Open Access
Genome-wide association mapping of flowering and ripening periods in apple
(Frontiers Media, 2017) Urrestarazu Vidart, Jorge; Muranty, Hélène; Denancé, Caroline; Leforestier, Diane; Ravon, Elisa; Guyader, Arnaud; Guisnel, Rémi; Feugey, Laurence; Aubourg, Sébastien; Celton, Jean Marc; Daccord, Nicolas; Dondini, Luca; Gregori, Roberto; Lateur, Marc; Houben, Patrick; Ordidge, Matthew; Paprstein, Frantisek; Sedlak, Jiri; Nybom, Hilde; Garkava Gustavsson, Larisa; Troggio, Michela; Bianco, Luca; Velasco, Riccardo; Poncet, Charles; Théron, Anthony; Moriya, Shigeki; Bink, Marco C. A. M.; Laurens, François; Tartarini, Stefano; Durel, Charles Eric; Producción Agraria; Nekazaritza Ekoizpena
Deciphering the genetic control of flowering and ripening periods in apple is essential for breeding cultivars adapted to their growing environments. We implemented a large Genome-Wide Association Study (GWAS) at the European level using an association panel of 1,168 different apple genotypes distributed over six locations and phenotyped for these phenological traits. The panel was genotyped at a high-density of SNPs using the Axiom®Apple 480 K SNP array. We ran GWAS with a multi-locus mixed model (MLMM), which handles the putatively confounding effect of significant SNPs elsewhere on the genome. Genomic regions were further investigated to reveal candidate genes responsible for the phenotypic variation. At the whole population level, GWAS retained two SNPs as cofactors on chromosome 9 for flowering period, and six for ripening period (four on chromosome 3, one on chromosome 10 and one on chromosome 16) which, together accounted for 8.9 and 17.2% of the phenotypic variance, respectively. For both traits, SNPs in weak linkage disequilibrium were detected nearby, thus suggesting the existence of allelic heterogeneity. The geographic origins and relationships of apple cultivars accounted for large parts of the phenotypic variation. Variation in genotypic frequency of the SNPs associated with the two traits was connected to the geographic origin of the genotypes (grouped as North+East, West and South Europe), and indicated differential selection in different growing environments. Genes encoding transcription factors containing either NAC or MADS domains were identified as major candidates within the small confidence intervals computed for the associated genomic regions. A strong microsynteny between apple and peach was revealed in all the four confidence interval regions. This study shows how association genetics can unravel the genetic control of important horticultural traits in apple, as well as reduce the confidence intervals of the associated regions identified by linkage mapping approaches. Our findings can be used for the improvement of apple through marker-assisted breeding strategies that take advantage of the accumulating additive effects of the identified SNPs.
Open Access
Assessing the causes of the low productivity of cider apple orchards in the Spanish region of Gipuzkoa
(ISHS, 2022) Miranda Jiménez, Carlos; Crespo Martínez, Sara; Oneka Mugica, Oihane; Laquidain Imirizaldu, María Jesús; Urrestarazu Vidart, Jorge; Santesteban García, Gonzaga; Agronomía, Biotecnología y Alimentación; Agronomia, Bioteknologia eta Elikadura
Apple cider-making has a long tradition in many northern Spanish regions, such as Gipuzkoa in the Basque Country. The production in this region is largely based on traditional local cider cultivars for which very little information is available on their pollination requirements, resulting in a generalized low productivity of the orchards. In this work the self-(in)compatibility, S-alleles and pollen quality have been studied for the main cider varieties grown in Gipuzkoa, which represent a wide genetic diversity. The S-RNase genotype of 25 cultivars is firstly reported here, which allows allocating the cultivars in their corresponding incompatibility group. All the S-alleles have been previously described, being S26, S3 and S5 the most frequently found. Regarding pollen quality triploid cultivars, as expected, showed lower viability (<70%) and germination rates (<20%). Whereas most diploid cultivars showed good pollen viability (>80%) and germination (>30%) rates, it is noteworthy the low performance of ‘Urtebete’, very similar to that of triploids. Self-compatibility tests both in vitro and in situ showed low rates of fruit set and, together with an upper position of the stigmas related to stamens, reveal a low degree of self-compatibility for most cultivars. Surprisingly, two cultivars called ‘Moko’ and ‘Txalaka’, showed certain selfcompatibility with around 7% fruit set. All in all, the results will enable to improve traditional varieties orchard design as well as the profitability of apple cider farms in the region.
