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Ital. J. Agron., 7, 1, 57-63
Italian Durum Wheat Agroclimatic Areas: their Influence on Kernel Shape
and Semolina Yield
P. NOVARO, F. COLUCCI, and M.G. D’EGIDIO
Istituto Sperimentale per la Cerealicoltura, Roma, Italy
Corresponding author: P. Novaro, Sezione di Pianificazione degli Esperimenti, Istituto Sperimentale per la Cerealicoltura, via Cassia 176, 00191 Rome, Italy. Tel: +39 06 3295705; Fax: +39 06 36298457; E-mail: [email protected]
Received: 2 August 2002. Accepted: 28 May 2003.
ABSTRACT
BACKGROUND. Previous research on durum wheat established the relationships between kernel shape and
semolina yield and classified durum wheat growing
areas as agroclimatic areas. The aim of this work was
to check whether kernel shape and semolina yield
were modified when durum wheat varieties were
grown in different agroclimatic areas.
METHODS. Grain samples (n = 240) were analysed of
15 durum wheat varieties grown in trials conducted
by the Rome Experimental Institute for Cereal Research during 1998 and 1999; trial locations were
grouped in 8 agroclimatic areas. For each sample different measurements for describing kernel shape
were determined by image analysis procedures, plus
1,000-seed weight and semolina yield. Factorial analysis of variance allowed the effects of growing area,
genotype and their interactions to be calculated for
the considered characteristics.
RESULTS. Factorial analysis of variance shows factors
and interactions significant for all the characteristics.
The significance of the interactions does not allow
tests of the main effects to be performed. For the
“year × growing area” interaction the 1999 results are
always significantly lower than those of 1998, however
North-Central Adriatic Coast appears to be the best
environment in both years. For the “growing area ×
genotype” interaction, considering kernel volume,
Simeto appears to be the best variety in all the environments, followed by Creso; Mongibello performs
well, especially in Sicily where this variety was selected. For 1,000-seed weight Simeto, Creso and Colosseo
confirm their good results in all areas. For semolina
yield San Carlo achieves the best values.
CONCLUSIONS. The North-central Adriatic Coast results as being the best growing area for both kernel
shape and semolina yield, followed by the Apennines.
Typical durum wheat growing areas (Apulia, Sicily
and Sardinia) show different results over the years
due to very variable weather conditions. Considering
the “growing area × genotype” interaction, Simeto
appears to be the best variety in all growing areas for
kernel volume and 1,000-seed weight; San Carlo gives
the best values of semolina yield. The most
favourable growing areas for the considered characteristics are those with stable climatic conditions over
the years.
Key-words: durum wheat, agroclimatic areas, image
analysis, kernel shape, semolina yield.
INTRODUCTION
Studies on the differences among wheat varieties grown in several agroclimatic areas in
terms of kernel size and shape and semolina
yield are an active area of research. Kernel size
and shape are evaluated by image analysis techniques to obtain objective measurements while
preserving intact seed for sowing.
Image analysis systems have been developed on
a variety of applications in agriculture. Many researchers studied cereal products to describe
the textural appearance of bread crumb
(Bertrand et al., 1992; Sapirstein et al., 1994; Zayas, 1993; Zghal et al., 1999); Symons et al.
(1996) developed an objective instrumental
method for counting specks in semolina, whereas Bacci et al. (1995) studied an automatic system for the evaluation of durum wheat grain alterations such as yellow-berry and shrivelling.
Image analysis techniques have also been applied to both kernel classification and discrimination (Zayas et al., 1985; 1986; 1994; Sapirstein
et al., 1987; Thomson and Pomeranz, 1991; Zayas and Steele, 1996; Sapirstein and Kohler,
1999) and to differentiate wheat-grain samples
according to grain morphology or other attributes related to milling quality (Marshall et al.,
58
Novaro et al.
