Study of morphological and chemical diversity in chestnut trees (var. “Judia”) as a function of temperature sum
Estudio de la diversidad morfológica y química del fruto de castaña (var. “Judia”) en función de la suma de la temperatura

Abstract

Fruits of variety “Judia” (Castanea sativa Mill.) were collected in different climatic locations during 2006 and 2007 and the average of sum temperature (degree-days, °D) were 2457 °D and 2147 °D (May–October), respectively. In 2007, the fruits were 38% bigger and contained 50% more starch than those from 2006 but they had less 6.41% crude fat content. In 2006, nuts from the coldest place (Valpaços: 1895 °D) were the biggest (62.5 fruits/kg) and had the highest content in starch (400.7 g/kg DM) contrarily to the fruits from the hottest place (Murça: 2751°D), which were the smallest (157.1 fruits/kg). In 2007, the biggest fruits were yielded in Macedo Cavaleiros (2163 °D) 46.4 fruits/kg, repeating Murça with smallest fruits (66.0 fruits/kg). The Nei genetic distances between trees ranged between 0.0 and 0.227 proving that all of them are from the same variety.

Los frutos de la variedad “Judía” (Castanea sativa Mill.) fueron recolectados en diferentes zonas climáticas, durante 2006 y 2007, con un promedio sumatorio de temperatura (días-grado, °D) de 2457 y 2147 °D (mayo-octubre), respectivamente. En 2007, los frutos fueron un 38% más desarrollados, conteniendo un 50% más de almidón que los de 2006, y un 6,41% de menos de grasa cruda. En 2006, los frutos del lugar más frío (Valpaços: 1895 °D), fueron los que registraron mayores tamaños (62,5 frutos/kg) y contenidos más altos de almidón (400,7 g/kg peso seco). Resultados contrarios a éstos fueron los obtenidos para los frutos de la localidad más cálida (Murça: 2751 °D), que fueron los que registraron tamaños más pequeños (157,14 frutos/kg). En 2007, los mayores frutos procedieron de Macedo Cavaleiros (2163 °D), 46,4 frutos/kg, siendo de nuevo Murça (2338 °D) la que proporcionó los frutos más pequeños (66,0 frutos/kg). Las distancias genéticas de Nei entre los árboles oscilaron entre 0,0 y 0227, demostrando que todos ellos son de la misma variedad.

Keywords:

• fruit biometry
• chemical composition
• clonal selection
• degree-days
• edaphoclimatics conditions
• molecular markers

Palabras clave:

• biometría del fruto
• composición química
• selección clonal
• grado-día
• condiciones edafoclimáticas
• marcadores moleculares

Introduction

Castanea sativa Miller is a multipurpose species found in the Northern Hemisphere, mostly in China, Korea and Japan in Asia, from Turkey to Atlantic Islands in Southern Europe and in the United States (Pereira-Lorenzo & Ramos-Cabrer, 2004). Chestnut fruit is an important economic food resource in many European countries due to the favorable climatic, edaphic, and ecological conditions provided in this area (Ferreira-Cardoso, 2009). Trás-os-Montes is Portugal's main chestnut producing region, covering almost 85% of the total national production. The predominant variety is “Judia” (Castanea sativa Mill.), and is included in two protected designations of origin (PDO): “Castanha da Terra Fria” and “Castanha da Padrela”. “Judia” also predominates in new orchards, mainly due to its better fruit size, (50–80 fruits/kg), good fruit appearance, flat shape, adequate for transformation, and excellent characteristics for fresh consumption. As referred by Künsch et al. (1999), chestnuts are rich in carbohydrates, have low content in fat content in fat and were recognized as an excellent source of starch. They also have interesting levels of minerals and vitamins (Pereira-Lorenzo, Ramos-Cabrer, Díaz-Hernández, Ciordia-Ara, & Ríos-Mesa, 2006; Vasconcelos, Bennet, Rosa, & Ferreira-Cardoso, 2007). However, these qualitative and technological characteristics vary for the edaphoclimatic characteristics influence (Borges, Gonçalves, Carvalho, Correia, & Silva, 2008; Ferreira-Cardoso, 2009).

In spite of its strong decrease during the second-half of the twentieth century, caused by ink disease, chestnut growing still goes on in the North Portugal; in fact, it has a rather significant socioeconomic importance, since it is widely spread and produces high quality nuts, which are most appreciated in European markets, either as a fresh food or as raw material for industrial transformation (Ferreira-Cardoso, 2009).

Yet, “Judia” shows some adaptative constraints to such summer high temperatures as the ones frequently registered in recent years, both in Terra Fria and Padrela, as a consequence of climate changes. According to Gomes-Laranjo, Peixoto, Wong Fong Sang, and Torres-Pereira (2006), the optimal temperature for photosynthesis in “Judia” is about 24 °C, its production being strongly reduced (over 50%) when temperature rises up to 32 °C.

Studies of genetic diversity have employed morphological traits (Ye, Zhang, Ning, & Bao, 2003; Wen & Hsiao, 2001), chromosome characteristics, isozymes, and DNA-based markers. SSR molecular markers of genome polymorphism have increasingly been used to analyze genetic relationships (Luís, Teresa, Carlos, & Cristina, 2001) and genetic stability (Martins, Sarmento, & Oliveira, 2004). The aim of this work is to characterize nuts from “Judia” variety, collected in different climatic localities, trying to find the optimal temperature sum conditions regarding the evaluation of the quality and fruit size.