Open Access
Hyperspectral imaging to assess the presence of powdery mildew (Erysiphe necator) in cv. Carignan Noir grapevine bunches
(MDPI, 2020) Pérez Roncal, Claudia; López Maestresalas, Ainara; López Molina, Carlos; Jarén Ceballos, Carmen; Urrestarazu Vidart, Jorge; Santesteban García, Gonzaga; Arazuri Garín, Silvia; Ingeniería; Estadística, Informática y Matemáticas; Agronomía, Biotecnología y Alimentación; Ingeniaritza; Estatistika, Informatika eta Matematika; Agronomia, Bioteknologia eta Elikadura; Gobierno de Navarra / Nafarroako Gobernua, Proyecto DECIVID (Res.104E/2017); Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa, FPI-UPNA-2017 (Res.654/2017)
Powdery mildew is a worldwide major fungal disease for grapevine, which adversely affects both crop yield and produce quality. Disease identification is based on visible signs of a pathogen once the plant has already been infected; therefore, techniques that allow objective diagnosis of the disease are currently needed. In this study, the potential of hyperspectral imaging (HSI) technology to assess the presence of powdery mildew in grapevine bunches was evaluated. Thirty Carignan Noir grape bunches, 15 healthy and 15 infected, were analyzed using a lab-scale HSI system (900–1700 nm spectral range). Image processing was performed to extract spectral and spatial image features and then, classification models by means of Partial Least Squares Discriminant Analysis (PLS-DA) were carried out for healthy and infected pixels distinction within grape bunches. The best discrimination was achieved for the PLS-DA model with smoothing (SM), Standard Normal Variate (SNV) and mean centering (MC) pre-processing combination, reaching an accuracy of 85.33% in the cross-validation model and a satisfactory classification and spatial location of either healthy or infected pixels in the external validation. The obtained results suggested that HSI technology combined with chemometrics could be used for the detection of powdery mildew in black grapevine bunches.
Open Access
Analysis of the genetic diversity and structure across a wide range of germplasm reveals prominent gene flow in apple at the European level
(BioMed Central, 2016) Urrestarazu Vidart, Jorge; Denancé, Caroline; Ravon, Elisa; Guyader, Arnaud; Guisnel, Rémi; Feugey, Laurence; Poncet, Charles; Lateur, Marc; Houben, Patrick; Ordidge, Matthew; Fernández Fernández, Felicidad; Evans, Kate M.; Paprstein, Frantisek; Sedlak, Jiri; Nybom, Hilde; Garkava Gustavsson, Larisa; Miranda Jiménez, Carlos; Gassmann, Jennifer; Kellerhals, Markus; Suprun, Ivan; Pikunova, Anna V.; Krasova, Nina G.; Torutaeva, Elnura; Dondini, Luca; Tartarini, Stefano; Laurens, François; Durel, Charles Eric; Producción Agraria; Nekazaritza Ekoizpena
Background: The amount and structure of genetic diversity in dessert apple germplasm conserved at a European level is mostly unknown, since all diversity studies conducted in Europe until now have been performed on regional or national collections. Here, we applied a common set of 16 SSR markers to genotype more than 2,400 accessions across 14 collections representing three broad European geographic regions (North + East, West and South) with the aim to analyze the extent, distribution and structure of variation in the apple genetic resources in Europe. Results: A Bayesian model-based clustering approach showed that diversity was organized in three groups, although these were only moderately differentiated (FST = 0.031). A nested Bayesian clustering approach allowed identification of subgroups which revealed internal patterns of substructure within the groups, allowing a finer delineation of the variation into eight subgroups (FST = 0.044). The first level of stratification revealed an asymmetric division of the germplasm among the three groups, and a clear association was found with the geographical regions of origin of the cultivars. The substructure revealed clear partitioning of genetic groups among countries, but also interesting associations between subgroups and breeding purposes of recent cultivars or particular usage such as cider production. Additional parentage analyses allowed us to identify both putative parents of more than 40 old and/or local cultivars giving interesting insights in the pedigree of some emblematic cultivars. Conclusions: The variation found at group and subgroup levels may reflect a combination of historical processes of migration/selection and adaptive factors to diverse agricultural environments that, together with genetic drift, have resulted in extensive genetic variation but limited population structure. The European dessert apple germplasm represents an important source of genetic diversity with a strong historical and patrimonial value. The present work thus constitutes a decisive step in the field of conservation genetics. Moreover, the obtained data can be used for defining a European apple core collection useful for further identification of genomic regions associated with commercially important horticultural traits in apple through genome-wide association studies.
