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Fertilisation and pesticides affect mandarin orange nutrient composition
Food Chemistry 134 (2012) 1020–1024
Contents lists available at SciVerse ScienceDirect
Food Chemistry journal homepage: www.elsevier.com/locate/foodchem
Fertilisation and pesticides affect mandarin orange nutrient composition Xiaotian Zhang a, Andrew P. Breksa III c, Darya O. Mishchuk a, Cindy E. Fake d, Michael A. O’Mahony a, Carolyn M. Slupsky a,b,⇑ a
Department of Food Science and Technology, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA Department of Nutrition, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA c Western Regional Research Center, Agricultural Research Service, United States Department of Agriculture, 800 Buchanan St., Albany, CA 94710, USA d UC Cooperative Extension, Placer and Nevada Counties, 11477 E Avenue, Auburn, CA 95603, USA b
a r t i c l e
i n f o
Article history: Received 26 August 2011 Received in revised form 6 February 2012 Accepted 28 February 2012 Available online 8 March 2012 Keywords: NMR Citrus Mandarin orange Satsuma Foliar fertilisation Pesticide Metabolomics
a b s t r a c t The effects of the application of foliar fertilisation and pesticide on nutritional quality of mandarin orange juices were evaluated using 1H NMR metabolomics. Significant differences between the use of fertiliser and pesticides during fruit formation were observed, and included changes in sugar, amino acid and organic acid composition. To determine whether the difference in sugar concentration was enough for the consumer to detect, a sensory experiment was performed in which two orange juice samples were prepared to resemble the sweet/sour taste balance of juice from mandarin oranges in which foliar fertilisation was either applied or not. In a test using non-trained individuals, 68% could correctly identify which juice had a sourer, or less sweet, taste. The implications of this study could impact citrus growers, and ultimately aid in development of fruit with superior sensory quality. Ó 2012 Elsevier Ltd. All rights reserved.
1. Introduction Citrus is an important horticultural crop, with worldwide agricultural production over 82 million metric tons per year (Blauer, 2010). Oranges represent a significant part of California’s citrus economy with more than 80% going to the fresh market, depending on the quality of the crop. Crop quality can depend on the growing season (i.e. rainfall and frost conditions), but can also depend on other factors. Therefore, a thorough understanding of the influence of growth conditions on the nutritional composition and sensory perception of the citrus fruit is important. From a grower’s point of view, it would be ideal to have high yield as well as fruit with superior sensory qualities, such as appearance, taste, smell, and texture. Thus optimisation of fruit production and nutrient composition to create a fruit with desirable sensory qualities will increase the demand for the fruit worldwide, and allow the grower to obtain the highest price per kilogram of fruit. A popular method to increase fruit yield is to use fertilisers, either chemical (based on nitrogen, phosphorus, potassium, and sometimes sulphur) or organic (such as manure or compost). Chemical based fertilisers often contain micronutrients as well, ⇑ Corresponding author at: Department of Food Science and Technology, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA. Tel.: +1 530 752 6804; fax: +1 530 752 8966. E-mail address: [email protected] (C.M. Slupsky). 0308-8146/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.foodchem.2012.02.218
including zinc, manganese, iron, copper, molybdenum, chlorine and boron. It has been shown that micronutrient uptake and transport can be increased by application of fertiliser to leaves (Fang et al., 2008). For instance, it has been shown that the dose, form, and method of nitrogen application has a significant influence on the concentration of phytochemicals such as vitamins, phenolic compounds, and sugars in cabbage and sage (Geneva, Stancheva, Boychinova, Mincheva, & Yonova, 2010; Sady, DomagalaSwiatkiewicz, & Rozek, 2010). A foliar spray of zinc and manganese along with urea has been shown to significantly increase the concentration of these elements in citrus leaves (Tariq, Sharif, Shah, & Khan, 2007). In contrast, however, phosphorus fertilisation of tomato, either through soil or foliar spray, has not been shown to provide any changes in yield, and increases in fruit quality were shown to be marginal at best (Oke, Ahn, Schofield, & Paliyath, 2005). Pesticides are biologically active substances used to control insects and fungi. Uptake, translocation, and persistence of pesticides in plants may lead to high levels that are a hazard to human health and ecosystems, and considerable research has gone into understanding the effects of these pollutants in humans and the environment (Juraske, Castells, Vijay, Munoz, & Anton, 2009; Trapp, 2004). To eliminate losses in citrus due to pests such as insects (Aphytis melinus, citrus thrips, brown scale, citricola scale, and black scale), and fungi (such as sooty mold or root rot), insecticides or fungicides are often sprayed onto trees, which can be at any time of year
X. Zhang et al. / Food Chemistry 134 (2012) 1020–1024
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including while the tree is fruiting. While proper organic treatment of a plant can increase its biomass production, potentially resulting in a lower incidence of pest infestation (Hsu, Shen, & Hwang, 2009), these treatments can be expensive and time-consuming, and ultimately impact final yield. To date, no research has been done to assess the impact of foliar fertilisation or the spraying of pesticides on fruit nutrient composition. We have previously shown that rootstock, soil depth, and grove elevation have a significant impact on the chemical composition of mandarin oranges (Zhang, Breksa, Mishchuk, & Slupsky, 2011). In this study, the effects of foliar fertilisation and pesticide application during fruit formation on the nutritional composition of mandarin oranges are further examined. In addition, we assess whether the observed changes are large enough to be detected by the consumer.