Material and methods

Plant material

According the farmer's opinion, 25 trees from “Judia” variety from Trás-os-Montes Region were selected at different altitudes, between 709 and 860 m a.s.l. (meters above sea level): Alfândega da Fé (A), Bragança (B), Chaves (C), Valpaços (V), and Vinhais (Vi) (four trees each local) Macedo de Cavaleiros (Ma) (tree trees) and Murça (M) (two trees). All trees are over 30 years old and are in good sanitary and nutritive status.

Edaphoclimatic conditions

This study was conducted in 2006 and 2007. The edaphoclimatic conditions were based on the soil and climatic conditions of each locality. According to Cesaraccio, Duce, and Snyder (2001), we estimated the degree-days (sum of temperature, °D). To calculate it, we used ΣTemperature (°D) = (Tx – t0) × n: where “x” is the average temperature of each month; “t ₀” the base temperature, which was considered 6 °C for chestnut (Gomes-Laranjo, Coutinho, & Francisco, 2008); and “n” total days of each month.

Concerning soil analysis (Supplementary Table 1B), extractable phosphorous (P₂O₅) content was extracted by the Egner–Riehm solution (ammonium lactate, pH 3.6) and determined by molecular absorption spectrophotometry (Egnér, Riehm, & Domingo, 1960). The pH was determined by potentiometry in suspensions (1:2.5) of soil in H₂O (ISRIC, 1993). Exchangeable bases (Ca, Mg, K, and Na) are extracted with 1M ammonium acetate 1M pH 7 (SPAC, 1999) and determined by atomic absorption spectrophotometry (Ca and Mg) or by flame emission spectrophotometry (K and Na). The organic matter (OM) was determined by dosage of organic carbon (C) using an elemental analyzer with NIR (near infrared) detector and application of the factor 1.724 (Nelson & Sommers, 1996).

Fruit biometry

Twenty urchins were randomly collected directly from each tree, 1 week after the beginning of fruit fall (October) in both years. For each urchin, the number of well-developed and aborted fruits was determined, being the good fruits individually weighted. The length, height, and thickness parameters of each fruit were measured with a digital sliding caliper (Absolute Digimatic CD-ISCP, Mitutoyo, UK). The number of well-developed and aborted fruits was determined for each urchin. Total fruit size (fruit/kg, TF) includes all the fruits, whether good, aborted, rotten, or wormy fruits. However, the corrected fruit size (fruit/kg, CF) refers only to good fruits.

Chemical analysis

Dry matter (DM), organic matter, and ash contents were determined according AOAC (1975). Crude protein and crude fat were determined using AOAC method (AOAC, 1990). Crude protein was calculated from nitrogen, determined by micro-Kjeldahl method with a selenium catalyst, using the factor N × 5.3 as recommended by McCarthy and Meredith (1988) and crude fat was analyzed by extraction with petroleum ether in a soxhelet apparatus. For extraction and quantification of the starch, samples were analyzed in triplicate. The initial conversion of starch to glucose (Rasmussen & Henry, 1990) was done in two phases, using a termo-stable α-amylase (A3306-Sigma) to break it in dextrins and oligosaccharides and amyloglucosidase (11976223-Roche) to ensure a more effective quantitative conversion to glucose (Salomonsson, Theander, & Westerlund, 1984). The colorimetric determination of glucose was done at 505 nm using the single-solution reagent method previously reported, which involves the coupled enzymatic glucose oxidase/peroxidase reaction in combination with the 4-amino antipyrine chromogen system (Blakeney & Matheson, 1984). After obtaining the standard line, the soluble sugars were determined by the method of anthrone (Irigoyen, Emerich, & Sánchez-Díaz, 1992). After having been in water-bath in ethanol to 80%, added to solution of anthrone. Finally, the solutions were read in spectrophotometer at 625 nm.

All chemicals and reagents were of analytical grade and obtained from various commercial sources (Sigma/Aldrich, Roche, Merck and Pronalab).

Molecular characterization

Leaves were harvested in spring and conserved at –80 °C until DNA isolation. DNA was isolated using DNeasy Plant Mini Kit of the Quiagen. We studied nine polymorphic and unliked SSR: CsCAT 3, CsCAT 16, CsCAT 14, and CsCAT 41 (Marinoni, Akkak, Bounous, Edwards, & Botta, 2003), EMCs 2, EmCs 14, and EMCs 15 (Buck, Hadonou, James, Blakesley, & Russel, 2003) developed for Castanea sativa and QpZAG 36 and QpZAG 110 (Kampfer, Lexer, Glössl, & Steinkellner, 1998; Steinkellner et al., 1997) developed for Quercus petrae. DNA extraction and amplification of microsatellite loci were done following the same methodology used by Pereira-Lorenzo et al. (2010).

Data analysis

Analysis of variance (ANOVA) was conducted to estimate the effects of the region and the year, using Microsoft Excel and StatView 4.0 programs (Abacus, concepts, Inc.). Comparisons were made with Fisher test, using a significance level of 95%. Multivariate analysis was performed in Statistica 8.0 (Statsoft, Tulsa, USA). A dendogram was built using fruit biometry and chemical analysis parameters, according to the Euclidean distance and ward's method. The genetic dendogram was built using the Dice distance (Nei & Li, 1979) which is included in the computational module SIMQUAL and the UPGMA clustering method was done using the computational module SHAN, both modules belonging to NTSYS 2.02h software version (Rohlf, 2000).

