LIBRO-CONGRESO-CITRUS

S22
demand is growing due to knowledge of pomegranates’ nutritional benefits and functional food qualities. In
this paper, we analyze the different techno-economic aspects of citrus and pomegranate growing, as they
pose ever increasing competition to each other. Comparison of these two crops begins with an assessment,
from the farm economy perspective, of the main results published in the scientific literature on regulated
deficit irrigation, this being one of the most up-to-date techniques used to address water shortage not clear.
Also, the study analyzes the trend in prices received by farmers for the ‘Lane Late’ orange, ‘Clemenules’
mandarin, and for the two main Spanish varieties of pomegranate. The economic outlook expected from
these two crops is rounded off by an analysis of investments, which shows the profitability of individual farms.
S22P07
PDO and PGI citrus productions: state of the art and perspectives
Scuderi A . , and Pecorino B.
Faculty of Agriculture, University of Catania, (DIGESA), Department of agri-food and environmental systems and management, Italy.
alessandro.scuderi@unict.it
Within the field of agrifood and certified hortofruit productions, citrus fruits play a very important role,
especially for Italy. In fact, 12 appellations out of the 19 ones worldwide recognized have Italian origin. In
fact, they have become a significant and strategic sector of the national economy, in particular for the South,
which, nevertheless, in the last times is experiencing a severe crisis, with growing loss of market shares and
profitability for producers. Therefore, the need of an intervention is pressing now, at structural, economic and
financial level, to overcome it. Besides, improving production efficacy and farmers’ profits, special attention is
to be paid to the economic development of the entire production system, focusing on the concept of global
quality. The new strategy of the modernization process of Italian citrus growing is to be based on two priority
targets: food safety for consumer protection and enhancement of agrifood production quality. To this end this
report analyzed, in a system perspective, the state of the art of quality productions by adopting SWOT analysis
mode. Preferring the system approach implied an articulated group of specific targets aiming at obtaining the
improvement of the conditions of the production phase and the market efficiency for citrus productions.
S22P08
Comparisons of fruits load estimation methods using geostatistical techniques
Gimenez L.I., Cabrera Brunetti S.C., Avanza M.M., and Mazza S.M.
Universidad Nacional del Nordeste (UNNE), Facultad de Ciencias Agrarias, Argentina. smmazza@gmail.com
Anticipated knowledge of fruits harvest is useful to define management and marketing strategies. Prediction
methods use objective field data by counting the fruit in the entire canopy of trees or in sections of them,
with known volume, and then apply mathematic expressions for geometric bodies, to calculate the total
volume. Variability in load of fruit trees occurs, in time, with alternation between years of high and low
production, and in space, between areas of higher and lower productivity. Geostatistical techniques allow
using spatial information for estimating variables distributed in space. This study aimed to compare methods
for estimating fruit load in ‘Valencia late’ sweet orange quantifying the spatial dependence. Field data were
obtained on a commercial orchard of ‘Valencia late’ sweet orange, located in Entre Rios, Argentina, during
the seasons 2009/10 and 2010/11. Load was estimated 60 days before harvest on sample of the 6.5% of
trees, by two methods: counting fruits in the entire canopy (TC) or into a frame of 0.5 m of side (0.125 m3)
and applying the cone volume formula (FC); at harvest all fruit in the canopy was counted (RL). Using the
residual sums of square as a selection criterion, mathematical models that quantify spatial dependence of
harvested (RL) and estimated load (TC and FC) were determined. Real load adjusted to a spherical model, in
both seasons, with ranges of spatial dependence of 20.58 m and 16.52 m and estimates of the total variance
of 140.574 and 129.043 in seasons 2009/10 and 2010/11 respectively. In season 2009/10 predicted values
by both methods fitted to an exponential model, with ranges of 20.82 m and 25.38 m and sills of 104.263
and 86.022 respectively. In season 2010/11 predicted values by both methods fitted to a spherical model
with ranges of 16.58 m and 14.62 m and sills of 69.887 and 100.426 respectively. Both methods characterize
adequately the structure of spatial dependence but underestimate total variance.
372 - VALENCIA CONFERENCE CENTER, 18th-23rd NOVEMBER 2012