1986; Zayas et al., 1986; Symons and Fulcher,
1988 a, b; Draper and Keefe, 1989; Newman et
al., 1989; Sapirstein, 1995 ; Wrigley and Morris,
1995; Troccoli and Di Fonzo, 1999).
Berman et al. (1996) applied image analysis to
whole-grain samples to predict milling quality.
In selecting for this character in bread wheat,
they found four parameters (area, length of minor and major axes and kernel volume) and test
weight to be related to flour yield. Novaro et al.
(2001) studied the relationships among kernel
shape and size measurements obtained by image analysis, 1,000-seed weight, test weight and
semolina yield to define equations useful for
predicting semolina yield in durum wheat: they
found kernel volume jointly with 1,000-seed
weight or test weight to be the best predictors.
On the basis of these results and having classified durum wheat growing areas as agroclimatic areas by using the results of variety testing
trials conducted by the Rome Experimental Institute for Cereal Research from 1975 to 2001,
the present work was done to determine the influence of growing areas on kernel shape and
size and semolina yield and how these characteristics are modified among varieties and for a
single variety when grown in different agroclimatic areas.
MATERIALS AND METHODS
Samples
Grain samples of 15 durum wheat varieties included in a national network of trials conducted in Italy during 1997-98 and 1998-99 growing
seasons were analysed. The varieties, representative of genotypes currently grown in Italy,
were cultivated in 48 locations in the first season and 46 during the second. Due to the en-
vironmental diversity of Italy and on the basis of
the results of trials on durum wheat conducted
by the Rome Experimental Institute for Cereal
Research during the last 30 years, the trial locations were grouped in 8 different agroclimatic areas (Novaro, 1997): Po Valley, North-Central
Adriatic Coast, North-Central Tyrrhenian Coast,
North-Central Apennines, Central-South Apennines, Adriatic Ionian Coast, Sicily and Sardinia
(Table 1). Composite samples for each variety
were made up by mixing grains from locations
belonging to the same agroclimatic area (Lukow
and McVetty, 1991; Mariani et al., 1995).
For kernel characteristics 240 samples were
analysed as duplicate sets (n=480), for 1,000-seed
weight and semolina yield, 240 samples were considered because replicates were not available.
Image analysis
A specific macro, a succession of image analysis procedures, was developed on an image
analysis system which included a videocamera
(JVC TK-C 1380), a 5000 K light and KS 400
software (ZEISS). The system was used to study
the durum wheat kernel shape and dimensions.
Images were captured for each sample as duplicate sets of 50 grains randomly chosen and
arranged to minimise contact among the grains
(Berman et al., 1996). For each sample different
measurements useful for describing kernel
shape such as area (AREA), perimeter (PERIM), length of minor (AMIN) and major
(AMAX) axes and volume (VOL) were taken.
According to Berman et al. (1996), on the assumption that a grain is an ellipsoid with circular cross section, the kernel volume was computed applying the formula: π·AMAX·AMIN2/6.
Technological tests
Semolina yield (SEM) and 1,000-seed weight
(SEEDW) were considered: 1,000-seed weight
Table 1. Italian durum wheat growing areas.
1
2
3
4
5
6
7
8
Agroclimatic areas
Geographical areas
Po Valley
North-Central Adriatic Coast
North-Central Tyrrhenian Coast
North-Central Apennines
Central – South Apennines
Adriatic – Ionian Coast
Sicily
Sardinia
Lombardy, Veneto, Emilia
Romagna, Marche, Abruzzo (Coast)
Tuscany (Coast), Latium (Coast)
Tuscany (Apennines), Umbria, Latium (Apennines)
Campania (Apennines), Molise, Basilicata (Apennines), Calabria
Apulia, Basilicata (Coast)
Sicily
Sardinia
Durum Wheat Agroclimatic Areas
59
Table 2. Mean value and standard deviation of characteristics considered.