2. Materials and methods 2.1. Plant materials Fruits (Owari selection of Satsuma mandarin ( Citrus unshiu Marcovitch)) from each of 11 different groves were harvested as previously described (Zhang et al., 2011). Data on the elevation, soil type, soil depth, type of rootstock, and geographical orientation of each grove were collected described elsewhere (Zhang et al., 2011). Data on the type and time of foliar fertilisation or pesticide application were also collected and used in analysis. 2.2. Sample preparation Healthy and undamaged fruits were taken from each location and randomly divided into three groups, where 10 fruit were used to prepare a juice sample for analysis as described (Zhang et al., 2011). For each grove, a total of four samples were utilised for metabolomics analysis; three samples were clarified juice, and the fourth was a replicate of the first filtered juice sample prepared from the frozen juice homogenate. 2.3. NMR data collection Samples were prepared by thawing, and centrifuging for 15 min at a maximum speed of 4 °C, to remove particulate matter. The supernatant was subsequently filtered through Omega-3 3000 MW cutoff filters (Pall Life Sciences, Ann Arbor, MI) to remove pectin, and samples were prepared for NMR analysis as described (Zhang et al., 2011). Distribution of soluble metabolites was primarily in the juice, as homogenisation of pulp/juice together produced the same metabolite profile as the sample of juice alone. Additionally, extraction of the pulp/juice using a methanol/chloroform extraction procedure did not alter the observed soluble metabolite profile. NMR spectra were acquired using a Bruker ‘noesypr1d’ experiment on a Bruker AVANCE 600 MHz spectrometer equipped with a SampleJet (Zhang et al., 2011). Metabolite identification and quantification was accomplished using Chenomx NMRSuite 6.1 (Chenomx Inc., Edmonton, Canada) (Weljie, Newton, Mercier, Carlson, & Slupsky, 2006), with a total of 29 compounds assigned and quantified (Zhang et al., 2011). Metabolite concentrations were subjected to log10 transformation, to account for non-normal distribution of the concentration data, and reduce the chance of skewed variables, and multivariate statistical data analyses (PCA and OPLS-DA) was performed using SIMCA-P (version 11, Umetrics, Umeå, Sweden), with mean centering and unit variance scaling applied. Significance testing, using Student’s t-test, was performed using Microsoft Excel. Significance was set at a = 0.05.
Fig. 1. Comparison of metabolic composition of orange juice taken from groves in which growers used foliar fertilisation (groves 2, 3, 9, and 11), and those that did not (groves 1, 4, 5, 6, 7, 8, and 10). (A) OPLS-DA (j, foliar fertilisation; s, no foliar fertilisation). (B) Loadings plot corresponding to (A). (C) Validation of PLS-DA analysis in (A) using permutation testing. R2 (s) is a measure of how well the model fits the data, and Q2 (j) is a measure of the predictive ability of the model. Both R2 and Q2 have positive slopes indicating a good model.
2.4. Sensory testing To determine whether consumers could detect the difference in sweetness/sourness based on the results of this study, two orange juice samples were prepared to resemble the sweet/sour taste balance observed. Since mandarin orange juice is not available commercially, and there was not sufficient mandarin juice available from this study to conduct taste panels, cartons of Florida’s Natural
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Table 1 Comparison of the metabolite concentrations of juice from oranges in which growers applied foliar fertilisers (groves 2, 3, 9, and 11) and those that did not (groves 1, 4, 5, 6, 7, 8, and 10). Metabolites
% Difference (none vs. foliar fertilisation)
p-Value
Asparagine Unk at 2.9 ppm Phenylalanine Threonine Histidine Aspartate Synephrine Adenosine Valine Fructose Glucose Sucrose Limonin Glucoside Ethanol
43.16 34.83 28.14 26.71 21.44 19.54 13.88 12.75 11.40 8.98 10.85 11.91 27.59 28.31
0.010 0.001 0.023 0.001 0.017 0.023 0.025 0.010 0.025 0.011 0.003 0.001 0.003 0.004
Premium orange juice (Florida’s Natural Growers, Citrus World, Inc., Lake Wales, FL) were purchased from a local grocery store and modified by adding 9.93 g/L of sucrose to reproduce juice with a similar Brix/acid ratio as observed with oranges produced with foliar fertilisation (‘FF’), and 17.46 g/L of sucrose to reproduce juice from oranges produced without foliar fertilisation (‘NFF’) (a difference of approximately 1 °Brix/acid). Sucrose alone was used to alter the °Brix in the commercial juice sample since the fructose and glucose concentrations in the commercial juice were approximately equal to their concentrations in the mandarin juice without FF. Preliminary testing indicated that the sour taste of juices ‘FF’ and ‘NFF’ was more salient than the sweet taste. The juices were refrigerated for storage, but presented at room temperature (21– 25 °C) as 10 mL aliquots in small plastic cups (30 mL, Solo Plastic Soufflés, Solo Cup Co., Highland Park, IL) In total, 100 subjects were recruited (61 F, 39 M, with age range 18–69 yrs) that included students and staff at the University of California, Davis. Once demographic details had been taken from each subject, they cleansed their mouth by rinsing thoroughly with purified water (Elga LabWater Prima 15 R.O.System; Siemens Water Technologies, Sacramento, CA; Inorganics >90% rejection, T.O.C <0.1 ppm) and were then given instructions. Having made sure that the subject understood the task, each subject proceeded with the test, taking a brief rinse before tasting each juice. Subjects were