Results and discussion

Edaphoclimatic conditions

According to climatic data (source: Portuguese Institute of Meteorology), 2006 was warmer than 2007, being the mean of annual ΣTemperature for all the selected places, 2875 °D in 2006 and 2446 °D in 2007 (Supplementary Table 1A). In 2006, the amount ranged between 3214 °D (Murça, 711m a.s.l.),) and 2540 °D (Valpaços, 860 m a.s.l) and relating to 2007, 2911 °D (Murça, 711m a.s.l.),) and 1895 °D (Valpaços). Variations in annual ΣTemperature, between 2006 and 2007, were 412, 353, 451, 350, 303, 645, 353 °D, for Alfândega da Fé, Bragança, Chaves, Macedo de Cavaleiros, Murça, Valpaços, and Vinhais, respectively (Supplementary Table 1A). Relative to annual precipitation, the highest values belonged to the warmest year (Supplementary Table 1A). However, in terms of the vegetative period (May–October), the precipitation amount was similar.

Most of soils are loamy, having strong variations in phosphorous (P₂O₅) content (Supplementary Table 1B). The pH varied between 3.54 in Alfândega da Fé (759 m a.s.l.) and 4.36 in Macedo de Cavaleiros (722 m a.s.l.), but generality of soils presented pH around 4.00. As soils are acid, have low have low levels of exchangeable bases (Ca, Mg, K, and Na). Soils from Alfândega da Fé were also the poorest (0.64%) organic matter (OM) and those from Vinhais the richest (4.56).

Fruit biometry

Significant differences were found among “Judia” ecotypes according to their origin, which are supported by the high CV values (coefficient of variation) (Supplementary Table 2). When we compared the results obtained in 2006 and 2007, respectively, almost all parameters (except the ratio between total and corrected fruit size) pointed to a higher variation in 2006 than in 2007 (Supplementary Table 2), being the maximal CV detected corresponding to the corrected fruit size (33.8%). Similarly, fruits produced in 2007 were bigger and had an overall chestnut fruit size of 94.1 fruit/kg, against the 112.4 fruit/kg registered in 2006. Actually, coldest locals in 2006 (2421 °D and 2316 °D, between May–October) produced bigger fruits, and the worst fruit size was obtained in the hottest locality (2751 °D). Quite different results were obtained in 2007. The biggest fruits were collected to 2186 °D, corresponding to a 71.7 fruit/kg, which was 33.2% bigger than in the previous year. This value is similar to that obtained by Gomes-Laranjo et al. (2006) for chestnut fruits. On the contrary, the locality with 1700 °D (coldest) produced the smallest fruits, 41.1% smaller size than in 2006.

After subtracting the aborted and infested fruits, fruit size changed from 112.4 to 91.3 fruit/kg in 2006, and from 94.1 to 57.3 fruit/kg in 2007, which indicates a variation of 18.7% and 39.1%, respectively. This also suggests a significant increase of bad fruits in 2007, which can be ascribed to the decrease in the average temperature, 4 °C, during the pollination period (June/July, see Supplementary Table 1A). These findings are supported by the highest total/corrected fruit/kg ratios, which were 1.26 and 1.66, in 2006 and 2007, respectively. As was previously described by Gomes-Laranjo et al. (2008), “Judia” is one of the most sensible varieties to heat stress, an element which has a direct bearing on fruit size. According to these authors, the optimal temperature to maximize photosynthesis rate is around 24 – 27 °C; over 34, there is 50% more inhibition. Gomes-Laranjo et al. (2006) explain it by means of the existence of a lake, in the thylakoid membrane potential, as a consequence of its excessive fluidity (Bukhov & Mohanty, 1999) rather than as the consequence of disturbances at the level of oxygen evolving in photosystem II complex.

As regards the corrected fruit size analysis, in 2007, fruits were 37.2% bigger than in 2006, with a special mention to Murça (hottest locality) and Valpaços (coldest locality), where fruits presented the highest (58.0%) and lowest (6.1%) variation, from 2006 to 2007). Results suggest that size increasing was mainly due to length and thickness-related causes, since both increased almost 15%.The highest sizes were obtained in localities where temperatures were relatively low, corresponding to a total sum of degree-day values between 2000 and 2200 °D, during the vegetative season (May – October). These degree-day values are usually measured at an altitude if 800–1000 m a.s.l., and results show that low altitude restricts chestnut growth due to excess of warmth. When chestnuts are grown under low degree-day values, as was the case in 2007, the above mentioned temperature span drops for 600–800 m a.s.l., where the biggest nuts are now produced (Supplementary Table 2). Nevertheless, the analysis of degree-day values influence on fruit size (Supplementary Figure 2) suggests that at higher altitudes (above 900 m a.s.l.) due to insufficient heat (lower than 2000 °D), growing conditions can also be limited. Typically, the biggest fruits (2007) were more flat, 1.121 (2007) vs. 0.987 (2006), of which ecotypes to 2186 °D were the least flat in 2006 and the flattest in 2007. “Judia” is grouped in the flattest variety set, with a length/height ratio of <1.10, along with other important varieties such as Lada, 1.02, Amarelais, 1.03 and Martaínha, 1.04. By comparison, other varieties, with a length/height ratio of > 1.10, have an elongated shape, especially the Longal variety, 1.20, which is the most popular. Among Portuguese varieties, the ones with highest fruit size usually have the flattest shape (Pimentel-Pereira, Gomes-Laranjo, & Pereira-Lorenzo, 2007). The tendency for polymorphism is known as a consequence of environment, and intracultivar variability was already referred by Costa et al. (2008) who found variations in ecotypes depending on the population's origin. These conclusions were also observed for “Judia” leaves by Dinis et al. (2008), who had reported significant differences in their shape index.