Variables
Code
Kernel minor axis length (mm)
Kernel major axis length (mm)
Kernel perimeter (mm)
Kernel area (mm2)
Kernel volume (mm3)
1,000-seed weight (g)
Semolina yield (%)
AMIN
AMAX
PERIM
AREA
VOL
SEEDW
SEM
was determined as the mean of 2 samples of 15
g each, semolina was obtained from a sample of
3.5 kg by laboratory scale milling on a Buhler
MLU 202 test mill with three breaking and
three sizing passages. The milling equipment
(mill and purifier) was adjusted to obtain
semolina within 0.9% ash content, according to
the Italian law. The semolina yield (%) was estimated as the ratio between milling product
(semolina) and raw material (grain).
Statistical analysis
Factorial analysis of variance was computed for
kernel characteristics, semolina yield and 1,000seed weight using the SPSS software package
(Norusis, 1996); year, growing area and variety
were considered as fixed factors.
For semolina yield and 1,000-seed weight, the
“year × growing area × genotype” interaction
was used as error variance because replicates
were not available. Duncan’s multiple range
test was applied to reveal significant differences among the means for factors and interactions.
RESULTS AND DISCUSSION
Mean and standard deviation of all the measured characteristics are reported in Table 2; the
Measures (n)
Mean value
Standard
Deviation
480
480
480
480
480
240
240
3.3
7.5
18.4
18.1
42.8
43.3
66.0
0.2
0.3
0.8
1.8
6.6
5.1
4.2
variability values for 1,000-seed weight, semolina yield and kernel measurements are those
usually found for durum wheat in Italy, as reported by Novaro et al. (2001).
Factorial analysis of variance (Table 3) shows
factors and interactions significant for all the
characteristics with the exception of the “year ×
genotype” interaction relative to semolina yield.
Having found significant interactions, tests of
the main effects are not performed unless for
the factor “growing area”, which is important
for us because it is a new way of considering
trial locations. The mean values for each growing area, tested by Duncan’s multiple range test,
are reported in Table 4 for all characteristics.
The best growing area both for kernel shape
measurements and for 1,000-seed weight and
semolina yield results as being the North-Central Adriatic Coast and in decreasing order,
North-Central and Central-South Apennines.
Adriatic-Ionic Coast, Sicily and Sardinia, typical
durum wheat growing areas, are placed at a lower level probably as a consequence of high climatic variability over the years (Desiderio et al.,
1998; 1999).
In a previous work, Novaro et al. (2001) studied the relationships among kernel size and
shape measurements, 1,000-seed weight and
semolina yield and found kernel volume jointly
Table 3. Factorial analysis of variance for the characteristics considered.
Source of variation
Year (Y)
Growing area (GA)
Genotype (G)
Y × GA
Y×G
GA × G
Y × GA × G
Error
AREA
695.6
19.2
26.0
13.1
1.8
1.2
0.9
0.5
**
**
**
**
**
**
**
**
PERIM
91.6
2.0
8.6
1.7
0.3
0.2
0.1
0.1
**
**
**
**
**
**
**
**
°P≤ 0.10; *P≤ 0.05; **P ≤ 0.01; ns= not significant
AMIN
9.15
0.52
0.26
0.23
0.03
0.02
0.02
0.01
**
**
**
**
**
**
**
**
AMAX
VOL
8.61 **
0.19 **
1.86 **
0.17 **
0.04 **
0.03 **
0.02 **
0.01 *
8409.5
377.2
262.2
173.9
22.8
16.5
12.4
7.1
SEEDW
**
**
**
**
**
**
**
**
1339.9
196.5
80.3
27.7
8.7
2.3
1.4
–
**
**
**
**
**
**
**
SEM
1379.0 **
119.8 **
10.0 *
73.9 **
5.6 ns
6.9 °
5.3 **
–
60
Novaro et al.
Table 4. Comparison among growing areas for the characteristics considered.