briefed beforehand that the sides of the tongue were the most sensitive to sourness and not to hold the juice in the mouth more than 2–3 s, so as to avoid adaptation effects. Each experimental session lasted 2–6 min. Each subject tested for discrimination between the two juices using the most statistically powerful and sensitive 2-AFC method (Dessirier & O’Mahony, 1999; Ennis, 1993) using an approach derived from earlier work on the effects of irradiation on oranges (O’Mahony and Goldstein, 1987a, 1987b; O’Mahony, Wong & Odbert, 1985). In summary, each subject was presented with a sample of each juice and was required to taste and report which of the two tasted more sour. They were allowed to expectorate or swallow the juice as desired. Further juice pairs were available for re-tasting as often as required so that subjects could be sure of their judgment. Juice pairs were always tasted from left to right so that a given subject always tasted juices ‘FF’ and ‘NFF’ in the same order. This order was counterbalanced over subjects, with juice ‘FF’ being on the right for half of the subjects, and on the left for the other half. Each subject gave his or her responses orally. 3. Results The same eleven mandarin orange groves as described in Zhang et al. (2011) were used to determine the effects of foliar fertilisation
Fig. 2. Comparison of metabolic composition of orange juice taken from groves in which growers used pesticide treatment during fruiting (groves 1, 2, 8, and 11), and those that did not (groves 5, 6, 9, and 10). (A) OPLS-DA (j, pesticide during fruit formation; s, no pesticide during fruit formation). (B) Loadings plot corresponding to (A). (C) Validation of PLS-DA analysis in (A) using permutation testing.
and pesticide use during fruiting on the nutritional quality of the oranges. Groves were divided into either those where the grower used foliar fertiliser (2, 3, 9, and 11), and those where the grower either did not use fertiliser, or used another method of fertilisation (1, 4, 5, 6, 7, 8, and 10). Careful attention was paid to ensure that average elevation (168–296 m for orchards in which foliar fertilisation
X. Zhang et al. / Food Chemistry 134 (2012) 1020–1024 Table 2 Comparison of the metabolite concentrations of juice from oranges in which growers applied pesticides during fruit formation (groves 1, 2, 8, and 11) and those that did not (groves 5, 6, 9, and 10). Metabolites
% Difference (none vs. pesticide during fruiting)
p-Value
Asparagine Proline Choline Phenylalanine 4-Aminobutyrate Arginine Aspartate Histidine Threonine myo-Inositol Sucrose Citrate Ascorbate
121.17 43.77 43.54 39.83 38.00 36.10 27.72 26.23 21.15 11.91 14.40 15.63 17.90
0.000 0.044 0.001 0.003 0.000 0.005 0.031 0.035 0.036 0.010 0.001 0.002 0.010
was used, and 122–282 m for orchards in which foliar fertilisation was not used), type of rootstock (both groups with C-35 and trifoliate rootstock), average soil depth (30–137 cm for most orchards in which foliar fertilisation was used, and 53–107 cm for orchards in which no foliar fertilisation was used (one orchard with 213 cm soil depth)), and use of pesticides (2 orchards in each group) was similar between both groups in the analysis. To determine whether there was a correlation between foliar fertilisation and metabolite composition of the juices, multivariate statistical analysis was employed. Fig. 1 shows an OPLS-DA scores plot with corresponding loadings plot illustrating complete discrimination between juices prepared from mandarin oranges obtained from trees in which foliar fertilisation was used versus those in which foliar fertilisation was not used indicating similar metabolite composition in each group. In general, trees grown with fertilisation tended to have higher concentration of amino acids (asparagine, phenylalanine, threonine, histidine, aspartate and valine), an unknown metabolite at 2.9 ppm, synephrine, and adenosine as well as lower concentrations of ethanol, limonin glucoside, and sugars (sucrose, glucose, and fructose) (Table 1). The largest difference was asparagine, with an increase of 43%, followed by the unknown metabolite at 2.9 ppm, with an increase of 35%, phenylalanine with 28%, and threonine with 27%. In addition, the average ethanol concentration decreased by 28%, together with the sugar concentration ( 12% for sucrose, 11% for glucose, and 9% for fructose). The average concentration of limonin glucoside also decreased by 28%. To explore the effect of the application of pesticides during fruit production on the metabolite concentration in the fruit, groves were divided into two groups. The first group had pesticide applied during the early stage of fruit formation (groves 1, 2, 8, and 11), while the other had no pesticide applied (groves 5, 6, 9, and 10). Similar characteristics of the groves were observed in both groups (elevation was 152–296 m for group not using pesticide, and 168– 229 m for group using pesticide; both groups had C35 and trifoliate rootstock; soil depth was 53–107 cm with one grove having 213 cm deep soil for group not using pesticide, and 30–107 cm for group using pesticide; three groves that used foliar fertiliser did not use pesticide, while two groups using foliar fertiliser used pesticide). Fig. 2 shows an OPLS-DA scores plot and corresponding loadings plot illustrating the metabolite differences between trees treated versus those not treated with pesticide during fruit formation. Table 2 illustrates that the largest variation is with asparagine,
