Mais les résultats doivent être attendus longtemps et il n'y a généralement pas de temps amoxicilline prix L'autre cas, c'est que l'achat d'un ou d'un autre antibiotique dans une pharmacie classique nécessite des dépenses matérielles considérables et pas toutes les personnes ne peuvent acheter des produits pharmaceutiques aussi coûteux.
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Effects of Organic Fertilisation on ‘Valencia late’ Orange Bearing Trees
B. Torrisi, P. Rapisarda and F. Intrigliolo
CRA - Research Centre for the Soil Plant System (CRA-RPS)
δ15N, leaf analysis, fruit quality, canonical discriminant analysis
In a study realised over a three year period on orange bearing trees (Citrus
sinensis (L.) Osbeck) ‘Valencia late’, grafted on sour orange (C. aurantium L.), the
effect of organic fertilisers (OF) on plant nutrition and performance was verified. In a
randomized block experimental design, four treatments were compared, namely:
mineral fertiliser (MF) treatment adopted as control, citrus byproduct compost (CB),
poultry manure (PM) and livestock waste compost (LW). The trees, with the exception
of (MF) treatment, were organically grown since 1994 in the experimental farm of
CRA-ACM in Lentini, Sicily, and received the same N input every year.
Significant differences for micronutrients (Fe, Mn, Zn) were noticed in leaf
analyses, whereas no difference was found between treatments for leaf macronutrient
content. The δ15N detected in leaves, proteins of pulp and amino acids of juice showed
the lower level in MF, an intermediate value in CB and the highest level in animal
derived fertilisers treatments (PM and LW). Fruit of the CB treatment showed values
of total soluble solids and total acidity significantly lower than other treatments.
Orange peel Chroma C* in CB and MF was higher than in PM and LW treatments.
Discriminant analysis of the leaf and fruit analytical data set successfully
separated treatments. First discriminant canonical function explains the 96,9% of the
variability, with highly significant Wilks’ lambda. Cross validation classified correctly
all MF and CB samples, whereas PM and LW in few cases were mixed up.
Despite the increase of importance of organic citrus industry, the behavior of
organic fertilisers (OF) and their ability either to satisfy orange trees nutrients
requirements and to optimize soil properties are not yet well known, especially for orange
bearing trees which have high nutrients demand (Canali, 2003).
The large increase of organic citrus industry in Italy and the shortage of data on
long term application of organic fertilisers (OF) in citrus groves soils imply the necessity
to identify agro-ecologic markers for either management control and fruit traceability.
The aim of the study was to: i) verify OF effects on orange trees nutritional status,
yield and fruit quality and ii) select plant and fruit parameters useful for organic citrus
MATERIALS AND METHODS
The study was realised between 2003 and 2006 in CRA-ACM experimental farm
“Palazzelli”, eastern Sicily (37°17’56”76N; 14°50’29”76E), in a 2 ha “Valencia late”
sweet orange orchard (Citrus sinensis
(L) Osbeck), grafted on sour orange (C. aurantium
L.), planted in a 6×4 m design on a sandy loam soil.