Growing areas
Po Valley
North-Central Adriatic Coast
North-Central Tyrrhenian Coast
North-Central Apennines
Central – South Apennines
Adriatic – Ionian Coast
Sicily
Sardinia
Mean
(1)
PERIM
(mm)
AREA
(mm2)
ce (1)
a
bc
b
bd
b
de
e
17.8
19.3
18.0
18.1
17.9
18.1
17.7
17.5
18.1
18.2
18.8
18.2
18.3
18.3
18.4
18.3
18.2
18.4
AMIN
(mm)
cd
a
d
cd
cd
b
bc
cd
3.23
3.45
3.26
3.29
3.25
3.22
3.17
3.15
3.25
AMAX
(mm)
cd
a
c
b
cd
d
e
e
7.5
7.6
7.4
7.5
7.5
7.6
7.5
7.5
7.5
d
a
e
d
d
ab
bc
d
VOL
(mm3)
41.8
48.4
42.5
43.6
42.5
42.2
41.0
40.2
42.8
cd
a
c
b
c
c
de
e
SEEDW
(g)
42.1
47.1
43.3
44.8
45.9
43.3
37.2
42.6
43.3
f
a
d
c
b
d
g
e
SEM
(%)
65.5
69.1
63.8
66.7
66.4
63.6
64.6
68.2
66.0
d
a
f
c
c
f
e
b
Duncan’s multiple range test, P= 0.05
Table 5. Kernel volume, 1,000-seed weight, semolina yield: year × growing area interaction.
Growing areas
1998
Po Valley
North-Central Adriatic Coast
North-Central Tyrrhenian Coast
North-Central Apennines
Central – South Apennines
Adriatic – Ionian Coast
Sicily
Sardinia
Mean
(1)
43.1
50.7
47.4
49.9
45.9
47.6
45.7
45.2
47.0
VOL (mm3)
1999
e (1)
a
bc
a
d
b
d
d
40.5
46.2
37.6
37.2
39.2
36.8
36.2
35.1
38.6
1998
f
cd
g
g
f
g
gh
h
44.2
48.6
46.9
47.
48.0
47.4
39.4
46.6
46.1
SEEDW (g)
1999
g
a
d
c
b
c
kl
e
40.1
45.7
39.6
42.2
43.8
39.2
35.0
38.5
40.5
1998
j
f
k
i
h
l
n
m
66.3
72.3
65.1
68.0
68.5
69.4
66.8
70.5
68.4
SEM (%)
1999
f
a
gh
d
d
c
e
b
64.7
65.9
62.5
65.3
64.2
57.8
62.3
65.9
63.6
hi
f
j
g
i
k
j
f
Duncan’s multiple range test, P= 0.05
with 1,000-seed weight to be useful traits for
predicting semolina yield. On the basis of these
results only kernel volume, 1,000-seed weight
and semolina yield will be discussed.
For the “year × growing area” interaction relative to the three characteristics chosen it can be
noted that the 1999 results are always signifi-
cantly lower than those of 1998, in any case the
North-Central Adriatic Coast appears to be the
best environment, followed by North-Central
and Central-South Apennines; the Adriatic-Ionic Coast shows good results during 1998 for the
favourable weather conditions during the year,
whereas in 1999 it assumes a lower level fol-
Table 6. Kernel volume (mm3): growing area × genotype interaction.