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with a 121% higher concentration in trees treated with pesticides in comparison to trees not treated with pesticides. Other amino acids were higher in concentration in pesticide-treated fruit versus non-pesticide-treated fruit. Significant increases of choline (44%), 4-aminobutyrate (GABA) (38%) was also observed in pesticidetreated fruit. The average concentrations of vitamin C (ascorbate), citrate acid, sucrose and myo-inositol were lower in the pesticide-treated fruit (Table 2). Citrus juices are a complex mixture of flavour and taste components. Historically, the contributions of taste components such as sugar (sweet) and acid (sour) were understood before the impact of aroma volatiles due to their higher concentrations (Rouseff, Ruiz Perez-Cacho, & Jabalpurwala, 2009). To determine whether individuals could detect differences in relative sourness, as was observed in analytical measurement in this study, a sensory experiment employing 100 subjects was performed. As a first step, commercial orange juice was purchased, and the Brix/Acid ratio was adjusted to be similar to what was observed in fruit where trees had been sprayed with foliar fertiliser, and those not treated with foliar fertiliser, by adding a suitable amount of sucrose. A significant majority of subjects (68/100, binomial p = 0.0002) were able to determine that a difference between the two juices could be observed, and were able to correctly identify the juice with the higher sugar content. 4. Discussion It has previously been shown that fertilisation practices can increase yield and change the nutrient composition of fruits and vegetables (Fang et al., 2008; Geneva et al., 2010; Oke et al., 2005; Sady et al., 2010; Tariq et al., 2007), and that sucrose accumulation may be related to nutrient and water availability (Souty, Reich, & Albagnac, 1999). The results presented herein confirm that foliar fertilisation affects nutrient composition of Satsuma mandarin oranges. In particular, the mandarin oranges significantly accumulated amino acids. However, sugars were not increased. It has been shown that overall consumer preference is related to fruit sweetness, with an increase in sourness related to consumer aversion (Tietel et al., 2010). In this study, it was shown that consumers can detect a difference of as little as 1 °Brix in orange juice, and can determine whether the juice is more sour or less sweet. This study provides evidence that the farming practices of the grower can impact the ultimate sensory characteristics of the resulting fruit. Indeed, the application of foliar fertiliser and/or the use of pesticides during fruit formation may not be an attractive way to achieve high fruit quality from the consumer’s standpoint. These results are significant, as it has not been previously shown that differences in fertilisation and/or pesticide use affect taste. In this study, we used 1H NMR to compare the metabolite profiles obtained for Satsuma mandarin orange juices prepared from fruit harvested in eleven separate groves, to determine whether factors such as the application of foliar fertilisation or pesticides would significantly alter the metabolite concentration of the juices. Both foliar fertilisation and pesticides lowered the Brix/acid ratio, and caused major changes to amino acid levels as well as levels of other organic molecules. We tested whether a Brix/acid ratio change of 1 unit would be detectable by an untrained set of subjects, and 68% of subjects clearly identified which juice had a higher sour content. Given that farming practices affect the final product, these results provide evidence that metabolomic analysis may be useful to optimise fertiliser and pesticide use to obtain an optimal sensory profile so citrus producers can remain competitive on the global market.
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References Blauer, R. (2010). July 2010 Citrus Update. USDA, Foreign Agricultural Service. 3. Dessirier, J. M., & O’Mahony, M. (1999). Comparison of d’ values for the 2-AFC (paired comparison) and 3-AFC discrimination methods: Thurstonian models, sequential sensitivity analysis and power. Food Quality and Preference, 10(1), 51–58. Ennis, D. M. (1993). The power of sensory discrimination methods. Journal of Sensory Studies, 8(4), 353–370. Fang, Y., Wang, L., Xin, Z., Zhao, L., An, X., & Hu, Q. (2008). Effect of foliar application of zinc, selenium, and iron fertilizers on nutrients concentration and yield of rice grain in China. Journal of Agriculture and Food Chemistry, 56(6), 2079–2084. Geneva, M. P., Stancheva, I. V., Boychinova, M. M., Mincheva, N. H., & Yonova, P. A. (2010). Effects of foliar fertilization and arbuscular mycorrhizal colonization on Salvia officinalis L. growth, antioxidant capacity, and essential oil composition. Journal of the Science of Food and Agriculture, 90(4), 696–702. Hsu, Y. T., Shen, T. C., & Hwang, S. Y. (2009). Soil fertility management and pest responses: A comparison of organic and synthetic fertilization. Journal of Economic Entomology, 102(1), 160–169. Juraske, R., Castells, F., Vijay, A., Munoz, P., & Anton, A. (2009). Uptake and persistence of pesticides in plants: Measurements and model estimates for imidacloprid after foliar and soil application. Journal of Hazardous Materials, 165(1–3), 683–689. Oke, M., Ahn, T., Schofield, A., & Paliyath, G. (2005). Effects of phosphorus fertilizer supplementation on processing quality and functional food ingredients in tomato. Journal of Agriculture and Food Chemistry, 53(5), 1531–1538. O’Mahony, M., & Goldstein, L. R. (1987a). Methods of sensory evaluation of Navel oranges treated with electron beam irradiation. LWT – Food Science and Technology, 20, 78–82.