Finally, the study of polyspermy indicates that the highest value calculated was for nuts that grew in localities corresponding to 2161 °D (7.5%). In the other ecotypes, polyspermy was 5% in 2041 °D and 2338 °D, 2% in 2163 °D and 2186 °D, and 0% in the coldest locality.

According to Supplementary Figure 1, there were not observed differences on fruit size in the range of 100 mm to 230 mm of precipitation in the period May–October, meaning that water availability seems not be restrictive in the soils of Trás-os-Montes. Martins et al. (2010) demonstrated that even when trees are subjected to prolonged periods of little or no precipitation, as it happened in 2005 (precipitation in May–September, between 60 and 100 mm), predawn leaf water potential in adult tress was preserved at −0.60 to −0.80 MPa from May to October and no significant differences between watered and non-watered plants were found. These authors explained it as being the consequence of the available water stored in the soil deep layers for the root system.

It was precisely in the interval of the sum temperature (May–October), 1700–2200 °D, that the biggest nuts were formed (40–60 fruits/kg) (Supplementary Figure 2). Above this range of temperature, fruit size decayed to almost 50%. Contrary to the precipitation influence, the temperature sum seems to influence the fruit size. This finding was particularly evident when both years are compared, 2006 (warm year) and 2007 (cold year) allowing a broad range of temperature sum as we present in the Supplementary Figure 2. So, in each year we can advise potential localities with highest fruits, only knowing their temperature sums. As an example from our results, in 2006 best fruits were collected in Bragança and Valpaços (848 and 860 m a.s.l.; 2421 and 2316 °D) at the same time the coldest localities (Supplementary Table 2) and in 2007, biggest fruits were collected in Macedo de Cavaleiros and Chaves (722 and 709 m a.s.l.; 2161 °D). According to these data, highest temperatures seem to be more influence than the lowest ones. Nevertheless, in localities with lowest temperature sum, pollination conditions could be worse than in the warmest localities, since the number of aborted fruits was bigger. Socias and Company (2005), for almond species, refer that low temperature during pollination may destroy easier the pistil than the pollen tubes, putting at risk the pollination process.

In the variance analysis of biometric traits (Supplementary Table 2) year, edaphoclimatic conditions explain 44.8% of the corrected fruit size variation, 36.0% of fruit height, and 68.1% of fruit length. The interaction between both, year and local, explains 47.7% of the total caliber. Contrarily, for thickness and the ratio between length and height are not mostly explained by the year, local, or the combination of both, suggesting then the possible influence of “Judia” genotype.

Chemical analysis

Analysis of the chemical composition is presented in Supplementary Table 3. DM content ranged between 527.4 g/kg and 642.0 g/kg in 2006, and between 428.7 g/kg and 555.6 g/kg in 2007, the mean content of all samples being 14% lower than in the driest year (2006). This tendency was supported by samples from orchards to Bragança (848 m a.s.l.), where this content decreased 26.2% from 2006 to 2007. On the contrary, nuts to 2572 °D preserved their DM content. According to Breisch (1995), the adequate average moisture content for good conservation in European chestnuts comprised between 490.0 and 600.0 g/kg, which is close to the values presented in this study (432.9 g/kg in 2006 and 514.6 g/kg in 2007) and by Vasconcelos et al. (2007), who determined a value of 500.0 g/kg for nuts produced in Trás-os-Montes during 2005 which was drier than 2006 or 2007. These authors also found equal values for Martaínha, although significantly lower than for Longal (54%), one of the ancestral varieties, very well appreciated for its organoleptic qualities and low level of polyspermy. These values are also similar to those determined for Spanish varieties as regards moisture, 54%, (Pereira-Lorenzo et al., 2006) yet higher as regards fresh weight (FW), 48% (Bellini, Giordani, Marinelli, & Perucca, 2005) namely in the case of Marrone del Mugello.

Concerning crude protein, crude fat, and starch, 2006 and 2007 affected these properties quite differently depending on edaphoclimatics conditions. 2007 was colder and dryer than 2006 and it led to a 50.4% increase in starch, a 8.6% increase in crude protein and also caused a decrease in crude fat (6.4%).