Genotypes
8
CRESO*
DUILIO*
SIMETO*
COLOSSEO
GARGANO
GIANNI
MONGIBELLO
NEFER
OFANTO
PARSIFAL
SAN CARLO
VARANO
Mean
45.3
42.3
46.7
41.5
40.7
40.9
44.2
36.7
39.3
40.5
41.9
39.4
40.2
7
ab
bd
a
bd
ce
ce
ac
e
de
ce
bd
de
(1)
44.2
40.7
46.0
42.8
43.1
38.4
44.9
39.1
43.7
35.9
41.5
44.6
41.0
Growing areas
6
1
ab
bd
a
ac
ac
de
ab
ce
ab
e
bd
ab
44.6
45.5
44.8
41.8
41.8
41.7
41.6
40.4
42.6
41.3
42.6
43.5
41.8
ab
a
ab
ab
ab
ab
ab
b
ab
ab
ab
ab
45.8
45.1
43.9
45.7
45.1
40.3
43.9
38.0
44.1
42.3
41.4
42.9
42.2
a
a
ab
a
a
bc
ab
c
ab
ab
ac
ab
3
45.3
44.4
50.2
45.1
43.2
43.1
39.2
44.3
43.5
43.9
37.7
43.4
42.5
5
b
b
a
b
b
b
c
b
b
b
c
b
*= control genotypes; the best 3 genotypes in each growing area are reported in bold.
(1)
Duncan’s multiple range test, P= 0.05
40.4
40.5
46.7
44.5
41.7
39.3
46.5
44.1
43.7
41.8
46.0
46.8
42.5
4
cd
cd
a
ac
cd
d
a
ac
ac
bd
ab
a
43.7
47.1
50.8
42.8
42.8
44.7
44.1
42.8
46.8
45.5
43.4
44.2
43.6
2
b
ab
a
b
b
b
b
b
b
b
b
b
48.5
51.4
55.7
51.1
49.9
48.5
52.3
46.6
50.4
47.1
46.4
51.0
48.4
bd
bc
a
bc
bd
bd
ab
d
bd
cd
d
bc
Durum Wheat Agroclimatic Areas
61
Table 7. 1,000-seed weight (g): growing area × genotype interaction.
Genotypes
7
CRESO*
DUILIO*
SIMETO*
COLOSSEO
GARGANO
GIANNI
MONGIBELLO
NEFER
OFANTO
PARSIFAL
SAN CARLO
VARANO
Mean
39.6
39.0
40.1
40.3
39.7
36.4
40.1
33.5
36.9
35.7
37.7
39.3
37.2
1
ac
c
ab
a
ac
ef
ab
g
e
f
d
bc
(1)
42.3
45.8
45.2
43.8
43.2
43.9
41.2
40.2
40.9
44.7
44.4
41.9
42.1
Growing areas
3
8
f
a
ab
de
e
de
gh
i
hi
bc
cd
f
46.5
45.0
46.7
46.2
44.4
43.4
42.1
37.4
41.7
42.6
43.9
41.7
42.6
ab
ac
a
ab
ad
bd
cd
e
d
cd
ad
d
46.2
45.5
47.1
46.4
42.2
44.4
40.8
43.7
42.6
44.7
42.5
43.1
43.3
bc
c
a
ab
h
de
i
ef
gh
d
gh
fg
6
46.6
44.8
46.5
47.3
45.3
43.5
44.3
41.4
43.3
41.6
44.8
43.8
43.3
4
ab
cd
b
a
c
ef
de
g
f
g
cd
ef
46.3
47.0
40.3
45.8
45.8
45.5
44.3
42.1
44.2
45.7
47.8
44.3
44.8
5
bc
b
g
cd
cd
d
e
f
e
cd
a
e
49.2
47.8
48.5
49.8
46.0
46.1
47.2
45.0
46.5
44.6
48.4
45.8
45.9
2
ab
cd
bc
a
f
f
de
g
ef
g
bc
f
47.2
49.1
52.4
51.0
48.6
49.9
46.5
43.5
48.5
47.3
48.9
47.7
47.1
e
cd
a
b
d
c
f
g
d
e
d
e
*= control genotypes; the best 3 genotypes in each growing area are reported in bold.
(1)
Duncan’s multiple range test, P= 0.05
lowed by Sicily (Table 5). These results are in
agreement with those reported for the main effects of growing area in Table 4.