Open Access
Assessment of flesh browning diversity in apple germplasm collections phenotyped by image analysis
(ISHS, 2023) Miranda Jiménez, Carlos; Irisarri, Patricia; Arellano Zapatero, Julia; Bielsa González, Francisco Javier; Valencia Leoz, Ana; Urrestarazu Vidart, Jorge; Pina, Ana; Santesteban García, Gonzaga; Castel, L.; Errea, Pilar; Agronomía, Biotecnología y Alimentación; Agronomia, Bioteknologia eta Elikadura; Institute for Multidisciplinary Research in Applied Biology - IMAB
Enzymatic flesh browning (EB) is one of the major problems affecting the quality and limiting the shelf life of minimally processed fruit. Traditionally, EB has been measured objectively using colourimeters. However, colourimeters are not suitable for phenotyping large quantities of fruit samples as they measure just one small area of a sample at a time, which hampers the acquisition of representative measurements and renders them time-consuming and costly. Previous research has shown that image analysis of digital photographs could be a viable alternative to obtain colour information of the entire surface of samples for large scale phenotyping, but to date there are no references for its practical application. The aim of this work was to assess the diversity in EB in a large set of cultivars phenotyped using digital photographs and a high-throughput analytical system based on image analysis developed by our team. A set of 143 cultivars from 104 genotypes, including modern references (16 cultivars) and traditional Spanish cultivars from UPNA (67 cultivars) and CITA (60 cultivars) germplasm collections was analysed in 2020 and 2021. The traditional cultivars were part of the core collection, which optimizes the representativeness of the genetic variation of apples preserved in Spanish collections. EB was evaluated in 10 fruits per cultivar and photographed at regular intervals from just after cutting to one hour later. A wide range of EB intensities was observed, with up to 20-fold differences between cultivars, which could be classified into five levels using two indices. The time at which EB was evaluated (30 or 60 min after slicing) had little influence on the classification. Traditional cultivars with low or very low EB were found to be comparable to those of references with less EB. The results show the potential of traditional germplasm to diversify the varietal offer and introduce new traits in apple breeding.