O’Mahony, M., & Goldstein, L. R. (1987b). Sensory techniques for measuring differences in California Navel oranges treated with doses of gamma-radiation below 0.6 Kgray. Journal of Food Science, 52, 348–352. O’Mahony, M., Wong, S.-Y., & Odbert, N. (1985). Sensory evaluation of Navel oranges treated with low doses of gamma-irradiation. Journal of Food Science, 50, 639–646. Rouseff, R. L., Ruiz Perez-Cacho, P., & Jabalpurwala, F. (2009). Historical review of citrus flavor research during the past 100 years. Journal of Agriculture and Food Chemistry, 57(18), 8115–8124. Sady, W., Domagala-Swiatkiewicz, I., & Rozek, S. (2010). Effect of nitrogen fertilization on sugars, ascorbic acid and phenolic compounds in white cabbage (Brassica oleracea var. capitata alba L.). Acta Scientiarum PolonorumHortorum Cultus, 9(4), 41–51. Souty, M. G. M., Reich, M. Albagnac, G. (1999). Effect of assimilate supply on peach fruit maturation and quality. Canadian Journal of Plant Science, 79(2), 259–268. Tariq, M., Sharif, M., Shah, Z., & Khan, R. (2007). Effect of foliar application of micronutrients on the yield and quality of sweet orange (Citrus sinensis L.). Pakistan Journal of Biological Sciences, 10(11), 1823–1828. Tietel, Z., Bar, E., Lewinsohn, E., Feldmesser, E., Fallik, E., & Porat, R. (2010). Effects of wax coatings and postharvest storage on sensory quality and aroma volatile composition of ‘Mor’ mandarins. Journal of the Science of Food and Agriculture, 90(6), 995–1007. Trapp, S. (2004). Plant uptake and transport models for neutral and ionic chemicals. Environmental Science and Pollution Research International, 11(1), 33–39. Weljie, A. M., Newton, J., Mercier, P., Carlson, E., & Slupsky, C. M. (2006). Targeted profiling: Quantitative analysis of 1H NMR metabolomics data. Analytical Chemistry, 78(13), 4430–4442. Zhang, X., Breksa, A. P., 3rd, Mishchuk, D. O., & Slupsky, C. M. (2011). Elevation, rootstock, and soil depth affect the nutritional quality of mandarin oranges. Journal of Agriculture and Food Chemistry, 59(6), 2672–2679.
Contents lists available at SciVerse ScienceDirect
Food Chemistry journal homepage: www.elsevier.com/locate/foodchem
Fertilisation and pesticides affect mandarin orange nutrient composition Xiaotian Zhang a, Andrew P. Breksa III c, Darya O. Mishchuk a, Cindy E. Fake d, Michael A. O’Mahony a, Carolyn M. Slupsky a,b,⇑ a
Department of Food Science and Technology, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA Department of Nutrition, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA c Western Regional Research Center, Agricultural Research Service, United States Department of Agriculture, 800 Buchanan St., Albany, CA 94710, USA d UC Cooperative Extension, Placer and Nevada Counties, 11477 E Avenue, Auburn, CA 95603, USA b
a r t i c l e
i n f o
Article history: Received 26 August 2011 Received in revised form 6 February 2012 Accepted 28 February 2012 Available online 8 March 2012 Keywords: NMR Citrus Mandarin orange Satsuma Foliar fertilisation Pesticide Metabolomics
a b s t r a c t The effects of the application of foliar fertilisation and pesticide on nutritional quality of mandarin orange juices were evaluated using 1H NMR metabolomics. Significant differences between the use of fertiliser and pesticides during fruit formation were observed, and included changes in sugar, amino acid and organic acid composition. To determine whether the difference in sugar concentration was enough for the consumer to detect, a sensory experiment was performed in which two orange juice samples were prepared to resemble the sweet/sour taste balance of juice from mandarin oranges in which foliar fertilisation was either applied or not. In a test using non-trained individuals, 68% could correctly identify which juice had a sourer, or less sweet, taste. The implications of this study could impact citrus growers, and ultimately aid in development of fruit with superior sensory quality. Ó 2012 Elsevier Ltd. All rights reserved.