In relation to starch, which is one of the causes of fruit sweetness, non-significant differences were observed in data referring to 2006. However, in 2007 samples showed significant differences, with values ranging between 529.5 g/kg DM (to 2186 °D) and 630.7 g/kg DM (to 2338 °D). At the same time, in 2007 the local with 2041 °D (848 m a.s.l.) registered the highest decrease in nut DM (24.9%) and the maximum starch increase (39.9%), which corresponds to the second highest value among all samples. Average starch content was 390.2 g/kg DM in 2006, which is close to the mean value for Galician chestnuts, as referred by Pereira-Lorenzo et al. (2006). In 2007, this content increases almost twice as much (586.8 g/kg), which corroborated the values referred in other Portuguese studies for Portuguese varieties (Vasconcelos et al., 2007) and also in Spanish studies (Pereira-Lorenzo et al., 2006) about Spanish varieties (570 g/kg DM, namely in Galician varieties with 600 g/kg DM). Supplementary Figure 3 shows how degree-days influence starch content. As we said before, nuts in 2006 were smaller than those in 2007, but they also had the highest DM content. The answer to this discrepancy might be provided by a temperature effect analysis. Lower degree-day values (total temperature sum, 2000–2300 °D) induced the production of almost twice as much non osmotic biomolecule storage sugar, and possible, the storage of a smaller quantity of osmotically active molecules of mineral nutrients. In the variance analysis of basic chemical traits (Supplementary Table 3), the year explains 36.0 and 90.5% of DM and starch, respectively.

Starch is partially hydrolyzed into soluble sugars, giving the fruits its sweetness (Pereira-Lorenzo et al., 2006). The average of soluble sugars content for “Judia” was 105.8 g/kg DW, less than in Galician varieties (140 g/kg DM). Differences were registered as regards soluble sugars, between 82.2 to 140.9 g/kg DM. Samples from the local at 816 m a.s.l. which had already shown one of the lowest starch contents, now present the lowest soluble sugar level.

Regarding protein, and the effect of temperature sum, in 2007 fruits from trees to 860 m a.s.l. of altitude (2102 °D) had 86.6 g/kg DM, representing an increase of 49.5% in their content in relation to 2006 (2316 °D), which is almost twice as much as the value from many other provenances. That value was 37.6% and 43.8% higher than those obtained by Borges et al. (2008) and Vasconcelos et al. (2007), for “Judia”. In Valpaços (the coldest local) once again presented the highest protein content, although this time did not go over 57.9 g/kg DM, similar to the values obtained in many studies (Borges et al., 2008; Pereira-Lorenzo et al., 2006).

Only crude fat seems to have been negatively affected by lowest temperatures, which induced that values from 2007 were generally lower than those from 2006. In fact, general content measured in coldest localities, 2041 °D (816 m a.s.l.) and 1700 °D (860 m a.s.l.), where 26.4 g/kg DM and 18.8 g/kg DM, similar to that obtained by Borges et al. (2008) for “Judia”. As opposed, the trees in warmest locality, 2361 °D presented a 29.0 g/kg DM. However, our values are higher than those obtained by several authors for the same variety (Barreira, Casal, Ferreira, Oliveira, & Pereira, 2009; Vasconcelos et al., 2007). The local seems be important to understanding the variation in crude protein and crude fat (42.1% and 39.0%, respectively) (Supplementary Table 3).

A good fruit size and a sweet flavor of the chestnuts are the key factors for a good commercial value, so it is important and necessary to know which is the behavior of ecotypes in different weather conditions because this is the main producing region in Portugal.

Multivariate analysis

Morphological and chemical heterogeneity between the seven localities under study are expressed in Supplementary Figure 4A. Five clusters were found in this dendogram. Based on these clusters, we could see that the clusters I, III and IV are more related with morphological parameters, whereas cluster II was more associated to biochemical analysis. Cluster V, contains both parameters. This grouping demonstrates that the same parameter by different years is usually included in same cluster, except for the starch content and the corrected fruit size, which are grouped in different clusters.

The UPGMA analysis performed for molecular markers produced the dendrogram shown in Supplementary Figure 4B. The seven local's inbred lines into two major clusters. Cluster I consisted of six locals: A (759 m a.s.l.), B (848 m a.s.l.), C (709 m a.s.l.), M (711 m a.s.l.), V (860 m a.s.l.) and Vi (816 m a.s.l.) and cluster II one local: Ma (722 m a.s.l.), thus showing less levels of similarity with the other ecotypes studied. Most of localities under study have the typical “Judia” genotype (Costa et al., 2008) and Macedo de Cavaleiros have few differences detected by the primers. In this analysis, the Nei genetic distance ranged between 0.0 and 0.227. SSR data analysis of ecotypes supported close similarities between Alfândega da Fé, Bragança, Chaves, Murça, Valpaços, and Vinhais (genetic distance = 0.0). Macedo de Cavaleiros is the ecotype that presented some genetic distances with the other localities (A:Ma = 0.227; B:Ma = 0.204; C:Ma = 0.207; M:Ma = 0.039; V:Ma = 0.213 and Vi:Ma = 0.129). Gobbin et al. (2007) also referred in their work about European chestnut growing in Switzerland that locality might induce differences in fruit morphologically and chemistry, instead they are genetically similar, which can help to explain the nut differences in present work.

