phytate content obtained in this study was higher that of the study by Abinet et al. (2011), who reported 378.44 mg/100 g of M. stenopetala leave samples collected from different parts of Ethiopia. The variation might be due to the differences in geographical location and soil type between the study areas.
 
 


 CONCLUSION

This study has clearly indicated that the nutritional, anti-nutritional and proximate composition of M. stenopetala leaves showed variation among the tree ages. The nutrient composition of M. stenopetala leaves in most cases was found higher in trees of  4 and 5 years compared to those of 3, 6 and 7, while anti-nutritional compositions, which are tannin and phytate of M. stenopetala leaves in most cases was found least for trees of 5 years compared to tree of 3, 4, 6 and 7 years; proximate composition has an adequate amount on trees of 3 and 5 years, respectively. Therefore, in this study the authors conclude that, trees of 5 years have better nutritional, anti-nutritional and proximate composition compared to all age categories included in this study.


 CONFLICT OF INTERESTS

The authors have not declared any conflict of interests.

 


 ACKNOWLEDGEMENTS

The authors are grateful to Ethiopian Public Health Institute for providing its laboratory facilities to carry out nutritional and proximate composition analysis. Authors would also like to extend gratitude to Mr. Addisu Leggese Chaka, staff of Ethiopian Public Health Institute for all support concerning the experiment condition and for doing some chemical analysis in the laboratory, and other staff members are acknowledged for their contributions in nutrient analysis. Finally, authors would like to  thank Central Ethiopia Environment and Forest Research Center for giving financial support for this study. 



 REFERENCES

Aberra M, Degnet H, Sandip B, Aster A, Amsalu S (2015). The Effect of Supplementing Air-Dried Moringa Stenopetala Leaf to Natural Grass Hay on Feed Intake and Growth Performances of Arsi-Bale Goats. Agriculture 5:1183-1194
Crossref

 

Abinet T, Adamu B, Kalab K, Meseret W, Behnu W, Yohannes T (2011). Nutritional Profile of Moringa stenopetala Species. Samples Collected in Different Places in Ethiopia and their Comparison with Moringa oliferea Species. Available at: 

View.

 
 

Abuye C, Urga K, Knapp H, Selmar D, Omwega AM, Jmungl Jk, Winterhalter P (2003). A Compositional study of Moringa stenopetala leaves. East African Medical Journal 80:247-52.
Crossref

 
 

Anjorin TS, Ikokoh P, Okolo S (2010). Mineral composition of Moringa oleifera leaves, pods and seeds from two regions in Abuja, Nigeria. International Journal of Agriculture Biology 12:431- 434.

 
 

Associattion of Official Analytical Chemists (AOAC) (1990). Offiial methods of analysis. 15th Edn. Washington DC

 
 

Associattion of Official Analytical Chemists (AOAC) (2005). Official methods of analysis. Food composition, additives, natural contaminants. Adrich RC, 15th Edn. AOAC inc. USA.

 
 

Assefa A, Emiru B, Tewodros T, Kiros M (2015). Moringa stenopetala Tree Species Improved Selected Soil Properties and Socio-economic Benefits in Tigray, Northern Ethiopia. Science, Technology and Arts Research Journal, pp. 2226-7522.

 
 

Burns JPT, Gardner D, Mathew GG, Duthie M, Lean E, Crozier A (2001). Extraction of phenolic and changes in antioxidant activity of red wine during verification. Journal of Agricultural and Food Chemistry 49:5797-5808.
Crossref

 
 

Dechasa J (1995). Moringa stenopetala, A Multipurpose Indigenous Tree and its Potential Role in the Rift Valley Farming Systems of Ethiopia. Forestry Research Centre, Ministry of National Resource, Development and Environmental Protection, Addis Ababa, Ethiopia.

 
 

Erhabor PO, Emokaro CO (2007). Relative technical efficiency of cassava farmers in the three agro-ecological Zones of Edo state, Nigeria. Journal of Applied Scenes 7:2818-2823.
Crossref

 
 

Eyassu S (2014). Actual and Potential Application of Moringa stenopetala, Underutilized Indigenous Vegetable of Southern Ethiopia. International Journal of Agricultural and food Research 3(4):8-19.
Crossref

 
 

Funk C, Dettinger MD, Michaelsen JC, Verdin JP, Brown ME, Barlow M, Hoell A (2008). 'Warming of the Indian Ocean threatens eastern and southern African food security but could be mitigated by agricultural development'. PNAS - Proceedings of the National Academy of Science 105(32):11081-11086.
Crossref

 
 

Ghosh Bk (2011). Essence of crop diversification: A study of West Bengal agriculture. Asian Journal of Agricultural Research 5:18-44.
Crossref

 
 

Gomez and Gomez (1995). Dual Language Enrichment (DLE) model was originally developed in and first implemented in 1995 in the pharr- san juan- Alamb.

 
 

Greenfield H, Southgate DAT (2003). Food composition data: Production, management and use. 2nd edition, FAO, Rome.

 
 

Guinad Y, Lemessa D (2000). Wild food plants in Southern Ethiopia:- Reflection on the role of famine foods at a time of drought. University of Pennslvania African Studies Center. 

 

 

Habtamu F, Negussie R (2014). Ant nutritional factors in plant foods:- potential health benefits and adverse effects. International Journal of Nutrition and Food Science 3(4):284-289.
Crossref

 
 

Ibrahim H, Bello M, Ibrahim H (2009). Food security and resource allocation among farming households in North Central Nigeria. Pakistan Journal of Nutrition 8:1235-1239.
Crossref

 
 

Ijarotimi OS (2013). Comparative study of natural profiles and photochemical components of raw blanched and fermented flour from the leaves of Moringa oleifera. Food Science and Nutrition, pp. 371-382.

 
 

Latta MC, Eskin M (1980). A simple and rapid spectrophtometric method for Phytate determination. Journal of Agricultural and Food Chemistry 28(6):1313-1315.
Crossref

 
 

Morlu K, Charles N, Haruna M, Habauka K (2017). Comparative Proximate and Mineral Composition of Moringa oleiferaand Moringa ovalifoliaGrown in Central Namibia. Sustainable Agriculture Research 6:4.
Crossref

 
 

Nilsen SS (ed.) (2010). Food Analysis, Forth edition, Wese lafayafatte, in, USA.

 
 

Stevens C, Ugese F, Otitoju G, Baiyeri K (2015). Proximate and anti-nutritional composition of leaves and seeds of moringa oleifera in nigeria: a comparative study. Agro-Science Journal of Tropical Agriculture, Food, Environment and Extension 14:9-17
Crossref

 
 

Wakil S, Kazeem M (2012). Quality assessment of weaning food produced from fermented cereal-legume blends using starters. International Food Research Journal 19:1679-1685.

 
 

Yebeyen D, Mulugeta L, Sisay F (2009). Characteristics and quality of gum arabic from naturally grown Acacia senegal (Linne) Willd. trees in the Central Rift Valley of Ethiopia. Food Hydrocolloids 23:175-180.
Crossref

 

 




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