1. Introduction Citrus is an important horticultural crop, with worldwide agricultural production over 82 million metric tons per year (Blauer, 2010). Oranges represent a significant part of California’s citrus economy with more than 80% going to the fresh market, depending on the quality of the crop. Crop quality can depend on the growing season (i.e. rainfall and frost conditions), but can also depend on other factors. Therefore, a thorough understanding of the influence of growth conditions on the nutritional composition and sensory perception of the citrus fruit is important. From a grower’s point of view, it would be ideal to have high yield as well as fruit with superior sensory qualities, such as appearance, taste, smell, and texture. Thus optimisation of fruit production and nutrient composition to create a fruit with desirable sensory qualities will increase the demand for the fruit worldwide, and allow the grower to obtain the highest price per kilogram of fruit. A popular method to increase fruit yield is to use fertilisers, either chemical (based on nitrogen, phosphorus, potassium, and sometimes sulphur) or organic (such as manure or compost). Chemical based fertilisers often contain micronutrients as well, ⇑ Corresponding author at: Department of Food Science and Technology, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA. Tel.: +1 530 752 6804; fax: +1 530 752 8966. E-mail address: [email protected] (C.M. Slupsky). 0308-8146/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.foodchem.2012.02.218
including zinc, manganese, iron, copper, molybdenum, chlorine and boron. It has been shown that micronutrient uptake and transport can be increased by application of fertiliser to leaves (Fang et al., 2008). For instance, it has been shown that the dose, form, and method of nitrogen application has a significant influence on the concentration of phytochemicals such as vitamins, phenolic compounds, and sugars in cabbage and sage (Geneva, Stancheva, Boychinova, Mincheva, & Yonova, 2010; Sady, DomagalaSwiatkiewicz, & Rozek, 2010). A foliar spray of zinc and manganese along with urea has been shown to significantly increase the concentration of these elements in citrus leaves (Tariq, Sharif, Shah, & Khan, 2007). In contrast, however, phosphorus fertilisation of tomato, either through soil or foliar spray, has not been shown to provide any changes in yield, and increases in fruit quality were shown to be marginal at best (Oke, Ahn, Schofield, & Paliyath, 2005). Pesticides are biologically active substances used to control insects and fungi. Uptake, translocation, and persistence of pesticides in plants may lead to high levels that are a hazard to human health and ecosystems, and considerable research has gone into understanding the effects of these pollutants in humans and the environment (Juraske, Castells, Vijay, Munoz, & Anton, 2009; Trapp, 2004). To eliminate losses in citrus due to pests such as insects (Aphytis melinus, citrus thrips, brown scale, citricola scale, and black scale), and fungi (such as sooty mold or root rot), insecticides or fungicides are often sprayed onto trees, which can be at any time of year
X. Zhang et al. / Food Chemistry 134 (2012) 1020–1024
1021
including while the tree is fruiting. While proper organic treatment of a plant can increase its biomass production, potentially resulting in a lower incidence of pest infestation (Hsu, Shen, & Hwang, 2009), these treatments can be expensive and time-consuming, and ultimately impact final yield. To date, no research has been done to assess the impact of foliar fertilisation or the spraying of pesticides on fruit nutrient composition. We have previously shown that rootstock, soil depth, and grove elevation have a significant impact on the chemical composition of mandarin oranges (Zhang, Breksa, Mishchuk, & Slupsky, 2011). In this study, the effects of foliar fertilisation and pesticide application during fruit formation on the nutritional composition of mandarin oranges are further examined. In addition, we assess whether the observed changes are large enough to be detected by the consumer.
2. Materials and methods 2.1. Plant materials Fruits (Owari selection of Satsuma mandarin ( Citrus unshiu Marcovitch)) from each of 11 different groves were harvested as previously described (Zhang et al., 2011). Data on the elevation, soil type, soil depth, type of rootstock, and geographical orientation of each grove were collected described elsewhere (Zhang et al., 2011). Data on the type and time of foliar fertilisation or pesticide application were also collected and used in analysis. 2.2. Sample preparation Healthy and undamaged fruits were taken from each location and randomly divided into three groups, where 10 fruit were used to prepare a juice sample for analysis as described (Zhang et al., 2011). For each grove, a total of four samples were utilised for metabolomics analysis; three samples were clarified juice, and the fourth was a replicate of the first filtered juice sample prepared from the frozen juice homogenate. 2.3. NMR data collection Samples were prepared by thawing, and centrifuging for 15 min at a maximum speed of 4 °C, to remove particulate matter. The supernatant was subsequently filtered through Omega-3 3000 MW cutoff filters (Pall Life Sciences, Ann Arbor, MI) to remove pectin, and samples were prepared for NMR analysis as described (Zhang et al., 2011). Distribution of soluble metabolites was primarily in the juice, as homogenisation of pulp/juice together produced the same metabolite profile as the sample of juice alone. Additionally, extraction of the pulp/juice using a methanol/chloroform extraction procedure did not alter the observed soluble metabolite profile. NMR spectra were acquired using a Bruker ‘noesypr1d’ experiment on a Bruker AVANCE 600 MHz spectrometer equipped with a SampleJet (Zhang et al., 2011). Metabolite identification and quantification was accomplished using Chenomx NMRSuite 6.1 (Chenomx Inc., Edmonton, Canada) (Weljie, Newton, Mercier, Carlson, & Slupsky, 2006), with a total of 29 compounds assigned and quantified (Zhang et al., 2011). Metabolite concentrations were subjected to log10 transformation, to account for non-normal distribution of the concentration data, and reduce the chance of skewed variables, and multivariate statistical data analyses (PCA and OPLS-DA) was performed using SIMCA-P (version 11, Umetrics, Umeå, Sweden), with mean centering and unit variance scaling applied. Significance testing, using Student’s t-test, was performed using Microsoft Excel. Significance was set at a = 0.05.
Fig. 1. Comparison of metabolic composition of orange juice taken from groves in which growers used foliar fertilisation (groves 2, 3, 9, and 11), and those that did not (groves 1, 4, 5, 6, 7, 8, and 10). (A) OPLS-DA (j, foliar fertilisation; s, no foliar fertilisation). (B) Loadings plot corresponding to (A). (C) Validation of PLS-DA analysis in (A) using permutation testing. R2 (s) is a measure of how well the model fits the data, and Q2 (j) is a measure of the predictive ability of the model. Both R2 and Q2 have positive slopes indicating a good model.