For the “growing area × genotype” interaction,
considering kernel volume (Table 6), Simeto appears to be the best variety in all the growing
areas, followed by Creso that decreases in Central-South Apennines. Mongibello has a good
performance in the best growing areas, in Sardinia and Sicily where this variety was selected.
Duilio gives good results in North-Central
Apennines and North-Central Adriatic Coast, as
well as in the Po Valley and Adriatic-Ionian
Coast. Colosseo stands out particularly in the
Adriatic-Ionian Coast, North-Central Tyrrenian
Coast and North-Central Adriatic Coast. Finally Varano can be cited for its good performance
in the enviroments of Central-South Apennines
and Sicily, and Ofanto in North-Central Apennines.
Considering 1,000-seed weight, Simeto, Colosseo and Creso, followed by Duilio, have the best
values in all areas (Table 7); San Carlo instead
gives good results in the Apennines.
Considering semolina yield, San Carlo followed
by Gianni, Creso and Mongibello give the best
values in the best growing areas: North-Central
Adriatic Coast and Apennines (Table 8).
Colosseo and Nefer give good results in many
enviroments except in North-Central Adriatic
Table 8. Semolina yield (%): growing area × genotype interaction.
Genotypes
Growing areas
6
CRESO*
DUILIO*
SIMETO*
COLOSSEO
GARGANO
GIANNI
MONGIBELLO
NEFER
OFANTO
PARSIFAL
SAN CARLO
VARANO
Mean
63.6
59.2
60.7
68.3
62.9
61.9
62.9
64.7
65.6
63.0
65.9
64.4
63.6
3
cd (1)
g
f
a
de
ef
de
bc
b
de
b
bd
63.1
62.9
66.4
64.2
61.4
64.8
63.2
65.2
61.3
65.2
61.3
62.3
63.8
7
cd
ce
a
bc
e
b
cd
ab
e
ab
e
de
60.4
65.6
64.7
66.5
64.4
62.6
64.9
68.1
65.8
65.7
66.0
65.0
64.6
1
e
bc
c
b
c
d
bc
a
bc
bc
bc
bc
65.3
66.4
66.5
67.2
68.5
67.0
65.4
66.1
60.1
66.8
67.7
65.5
65.5
5
d
bd
bd
ab
a
ac
cd
bd
e
bd
ab
cd
67.0
66.1
64.7
66.3
64.4
69.8
67.1
67.3
66.3
65.8
67.3
66.4
66.4
4
b
bc
cd
bc
d
a
b
b
bc
bd
b
b
*= control genotype; the best 3 genotypes in each growing area are reported in bold.
(1)
Duncan’s multiple range test, P= 0.05
66.7
64.7
66.9
67.2
67.6
68.0
65.3
65.5
66.2
67.4
71.3
66.3
66.7
8
bd
e
bd
bc
bc
b
de
de
ce
bc
a
bd
71.0
66.3
67.5
67.4
68.7
66.5
67.7
69.4
70.0
67.8
73.6
68.2
68.2
2
b
f
ef
ef
ce
f
ef
cd
bc
ef
a
de
68.2
68.2
67.4
67.7
69.2
69.4
71.9
72.2
69.7
69.5
68.5
67.7
69.1
bd
bd
d
cd
bc
b
a
a
b
b
bd
cd
62
Novaro et al.
Coast and North-Central Apennines, respectively.
For 1,000-seed weight and semolina yield the
second-order interaction was used as error variance to test the first-order interaction; for this
reason we have chosen to omit the discussion
on the second-order interaction relative to kernel volume.
Finally, Central-Adriatic Coast and Apennines,
having good water availability during grain filling, result as being the best growing areas for
kernel size and shape and semolina yield, but it
can be noted that these favourable weather conditions can also encourage the development of
fungal diseases. South of Italy instead, a typical
durum wheat growing area with high climatic
variability, gives different results over the years
for the considered characteristics; notwithstanding the fact that this environment is characterised by high temperatures and low soil moisture, it gives advantages such as seed soundness,
low yellow-berry and colour improvement (Novaro et al. 1997).