In order to establish the relationships between localities, principal components analysis (PCA) was applied to all variables under study. The first two PCs accounted for 77.8% of the total variance (TV) indicated that they provide a good description of the data. Supplementary Figure 5 shows the PCA results of variables used for the characterization of chestnut localities projected onto first two PCs. PC1 explained 59.7% of the TV and Murça in 2006 (6.3), Chaves (−3.4) and Valpaços (3.2) in 2007 are the values with largest contribution on the PC1. The parameters best correlated with PC2 (that accounted for 18.1% of TV) were Valpaços (3.1) and Alfândega da Fé (−2.9) in 2007 and Valpaços (1.9) in 2006. Four groups were defined according to the position of each sample. All localities in 2006, except Murça and Valpaços, showed similar variation whilst Valpaços in 2006 and the other localities in 2007 (except Valpaços) showed an inverse variation. Murça in 2006 and Valpaços in 2007 showed an inverse variation between both. In fact, the group formed by different localities and years (based in morphological and chemistry fruits characteristics) showed the climatic influence as showed in other studies (Borges et al., 2008). Murça in 2006 and Valpaços in 2007 are isolated in different groups. This could be explained by extreme degree-days obtained (2751 and 1700 °D, respectively). Valpaços in 2006 and the other localities in 2007 are in the same group. This locality was the coldest in both years, being its temperature sums in 2006 closest to the 2007's mean temperature sum. The other localities in 2006 are grouped due their warmest degree-days.

Conclusions

We detected small genetic distances between the selected clones, confirming that all of them are from the same variety. Although this study has been performed within the same variety, great differences were found between some areas and, therefore, it is interesting to complement this study with other parameters. But it is also important to refer that the edaphoclimatic conditions, namely degree-day values, strongly affect “Judia” productivity, whose optimal values range between 2000 and 2200 °D (from May to October). Under such conditions, “Judia” produces high-sized fruits, with high-starch content, but the number of aborted fruits increases slightly. From now, we can advise in each year the best localities for nut production (size and quality nut) only according to the temperature sums of the year. Based on the results of the PCA analysis and genetic dendogram, we could suppose that the differences of the fruit characteristics flow essentially by the different edaphoclimatic conditions in the dissimilar localities under study.

Acknowledgments

This research was funded by a scholarship from the FCT (“Selecção clonal em castanheiro”; Programme POCI/V.5/A0044/2005, and we are grateful to Maria Natália Campos Teixeira and Sara Ramos for technical assistance in the experimental field and in the analysis assays.

Supplementary material

Supplementary Table 1. Edaphoclimatic characterization of seven different locals. There are displayed the geographic coordinates, orchard altitude, climatic parameters (A) and soil physical and chemistry properties (0–50 cm) of each provenience (B).
Tabla adicional 1. Caracterización edafoclimática de siete diferentes localidades. Se muestran las coordenadas geográficas, altitud del castaño, parámetros climáticos (A) y las propiedades físico-químicas del suelo (0–50 centímetros) de cada procedencia (B).

	Coordinates			Average temperature (°C)				Degree-days (D°)				Precipitation (mm)
		“°W”	Altitude(m a.s.1.)	2006		2007		2006		2007		2006		2007
Local	“°N”			June–July	August–October	June–July	August–October	May–October	Year	May–October	Year	May–September	Year	May–September	Year
A
Alfândega da Fé	41.42	6.95	759	23.0	19.1	19.3	17.93	2593	2968	2186	2556	165	857	181	398
Bragança	41.68	6.72	848	22.0	18.3	18.3	17.23	2421	2699	2041	2346	212	884	228	563
Chaves	41.74	7.24	709	22.3	19.5	18.9	17.90	2572	3132	2161	2681	147	742	111	251
Mac. Cavaleiros	41.60	6.95	722	22.4	18.8	19.3	17.90	2545	2876	2163	2526	130	581	149	323
Murça	41.52	7.41	711	21.9	19.5	18.7	18.70	2751	3214	2338	2911	245	1176	230	607
Valpaços	41.60	7.43	860	21.0	17.8	16.2	15.50	2316	2540	1700	1895	162	838	134	379
Vinhais	41.83	7.08	816	22.0	18.3	18.3	17.20	2421	2699	2041	2346	212	884	228	563
Mean			775	22.09	18.76	18.42	17.48	2517	2875	2090	2466	182	852	180	441
SD			65.8	0.61	0.65	1.07	1.01	143.3	246.2	102.4	206.0	41.6	179.2	49.9	137.2
CV (%)			8.5	2.7	3.5	5.8	5.8	5.7	8.6	4.9	8.4	22.9	21.0	27.7	31.1
Note: OM, organic matter.
Nota: OM, materia orgânica.
B
Local	Texture	pHH2O	OM (%)	P2O5 (mg/Kg)	K2O (mg/Kg)	Ca (cmol/Kg)	Mg (cmol/Kg)	K (cmol/Kg)	Na (cmol/Kg)
Alfândega da Fé	loam	4.7	0.6	53.0	134.3	1.3	0.32	0.34	0.08
Bragança	loam	5.1	4.2	109.9	101.3	1.0	0.26	0.32	0.08
Chaves	sandy loam	5.2	1.0	64.1	135.0	1.0	0.23	0.39	0.10
Mac. Cavaleiros	loam	5.6	2.9	102.5	88.7	2.0	0.38	0.26	0.09
Murça	loam	5.1	2.4	27.6	110.5	0.5	0.23	0.30	0.08
Valpaços	loam	5.0	2.4	230.2	121.0	0.7	0.19	0.33	0.09
Vinhais	loam	5.2	4.6	43.8	209.8	1.3	0.35	0.43	0.52
Mean		5.14	2.60	90.2	128.66	1.13	0.28	0.34	0.15
SD		0.27	1.46	68.6	39.56	0.50	0.07	0.05	0.17
CV (%)		5.3	56.1	76.1	30.7	44.3	25.1	15.9	110.0
Note: OM, organic matter.
Nota: OM, materia orgânica.