2.4. Sensory testing To determine whether consumers could detect the difference in sweetness/sourness based on the results of this study, two orange juice samples were prepared to resemble the sweet/sour taste balance observed. Since mandarin orange juice is not available commercially, and there was not sufficient mandarin juice available from this study to conduct taste panels, cartons of Florida’s Natural
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Table 1 Comparison of the metabolite concentrations of juice from oranges in which growers applied foliar fertilisers (groves 2, 3, 9, and 11) and those that did not (groves 1, 4, 5, 6, 7, 8, and 10). Metabolites
% Difference (none vs. foliar fertilisation)
p-Value
Asparagine Unk at 2.9 ppm Phenylalanine Threonine Histidine Aspartate Synephrine Adenosine Valine Fructose Glucose Sucrose Limonin Glucoside Ethanol
43.16 34.83 28.14 26.71 21.44 19.54 13.88 12.75 11.40 8.98 10.85 11.91 27.59 28.31
0.010 0.001 0.023 0.001 0.017 0.023 0.025 0.010 0.025 0.011 0.003 0.001 0.003 0.004
Premium orange juice (Florida’s Natural Growers, Citrus World, Inc., Lake Wales, FL) were purchased from a local grocery store and modified by adding 9.93 g/L of sucrose to reproduce juice with a similar Brix/acid ratio as observed with oranges produced with foliar fertilisation (‘FF’), and 17.46 g/L of sucrose to reproduce juice from oranges produced without foliar fertilisation (‘NFF’) (a difference of approximately 1 °Brix/acid). Sucrose alone was used to alter the °Brix in the commercial juice sample since the fructose and glucose concentrations in the commercial juice were approximately equal to their concentrations in the mandarin juice without FF. Preliminary testing indicated that the sour taste of juices ‘FF’ and ‘NFF’ was more salient than the sweet taste. The juices were refrigerated for storage, but presented at room temperature (21– 25 °C) as 10 mL aliquots in small plastic cups (30 mL, Solo Plastic Soufflés, Solo Cup Co., Highland Park, IL) In total, 100 subjects were recruited (61 F, 39 M, with age range 18–69 yrs) that included students and staff at the University of California, Davis. Once demographic details had been taken from each subject, they cleansed their mouth by rinsing thoroughly with purified water (Elga LabWater Prima 15 R.O.System; Siemens Water Technologies, Sacramento, CA; Inorganics >90% rejection, T.O.C <0.1 ppm) and were then given instructions. Having made sure that the subject understood the task, each subject proceeded with the test, taking a brief rinse before tasting each juice. Subjects were briefed beforehand that the sides of the tongue were the most sensitive to sourness and not to hold the juice in the mouth more than 2–3 s, so as to avoid adaptation effects. Each experimental session lasted 2–6 min. Each subject tested for discrimination between the two juices using the most statistically powerful and sensitive 2-AFC method (Dessirier & O’Mahony, 1999; Ennis, 1993) using an approach derived from earlier work on the effects of irradiation on oranges (O’Mahony and Goldstein, 1987a, 1987b; O’Mahony, Wong & Odbert, 1985). In summary, each subject was presented with a sample of each juice and was required to taste and report which of the two tasted more sour. They were allowed to expectorate or swallow the juice as desired. Further juice pairs were available for re-tasting as often as required so that subjects could be sure of their judgment. Juice pairs were always tasted from left to right so that a given subject always tasted juices ‘FF’ and ‘NFF’ in the same order. This order was counterbalanced over subjects, with juice ‘FF’ being on the right for half of the subjects, and on the left for the other half. Each subject gave his or her responses orally. 3. Results The same eleven mandarin orange groves as described in Zhang et al. (2011) were used to determine the effects of foliar fertilisation
Fig. 2. Comparison of metabolic composition of orange juice taken from groves in which growers used pesticide treatment during fruiting (groves 1, 2, 8, and 11), and those that did not (groves 5, 6, 9, and 10). (A) OPLS-DA (j, pesticide during fruit formation; s, no pesticide during fruit formation). (B) Loadings plot corresponding to (A). (C) Validation of PLS-DA analysis in (A) using permutation testing.