Open Access
Pollen viability, self-incompatibility, and a very singular S-allele structure between the reasons for the limited potential productivity of traditional Basque cider apple varieties
(Elsevier, 2023) Crespo Martínez, Sara; Oneka Mugica, Oihane; Laquidain Imirizaldu, María Jesús; Urrestarazu Vidart, Jorge; Santesteban García, Gonzaga; Miranda Jiménez, Carlos; Agronomía, Biotecnología y Alimentación; Agronomia, Bioteknologia eta Elikadura; Institute for Multidisciplinary Research in Applied Biology - IMAB; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
Cider regions conserve a broad diversity of traditional cultivars for which knowledge has hardly evolved. Key aspects of their reproductive biology are barely known, hindering improvement in orchard management and resulting in highly variable yields. In this study, we characterized key aspects of the reproductive biology of some traditional apple cultivars from the Basque-style cider-producing area in northern Spain (Basque Country and Navarre). We tested for pollen quality, self-compatibility, and cross-compatibility (S-genotyping). The pollen quality was good except for Urtebete, Errezila, Reineta Encarnada, and triploid varieties. Self-pollination results confirm the need for pollinators, as only Moko and Txalaka showed certain self-compatibility. Regarding Sgenotyping, the population proved very singular, with an atypically high frequency of S26, a frequent allele within crabapples, and the appearance of a novel unpublished allele (S60). The knowledge generated for this variety pool will contribute to a better choice of suitable pollinators, preventing the use of popular crabapple varieties that are demonstrated to be partly incompatible with them, and will lead to an increase in potential yields in the region.
Open Access
Sampling stratification using aerial imagery to estimate fruit load in peach tree orchards
(MDPI, 2018) Miranda Jiménez, Carlos; Santesteban García, Gonzaga; Urrestarazu Vidart, Jorge; Loidi Erviti, Maite; Royo Díaz, José Bernardo; Agronomía, Biotecnología y Alimentación; Agronomia, Bioteknologia eta Elikadura
A quick and accurate sampling method for determining yield in peach orchards could lead to better crop management decisions, more accurate insurance claim adjustment, and reduced expenses for the insurance industry. Given that sample size depends exclusively on the variability of the trees on the orchard, it is necessary to have a quick and objective way of assessing this variability. The aim of this study was to use remote sensing to detect the spatial variability within peach orchards and classify trees into homogeneous zones that constitute sampling strata to decrease sample size. Five mature peach orchards with different degrees of spatial variability were used. A regular grid of trees was established on each orchard, their trunk cross-sectional area (TCSA) was measured, and yield was measured as number of fruits/tree on the central tree of each one of them. Red Vegetation Index (RVI) was calculated from aerial images with 0.25 m pixel -1 resolution, and used, either alone or in combination with TCSA, to delineate sampling strata using cluster fuzzy k-means. Completely randomized (CRS) and stratified samplings were compared through 10,000 iterations, and the Minimum Sample Size required to obtain estimates of actual production for three quality levels of sampling was calculated in each case. The images allowed accurate determination of the number of trees, allowing a proper application of completely randomized sampling designs. Tree size and the canopy density estimated by means of multispectral indices are complementary parameters suitable for orchard stratification, decreasing the sample size required to determine fruit count up to 20–35% compared to completely randomized samples.
Open Access
Evaluation of the agronomic performance of 'Syrah' and 'Tempranillo' when grafted on 12 rootstocks
(Julius Kühn Institute (JKI), 2019) Marín Ederra, Diana; García, R.; Eraso Zabalegui, Javier; Urrestarazu Vidart, Jorge; Miranda Jiménez, Carlos; Royo Díaz, José Bernardo; Abad Zamora, Francisco Javier; Santesteban García, Gonzaga; Agronomía, Biotecnología y Alimentación; Agronomia, Bioteknologia eta Elikadura; Gobierno de Navarra / Nafarroako Gobernua; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
Beyond pest resistance, rootstocks significantly influence the performance of grapevine varieties. However, the effect of the rootstock is strongly affected by its interaction with the environment, and it is therefore necessary to evaluate their influence in a particular terroir. With the aim of evaluating the influence of 12 rootstocks on the agronomic performance of 'Syrah' and 'Tempranillo', a trial was established in 2011 and 2012 in Miranda de Arga (Navarra, Spain), under the typical environmental conditions of the Ebro Valley. Growth and yield, as well as industrial and phenolic maturity parameters were analysed during four consecutive seasons (2015-2018). Most rootstocks showed a similar performance with both varieties, not always following the trends reported in bibliography, which highlights the relevance of studying rootstocks in different conditions. 3309 C was the rootstock conferring the highest vigour, whereas the lowest were provided by 420 A MGt and 'Fercal'. The implications on grape composition were much more diverse, and were partially conditioned by yield. Results were obtained during the four first harvests of the vineyard, and could therefore change to some extent as the vineyard reaches stability.