Supplementary Table 2. Effect of year, locality and respective interaction on chestnut fruit biometry.
Tabla adicional 2. Efecto del año, localidad y la respectiva interacción en la biometría del fruto de castaña.

									Fruit size (fruits/kg(						Shape index
Local	Length (mm)	Var. (%)	Height (mm)	Var. (%)	Thickness (mm)	Var. (%)	Weigh (g)	Var. (%)	Corrected	Var. (%)	Total	Var.(%)	TF/CF	Var. (%)	Length/height	Var. (%)	Polyspermy (fruits/kg)
2006
Alfândega da Fé	31.4 e	100	32.0 c	100	18.6 d	100	12.0 d	100	90.4 b	100	107.3 d	100	1.19	100	0.987 b	100	ND
Bragança	34.1 b	100	34.2 b	100	20.3 b	100	14.3 b	100	73.2 c	100	88.0 cd	100	1.20	100	1.057 ab	100	ND
Chaves	33.6 c	100	34.1 b	100	20.7 b	100	14.1 b	100	76.7 c	100	105.2 bc	100	1.37	100	0.989 b	100	ND
Mac.Cavaleiros	32.8 d	100	32.4 c	100	20.2 b	100	13.0 c	100	87.2 b	100	126.3 bc	100	1.45	100	1.020 ab	100	ND
Murça	27.8 f	100	26.6 e	100	15.0 f	100	6.9 f	100	157.1 a	100	161.7 a	100	1.03	100	1.050 ab	100	ND
Valpaços	35.2 a	100	35.6 a	100	21.8 a	100	16.9 a	100	62.5 d	100	86.8 d	100	1.39	100	0.993 b	100	ND
Vinhais	33.0 cd	100	31.4 c	100	19.5 c	100	12.0 d	100	92.1 b	100	111.3 bc	100	1.21	100	1.112 a	100	ND
Mean	32.5	100	32.3	100	19.4	100	12.7	100	91.3	100	112.4	100	1.26	100	1.03	100	ND
SD	2.4		2.9		2.2		3.1		30.9		25.7		0.1		0.0
CV (%)	7.3		9.0		11.3		24.2		33.8		22.9		11.6		4.5
2007
Alfândega da Fé	38.3 b	122.0	34.2 c	106.6	21.6 c	116.3	17.0 c	142.2	58.7 bc	65.0	71.7 d	66.8	1.22	66.8	1.121 a	113.6	0.75 ab
Bragança	37.6 bc	110.4	37.9 a	110.7	22.6 b	111.6	18.0 b	125.4	56.0 c	76.5	84.4 cd	96.0	1.51	96.0	1.049 cd	99.2	0.25 ab
Chaves	39.8 a	118.3	37.1 ab	108.7	23.3 ab	112.6	19.7 a	140.1	49.9 d	65.1	79.2 cd	75.3	1.59	75.3	1.075 b	108.7	2.25 a
Mac.Cavaleiros	36.9 d	112.4	35.1 bc	108.3	22.2 c	110.0	17.0 d	131.0	46.4 e	53.2	98.9 bc	78.3	2.13	78.3	1.027 d	100.7	0.67 ab
Murça	35.4 e	127.1	34.5 bc	129.7	21.8 c	145.8	15.2 e	220.4	66.0 b	42.0	111.9 ab	69.2	1.70	69.2	1.053 b	100.3	2.00 ab
Valpaços	37.0 c	105.1	34.5 bc	97.0	23.9 a	109.7	17.1 bc	101.2	58.7 c	93.9	122.4 a	141.1	2.09	141.1	1.078 b	108.6	0.00 b
Vinhais	36.7 e	111.2	34.3 c	109.3	21.5 c	110.0	15.8 d	132.3	65.1 ab	70.8	89.9 cd	80.8	1.38	80.8	1.070 bc	96.2	2.00 ab
Mean	37.4	114.8	35.4	109.3	22.4	115.4	17.1	134.5	57.3	62.7	94.1	83.7	1.66	83.7	1.070	103.9	1.13
SD	1.4		1.5		0.9		1.5		7.3		18.2		0.3		0.03		0.93
CV (%)	3.7		4.2		4.1		8.6		12.7		19.3		20.7		2.8		82.1
Analisys of variance (%)	SL		SL		SL		SL		SL		SL		SL		SL
Year	68.1 ***		36.0 ***		1.8 ns		9.2 ***		44.8 ***		13.6 ***		1.9 ***		19.4 **
Locality	11.2 ***		20.0 ***		0.0 ns		10.2 ***		14.5 ***		20.3 ***		3.2 **		0.7 ns
Year × Locality	11.6 ***		21.2 **		0.7 ns		11.0 ***		28.1 ***		47.7 ***		5.3 **		20.5 ns
Note: Comparisons were made within the parameter, among origins of chestnuts. The values with the same letter are not significantly different, according to the Fisher test, 5%.
SL, significant level; ns, not significant (P > 0.05); ** and ***, significant at P < 0.01 and P < 0.001, respectively.
TF/CT, ratio between total fruit size and corrected fruit size; Var., percentage of variation of 2007's values compared to 2006.
Nota: Las comparaciones han sido hechas dentro del mismo parámetro en las diferentes localidades. Los valores con letras iguales no son significativamente diferentes, según el teste de Fisher, 5 %.
SL – grado de significancia; ns – no significante (P > 0.05); ** y ***, ignificante al P < 0.01 and P < 0.001, respectivamente.
TF/CT – razón entre calibre total y calibre corregido; Var. – porcentaje de variación de los valores de 2007 relativamente a 2006.