and pesticide use during fruiting on the nutritional quality of the oranges. Groves were divided into either those where the grower used foliar fertiliser (2, 3, 9, and 11), and those where the grower either did not use fertiliser, or used another method of fertilisation (1, 4, 5, 6, 7, 8, and 10). Careful attention was paid to ensure that average elevation (168–296 m for orchards in which foliar fertilisation
X. Zhang et al. / Food Chemistry 134 (2012) 1020–1024 Table 2 Comparison of the metabolite concentrations of juice from oranges in which growers applied pesticides during fruit formation (groves 1, 2, 8, and 11) and those that did not (groves 5, 6, 9, and 10). Metabolites
% Difference (none vs. pesticide during fruiting)
p-Value
Asparagine Proline Choline Phenylalanine 4-Aminobutyrate Arginine Aspartate Histidine Threonine myo-Inositol Sucrose Citrate Ascorbate
121.17 43.77 43.54 39.83 38.00 36.10 27.72 26.23 21.15 11.91 14.40 15.63 17.90
0.000 0.044 0.001 0.003 0.000 0.005 0.031 0.035 0.036 0.010 0.001 0.002 0.010
was used, and 122–282 m for orchards in which foliar fertilisation was not used), type of rootstock (both groups with C-35 and trifoliate rootstock), average soil depth (30–137 cm for most orchards in which foliar fertilisation was used, and 53–107 cm for orchards in which no foliar fertilisation was used (one orchard with 213 cm soil depth)), and use of pesticides (2 orchards in each group) was similar between both groups in the analysis. To determine whether there was a correlation between foliar fertilisation and metabolite composition of the juices, multivariate statistical analysis was employed. Fig. 1 shows an OPLS-DA scores plot with corresponding loadings plot illustrating complete discrimination between juices prepared from mandarin oranges obtained from trees in which foliar fertilisation was used versus those in which foliar fertilisation was not used indicating similar metabolite composition in each group. In general, trees grown with fertilisation tended to have higher concentration of amino acids (asparagine, phenylalanine, threonine, histidine, aspartate and valine), an unknown metabolite at 2.9 ppm, synephrine, and adenosine as well as lower concentrations of ethanol, limonin glucoside, and sugars (sucrose, glucose, and fructose) (Table 1). The largest difference was asparagine, with an increase of 43%, followed by the unknown metabolite at 2.9 ppm, with an increase of 35%, phenylalanine with 28%, and threonine with 27%. In addition, the average ethanol concentration decreased by 28%, together with the sugar concentration ( 12% for sucrose, 11% for glucose, and 9% for fructose). The average concentration of limonin glucoside also decreased by 28%. To explore the effect of the application of pesticides during fruit production on the metabolite concentration in the fruit, groves were divided into two groups. The first group had pesticide applied during the early stage of fruit formation (groves 1, 2, 8, and 11), while the other had no pesticide applied (groves 5, 6, 9, and 10). Similar characteristics of the groves were observed in both groups (elevation was 152–296 m for group not using pesticide, and 168– 229 m for group using pesticide; both groups had C35 and trifoliate rootstock; soil depth was 53–107 cm with one grove having 213 cm deep soil for group not using pesticide, and 30–107 cm for group using pesticide; three groves that used foliar fertiliser did not use pesticide, while two groups using foliar fertiliser used pesticide). Fig. 2 shows an OPLS-DA scores plot and corresponding loadings plot illustrating the metabolite differences between trees treated versus those not treated with pesticide during fruit formation. Table 2 illustrates that the largest variation is with asparagine,
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with a 121% higher concentration in trees treated with pesticides in comparison to trees not treated with pesticides. Other amino acids were higher in concentration in pesticide-treated fruit versus non-pesticide-treated fruit. Significant increases of choline (44%), 4-aminobutyrate (GABA) (38%) was also observed in pesticidetreated fruit. The average concentrations of vitamin C (ascorbate), citrate acid, sucrose and myo-inositol were lower in the pesticide-treated fruit (Table 2). Citrus juices are a complex mixture of flavour and taste components. Historically, the contributions of taste components such as sugar (sweet) and acid (sour) were understood before the impact of aroma volatiles due to their higher concentrations (Rouseff, Ruiz Perez-Cacho, & Jabalpurwala, 2009). To determine whether individuals could detect differences in relative sourness, as was observed in analytical measurement in this study, a sensory experiment employing 100 subjects was performed. As a first step, commercial orange juice was purchased, and the Brix/Acid ratio was adjusted to be similar to what was observed in fruit where trees had been sprayed with foliar fertiliser, and those not treated with foliar fertiliser, by adding a suitable amount of sucrose. A significant majority of subjects (68/100, binomial p = 0.0002) were able to determine that a difference between the two juices could be observed, and were able to correctly identify the juice with the higher sugar content. 4. Discussion It has previously been shown that fertilisation practices can increase yield and change the nutrient composition of fruits and vegetables (Fang et al., 2008; Geneva et al., 2010; Oke et al., 2005; Sady et al., 2010; Tariq et al., 2007), and that sucrose accumulation may be related to nutrient and water availability (Souty, Reich, & Albagnac, 1999). The results presented herein confirm that foliar fertilisation affects nutrient composition of Satsuma mandarin oranges. In particular, the mandarin oranges significantly accumulated amino acids. However, sugars were not increased. It has been shown that overall consumer preference is related to fruit sweetness, with an increase in sourness related to consumer aversion (Tietel et al., 2010). In this study, it was shown that consumers can detect a difference of as little as 1 °Brix in orange juice, and can determine whether the juice is more sour or less sweet. This study provides evidence that the farming practices of the grower can impact the ultimate sensory characteristics of the resulting fruit. Indeed, the application of foliar fertiliser and/or the use of pesticides during fruit formation may not be an attractive way to achieve high fruit quality from the consumer’s standpoint. These results are significant, as it has not been previously shown that differences in fertilisation and/or pesticide use affect taste. In this study, we used 1H NMR to compare the metabolite profiles obtained for Satsuma mandarin orange juices prepared from fruit harvested in eleven separate groves, to determine whether factors such as the application of foliar fertilisation or pesticides would significantly alter the metabolite concentration of the juices. Both foliar fertilisation and pesticides lowered the Brix/acid ratio, and caused major changes to amino acid levels as well as levels of other organic molecules. We tested whether a Brix/acid ratio change of 1 unit would be detectable by an untrained set of subjects, and 68% of subjects clearly identified which juice had a higher sour content. Given that farming practices affect the final product, these results provide evidence that metabolomic analysis may be useful to optimise fertiliser and pesticide use to obtain an optimal sensory profile so citrus producers can remain competitive on the global market.
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