CONCLUSIONS
Durum wheat growing areas in Italy are quite
different in terms of climatic conditions; weather, specially rainfall, is more stable over the
years in North and Central Italy than in the
South. So, for the considered characteristics,
North-Central Adriatic Coast followed by
North-Central Apennines result as the best
growing areas for all genotypes, whereas typical durum wheat growing areas, Apulia, Sicily
and Sardinia, with pronounced climatic variability, give different results over the years.
The influence of growing area on genotype behaviour can be summarised as follows:
− for kernel volume: Simeto, Creso, Duilio,
Colosseo, Mongibello and Ofanto give the
best results in all the growing areas, whereas
Varano appears to be good in South Apennines and Sicily;
− for 1,000-seed weight: Simeto, Colosseo and
Creso followed by Duilio have good results
in all areas, San Carlo gives good values in
the Apennines;
− for semolina yield: San Carlo, Gianni, Creso
and Mongibello give the best values in the
best growing areas.
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L’INFLUENZA DEGLI AREALI AGROCLIMATICI SULLA GRANDEZZA E LA FORMA
DEL GRANELLO E SULLA PRODUZIONE DI SEMOLA DEL FRUMENTO DURO
SCOPO. Avendo classificato in precedenti ricerche le zone di coltura del frumento duro come areali agroclimatici,
obiettivo di questo lavoro è controllare se la forma e le dimensioni del granello e la produzione di semola siano
influenzati dall’areale di coltivazione e come queste caratteristiche varino tra le varietà e entro una stessa varietà.
METODI. Sono stati analizzati 240 campioni di granella di 15 varietà di frumento duro allevate nella rete di prove
di confronto varietale coordinata dall’Istituto Sperimentale per la Cerealicoltura di Roma negli anni 1998 e 1999;
le località di prova sono state raggruppate in 8 areali. Le misure di forma del seme, ottenute attraverso la metodologia di analisi d’immagine, sono state analizzate insieme al peso 1000 semi e alla resa in semola. Un’analisi fattoriale della varianza ha consentito di evidenziare gli effetti dell’areale di coltivazione sulle variabili considerate.
RISULTATI. L’analisi fattoriale mostra che le varianze dei fattori e delle interazioni sono significative per tutti i caratteri considerati. La significatività delle interazioni esclude i tests sugli effetti principali. Riguardo l’interazione
“anno × areale di coltura” i risultati del 1999 sono sempre significativamente inferiori a quelli del 1998; comunque
la Costiera Adriatica Nord-Centro risulta essere il miglior ambiente nei 2 anni. L’interazione “areale di coltura ×
genotipo”, per quanto riguarda il volume del granello, evidenzia che il Simeto è la migliore varietà in tutte le zone seguita dal Creso; Mongibello emerge specialmente in Sicilia dove è stato selezionato. Per il peso 1000 semi Simeto, Creso e Colosseo confermano il loro buoni risultati in tutte le aree. Per la produzione di semola la varietà
San Carlo raggiunge i migliori valori.
CONCLUSIONI. La miglior area di coltura risulta la Costiera Adriatica Nord-Centro seguita dagli Appennini. Le zone tipiche di coltura del grano duro (Puglia, Sicilia e Sardegna) a causa della variabilità climatica danno risultati
discontinui tra gli anni. Considerando l’interazione “areale di coltura × genotipo”, Simeto appare la migliore varietà in tutti gli areali per il volume del seme e peso 1000 semi; mentre per la produzione di semola emerge San
Carlo. Gli areali che risultano migliori per i caratteri considerati sono quelli che hanno condizioni climatiche più
stabili negli anni.
Parole chiave: frumento duro, areali agroclimatici, analisi d’immagine, forma del granello, resa in semola.