Open Access
Genetic diversity of Spanish Prunus domestica L. germplasm reveals a complex genetic structure underlying
(Public Library of Science, 2018) Urrestarazu Vidart, Jorge; Errea, Pilar; Miranda Jiménez, Carlos; Santesteban García, Gonzaga; Pina, Ana; Producción Agraria; Nekazaritza Ekoizpena
European plum (Prunus domestica L.) is an ancient domesticated species cultivated in temperate areas worldwide whose genetic structure has been scarcely analyzed to date. In this study, a broad representation of Spanish European plum germplasm collected in Northeastern Spain and a representative set of reference cultivars were compared using nuclear and chloroplast markers. The number of alleles per locus detected with the SSR markers ranged from 8 to 39, with an average of 23.4 alleles, and 8 haplotypes were identified. Bayesian model-based clustering, minimum spanning networks, and the analysis of molecular variance showed the existence of a hierarchical structure. At the first level, two genetic groups were found, one containing 'Reine Claude' type reference cultivars altogether with ca. 25% of local genotypes, and a second one much more diverse. This latter group split in two groups, one containing most (ca. 70%) local genotypes and some old Spanish and French reference cultivars, whereas the other included 24 reference cultivars and only six local genotypes. A third partition level allowed a significant finer delineation into five groups. As a whole, the genetic structure of European plum from Northeastern Spain was shown to be complex and conditioned by a geographical proximity factor. This study not only contributes to genetic conservation and breeding for this species at the national level, but also supports the relevance of undertaking similar tasks of collection and characterization in other unexplored areas. Moreover, this kind of research could lead to future coordinated actions for the examination of the whole European plum diversity, to define conservation strategies, and could be used to better understand the genetic control of traits of horticultural interest through association mapping.
Open Access
Applications of sensing for disease detection
(Springer, 2021) Castro, Ana Isabel de; Pérez Roncal, Claudia; Thomasson, J. Alex; Ehsani, Reza; López Maestresalas, Ainara; Yang, Chenghai; Jarén Ceballos, Carmen; Wang, Tianyi; Cribben, Curtis; Marín Ederra, Diana; Isakeit, Thomas; Urrestarazu Vidart, Jorge; López Molina, Carlos; Wang, Xiwei; Nichols, Robert L.; Santesteban García, Gonzaga; Arazuri Garín, Silvia; Peña, José Manuel; Agronomía, Biotecnología y Alimentación; Agronomia, Bioteknologia eta Elikadura; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Ingeniería; Ingeniaritza; Gobierno de Navarra / Nafarroako Gobernua; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
The potential loss of world crop production from the effect of pests, including weeds, animal pests, pathogens and viruses has been quantifed as around 40%. In addition to the economic threat, plant diseases could have disastrous consequences for the environment. Accurate and timely disease detection requires the use of rapid and reliable techniques capable of identifying infected plants and providing the tools required to implement precision agriculture strategies. The combination of suitable remote sensing (RS) data and advanced analysis algorithms makes it possible to develop prescription maps for precision disease control. This chapter shows some case studies on the use of remote sensing technology in some of the world’s major crops; namely cotton, avocado and grapevines. In these case studies, RS has been applied to detect disease caused by fungi using different acquisition platforms at different scales, such as leaf-level hyperspectral data and canopy-level remote imagery taken from satellites, manned airplanes or helicopter, and UAVs. The results proved that remote sensing is useful, effcient and effective for identifying cotton root rot zones in cotton felds, laurel wilt-infested avocado trees and escaaffected vines, which would allow farmers to optimize inputs and feld operations, resulting in reduced yield losses and increased profts.