Proc. XXVIIIth IHC – IS on Organic Horticulture:
Four fertiliser treatments were applied: citrus by-products compost (CB), poultry
manure (PM), livestock waste compost (LW) and mineral fertiliser (MF), as control. The
trees, with the exception of MF treatment, were organically grown since 1994 and
received annually the same N input. Treatments were distributed in three blocks of 4 plots
of 60 plants each; in each block 8 index plants were selected for all soil and plant material
Plant nutritional status was determined by foliar analysis performed on 80 spring-
cycle leaves of the index trees collected in each plot in October from terminal, non-
fruiting shoots (Embleton et al., 1973). Total yield was recorded in field for each index
plant. Mean weight and fruit physical and chemical parameters were determined in a
sample of 40 fruits collected at harvest from the outer part of the canopy of the index
trees. The leaves were: i) washed in tap water by rubbing both sides using cheesecloth,
ii) rinsed in deionised water, iii) oven dried at 65°C for 72 h, iv) ground and v) dried at
105°C for 4 h. The concentration of N was determined on 1 g of ground leaf tissue using
the micro-Kjeldahl method (Büchi Distillation Unit K370). Another 1 g of ground leaf
tissue was ashed in a muffle furnace at 550°C for 12 h. After incineration and extraction
with nitric acid (1% v/v), P, K, Ca, Mg, Fe, Zn and Mn were determined using inductive
coupled plasma-optical emission spectrometry (ICP-OES; OPTIMA 2000DV, Perkin-
On each fruit sample, physical parameters (firmness, fruit weight, width of the
central axis, and peel thickness) were measured using standard methods (Wardowski et
al., 1979). Fruit color measurements were realized with a portable spectrophotometer
(CM-2550d, Konica Minolta Italia). Each sample of fruits was squeezed, and juice
content, total acidity (TA) and total soluble solids (TSS) were determined. Vitamin C was
analyzed by high-performance liquid chromatography (HPLC) (Rapisarda and Intelisano,
1996). Synephrine content was determined by the HPLC method described by Rapisarda
Measurement of the 15N/14N ratio of leaves, pulp and amino acids of juice were
realized following the methods described by Bricout and Koziet (1987) with slight
modification. For the measurement, an isotope ratio mass spectrometer (Delta plus XP
ThermoFinnigan, Bremen, Germany) equipped with an elemental analyzer (EA Flash
1112 ThermoFinnigan) was used. The values were expressed in δ‰ against international
standards (air for δ15N). The isotopic values were calculated against working in-house
standards (mainly casein), calibrated against L-glutamic acid USGS 40. The uncertainty
ANOVA was performed and mean values separated with Tukey HSD test (SPSS
package ver. 18). Moreover, data were processed by means of canonical discriminant
analysis (CDA) to evaluate all parameters at the same time and detect those that mostly
RESULTS AND DISCUSSION
No significant difference between treatments was noticed for leaf N, K and P
contents, whereas significant differences for Ca, Mg and micronutrients were observed in
leaf analyses (Table 1). Ca content was higher in CB only in respect to LW; the latter also
showed Mg values lower than other treatments. All values for macronutrients were in the
optimal range according to the international standard for diagnosing nutritional status
CB leaves constantly showed higher micronutrient content, in the case of iron
compared to PM and LW, for manganese compared to PM and for zinc compared to MF.
Even though leaf levels of Mn and Zn were deficient, no deficiency symptoms were
No significant difference was noticed for yield (Table 2). Regarding fruit quality
parameters, CB treatment showed values of total soluble solids and total acidity lower
than other treatments; this result had no relevance on maturity index (TSS/TA). Total N
content in juice was higher in LW and MF compared to PM and CB treatments. Orange
peel Chroma C* in CB and MF was higher than in LW treatment; PM showed the lowest
value. No difference among treatments was recorded for fruit weight, firmness, peel
thickness, central axis, juice content, vitamin C and synephrine (data not shown).
The δ15N detected in leaves (Table 1) and amino acids of juice (Table 2) showed
the lowest level in MF, an intermediate value in CB and the higher level in animal derived
fertilisers (PM and LW). In the case of δ15N in proteins of pulp the complete separation
Discriminant analysis of overall leaf and fruit analytical data set successfully
separated treatments. First discriminant canonical function explains 96.9% of the
variability with highly significant Wilks’ lambda (Table 3). Values indicate the weight of
each variable on separation between groups for each discriminant function. Pulp δ15N,
leaf N and K levels and juice acidity showed higher relative weights.
Standardized discriminant canonical scores of function 1 and 2 are plotted in
Figure 1. Distribution of points allows visualizing clearly the separation of groups, and
the predominant effect of function 1. PM and LW treatments were not clearly
differentiated. As a matter of fact cross validation classified correctly all MF and CB
samples (100% of cases) whereas PM and LW were mixed up in few cases.