Supplementary Table 3. Effect of locality, year and respective interaction on basic chemical composition (g/kg DW) of the chestnut fruits.
Tabla 3. Efecto del año, localidad y la respectiva interacción en la composición química básica (g/kg DW) de los frutos de castaña recogidas.

Local	Dry Year matter	Var. (%)	Crude Protein	Var. (%)	Crude Fat	Var. (%)	Starch	Var. (%)	Soluble Sugar
2006
Alfândega da Fé	555.6 abc	100	48.9 ab	100	30.0 ab	100	366.0 a	100	ND
Bragança	642.0 a	100	45.0 b	100	31.2 a	100	376.0 a	100	ND
Chaves	462.5 c	100	53.8 ab	100	23.0 b	100	404.1 a	100	ND
Mac. Cavaleiros	527.4 bc	100	44.9 b	100	31.8 a	100	396.4 a	100	ND
Murça	616.0 ab	100	55.1 ab	100	29.7 ab	100	395.6 a	100	ND
Valpaços	546.0 abc	100	57.9 a	100	22.8 b	100	400.7 a	100	ND
Vinhais	620.4 ab	100	43.5 b	100	32.2 a	100	392.8 a	100	ND
Mean	567.1	100	49.9	100	28.7	100	390.2	100
SD	63.2		5.8		4.1		13.9
CV (%)	11.1		11.5		14.1		3.6
2007
Alfândega da Fé	511.2 ab	92.0	40.6 c	83.0	30.9 a	102.9	529.5 c	144.7	140.9 a
Bragança	473.8 bc	73.8	46.5 bc	103.4	28.9 ab	92.7	615.9 a	163.8	98.2 b
Chaves	481.5 bc	104.1	52.7 b	98.0	25.3 b	109.7	584.4 ab	144.6	114.4 ab
Mac. Cavaleiros	466.8 cd	88.5	50.0 b	111.6	28.8 ab	90.3	609.7 a	153.8	101.5 ab
Murça	555.6 a	90.2	49.6 bc	90.0	29.0 ab	97.5	630.7 a	159.4	95.7 ab
Valpaços	428.7 d	78.5	86.6 a	149.5	18.8 c	82.4	597.3 a	149.0	108.0 ab
Vinhais	480.1 bc	77.4	53.0 b	121.9	26.4 ab	81.8	540.9 bc	137.7	82.2 b
Mean	485.4	85.6	54.1	108.6	26.8	93.6	586.9	150.4	105.8
SD	39.4		14.9		4.0		38.3		18.5
CV (%)	8.1		27.6		14.9		6.5		17.4
Analisys of variance (%)	SL		SL		SL		SL
Year	36.0***		3.0 ns		2.5 ns		90.5***
Locality	14.2**		42.1***		39.0***		1.6*
Year × Locality	18.0*		29.8***		0.0 ns		1.1 ns
Note: Comparisons were made within the parameter, among origins of chestnuts. The values with the same letter are not significantly different, according to the Fisher test, 5%.
ND, not determined; Var., percentage of variation of 2007's values compared to 2006.
SL – significant level; ns – not significant (P > 0.05); *, ** and ***, significant at P < 0.05, P < 0.01 and P < 0.001, respectively.
Nota: Las comparaciones han sido hechas dentro del mismo parámetro en las diferentes localidades. Los valores con letras iguales no son significativamente diferentes, según el teste de Fisher, 5 %
ND – no determinado; Var. – porcentaje de variación de los valores de 2007 relativamente a 2006.
SL – grado de significancia; ns – no significante (P > 0.05); ** y ***, significante al P < 0.01 y P < 0.001, respectivamente.

Supplementary Figure 1. Influence of total amount of precipitation occurred between May and September in the total fruit size.

Figura adicional 1. Influencia de las precipitaciónes caídas entremayo y septiembre en el tamaño total de los frutos (buenos y los abortados).

Supplementary Figure 2. Effect of temperature amount (May–October) displayed as degree-day (°D) in the total and corrected fruit size. Correlation was done with all local data from 2006 to 2007.

Figura adicional 2. Efecto de la temperatura (mayo–octubre), en grado-día (D°), sobre el tamaño total y el corregido. La correlación se hizo con todos los datos locales de 2006 y 2007.

Supplementary Figure 3. Influences of the temperature amount (May–October) displayed as degree-day (°D) in the percentage starch.

Figura adicional 3. Influencia de la temperatura, en grado-día (D°), sobre el porcentaje del almidón.

Supplementary Figure 4. Dendrogram (A) built according the morphological and chemistry data and dendrogram showing the genetic similarity among different ecotypes (B).

Figura adicional 4. Dendrograma construido según valores morfológicos y químicos (A), y dendrograma mostrando la similitud genética entre los ecotipos (B).

Supplementary Figure 5. Variability of the localities under study, in both years using the first two principal components based on fruit biometry and chemical analysis data.

Figura adicional 5. Variabilidad de las localidades en estudio, en los dos años, utilizando los dos primeros componentes principales basado en los datos de la biometría del fruto y análisis químico.