Organic fertilisers showed to assure in the medium period a balanced nutritional
status of citrus trees, comparable to mineral fertilisers. The compost from citrus by-
products (CB) seemed to have higher nutrient use efficiency, probably due to the effect of
higher organic matter addition and the related effects on soil biological fertility
(Srivastava et al., 2002; Toselli, 2010).
OF treatments showed yield levels similar to MF, thus demonstrating that fertiliser
treatments did not affect productivity, whereas some fruit quality parameters were
The fertilization regimens may be sufficient to produce differences between
treatments if levels of N-containing compounds vary, but in our experiment no differences
were observed in synephrine content between organic and conventional fruits with equal
level of total N applied to the different plots. 15N tracing in plots fertilised with animal by-
products (PM and LW) showed some differences with plant derived fertiliser (CB), but
main differences were noticed in the comparison all OF with synthetic mineral fertiliser.
Multivariate approach by means of discriminant analysis succeeded to highlight
the effects of fertiliser treatments namely, mineral, plant based organic and animal based
organic fertilisation. δ15N was confirmed to be a good indicator for management
discrimination (Rapisarda et al., 2005, 2010), but few other leaf (N, K) and fruit
parameters (acidity) affected the separation between data sets, too.
This study was realized in the project “Advanced Researches in Citriculture and
their applications” (RAVAGRU) funded by the Italian Ministry of Agriculture, Food and
Forestry Policies (MiPAAF) -
Pub. No. 41.
Bricout, J. and Koziet, J. 1987. Control of authenticity of orange juice by isotopic
analysis. J. Agric. Food Chem. 35:758-760.
Canali, S. 2003. Soil quality of organically managed citrus orchards in the Mediterranean
area. p.115 125. In Organic Agriculture: Sustainability, Markets and Policies. OECD,
Embleton, T.W., Jones, W.W., Labanauskas, C.K. and Reuther, W. 1973. Leaf analysis as
a diagnostic tool and guide for fertilization. p.183-210. In: W. Reuther (ed.), The
Citrus Industry, Vol. III, Production Technology, University of California, CA.
Rapisarda, P. and Intelisano, S. 1996. Sample preparation for vitamin C analysis of
pigmented orange juices. Ital. J. Food Sci. 3:251-256.
Rapisarda, P., Calabretta, M.L., Romano, G. and Intrigliolo, F. 2005. Nitrogen metabolism
components as a tool to discriminate between organic and conventional citrus fruits. J.
Rapisarda, P., Camin, F., Faedi, W., Paoletti, F. and Tobileo, M.R. 2010. New markers for
the traceability of organic fruit. Acta Hort. 873:173-183.
Srivastava, A.K., Singh, S. and Marathe, R.H. 2002. Organic citrus: soil fertility and plant
Toselli, M. 2010. Nutritional implications of organic management in fruit tree production.
Wardowski, W., Soule, J., Grierson, W. and Westbrook, G. 1979. Minimum Quality
(Maturity) Standards. In: Florida Citrus Quality Tests; Florida Cooperative Extension
Service, IFAS, University of Florida: FL.
Table 1. Leaf analysis results on dry matter basis (mean of 3 years).
1 Mean separation at 5% level with Tukey HSD test. Table 2. Values of yield and main fruit parameters (mean of 3 years).
1 Mean separation at 5% level with Tukey HSD test.
Table 3. Standardized canonical discriminant function coefficients.
Fig. 1. Canonical discriminant functions 1 vs. 2.
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Pharm World Sci (2006) 28:239–247DOI 10.1007/s11096-006-9023-9Drug-related problems in patients with angina pectoris, type 2diabetes and asthma – interviewing patients at homeLotte Stig Haugbølle Æ Ellen Westh SørensenReceived: 12 January 2006 / Accepted: 12 April 2006 / Published online: 26 October 2006Ó Springer Science+Business Media B.V. 2006‘‘Other problems’’ (such as limi