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Quality control of flour is essential to control the quality of bread produced from it. We propose a control method based on the morphological characteristics of the granules of starch. The automation of the identification, segmentation and determination of the average size of the granules of starch of each of the cereals that make up a flour, from microscopy images, is an essential procedure for producers who want to produce bread under the protected geographical indication (PGI) ‘Galician Bread’. This identification and counting procedure, if performed manually, is a tedious activity for a trained expert, and is very time consuming. Thus, automating this task would streamline the process, in addition to saving a great deal of time. This paper addresses this problem by using deep learning approaches (Mask R–CNN) to predict the type of the granule of starch and its size for the first time. The trained models are then evaluated with the same raw microscopy images of these granules observed under polarized light, as has been previouly used for manual identification and counting. A dataset comprising 1308 2564 × 1924-pixel images is analysed. The images contain 17000 labelled granules of starch for two types of wheat: commercial wheat flour from ‘Castilla’ (type 0) and the Galician autochthonous flour ‘Caaveiro’ (type 1). The number of samples is approximately the same for each class. Instance segmentation with Mask R–CNN (Model II) achieved valid results for unseen images, with a categorical global accuracy of about 88.6% and with a discrepancy with respect to the areas of the granules as estimated by a human expert of less than 4%. The performance achieved by Mask R–CNN produces a strong correlation between the results of an expert and the results of the network, confirming the practical validity of our proposal

The genetic erosion of the European grapevine diversity in the last century has promoted the conservation of varieties in germplasm banks to prevent their disappearance. The study of these varieties is necessary as it would allow the diversification of the wine market, as well as provide a source of genes to face new pathogens or climate constraints. In this work, the grapevine varieties preserved in the "Estación de Viticultura e Enoloxía de Galicia" (EVEGA) Germplasm Bank (Ourense, Spain) were widely characterized, combining ampelography, ampelometry, agronomy, and phytopathology. Moreover, genetic characterization was carried out through the analysis of 48 single-nucleotide polymorphisms (SNPs). A Bayesian analysis based on the SNP data was carried out to define the genetic structure of the EVEGA Germplasm Bank, which allowed the differentiation of two main reconstructed panmictic populations (RPPs), confirming previous results obtained based on microsatellite markers (SSRs). A great diversity between varieties was found for almost every parameter evaluated for ampelography, ampelometry, phytopatology, phenology, and berry quality. A principal component analysis (PCA) performed with these phenotypical data allowed discrimination among some groups of varieties included in different genetic populations. This study allowed us to evaluate the grapevine diversity maintained in the EVEGA Germplasm Bank and characterize varieties of potential value for breeding programs of interest for the Galician viticulture.

The analysis of simple sequence repeats (SSRs) and of bulk ground samples by droplet digital polymerase chain reaction (ddPCR) was investigated as an alternative to individual kernel testing for assessing the presence of local cultivars in common wheat (Triticum aestivum L.) varietal blends. The recent Protected Geographical Indication (PGI) of ‘Pan Galego’ (Galician bread) requires that the flour comprise a minimum 25% local wheat cultivars. As a test for compliance with this minimum level, wheat flours were prepared by mixing commercial flours with 0%, 5%, 20%, 25% and 30% ‘Caaveiro’ and 100% ‘Caaveiro’ and 100% commercial flours were used as controls. A second analysis was performed with a second set of wheat flours with 5% and 25% ‘Caaveiro’. These were mixed with two different commercial flours to assess the potential ability of five SSRs to identify the percentage of ‘Caaveiro’, constituting the first reference of the use of SSRs in the traceability of specific autochthonous cultivars in flour blends. ddPCR using the QX200 system platform was used to the targeted proportions across the simulated range with two out of five SSRs, indicating that they can be used in the traceability of ‘Caaveiro’ in mixed flours and breads

‘Galician Bread’ is a traditional baked product and a national benchmark that has recently been granted the European mark of Protected Geographical Indication (PGI), which requires at least 25% of the flour to be produced from autochthonous varieties such as ‘Caaveiro’. The objective of this work was to find a method that guarantees the presence and the percentage of ‘Caaveiro’ wheat in blended flours by using microscopy techniques. Using optical microscopy, including bright-field and polarizing microscopy, autochthonous and foreign flours were analyzed and compared. ‘Caaveiro’ starch presented a different birefringence pattern (associated with a higher amount of amylose) with respect to other cultivars used to produce flours, a feature used to make a computation of the two starch granule types in the mixtures of ‘Caaveiro’ with foreign flours. Repetitions with different mixture percentages allowed us to develop a mathematical model to estimate the percentage of ‘Caaveiro’ flour present in the mixture. Firstly, the most effective method for preparing samples was determined by ensuring the homogeneity of the samples and, subsequently, a validation was carried out with blind samples. Starch birefringence properties allowed the detection of ‘Caaveiro’ wheat flour in mixtures with foreign/Castilian wheat flours and to determine the percentages used in the flour mixtures applying a calibration line (R2 = 0.9577). Deviations were due to the difficulty in obtaining precise mixtures of the blended flours, as happened with other Simple Sequence Repeat (SSR)-based methods used in the same samples. This is a novel method for detecting contraventions/infractions of the percentage of ‘Caaveiro’ used in wheat flours, which is simple, effective and inexpensive

Crop rotation represents a potentially sustainable strategy to address environmental problems of intensive agricultural practices, such as soil degradation, biodiversity reduction, and greenhouse gas emissions. This manuscript assesses the environmental and economic implications of introducing lupin cultivation into winter wheat-based rotation systems under an organic regime in Galicia, Spain. Life Cycle Assessment methodology was used to determine the environmental impacts of three rotation systems over a six-year period: lupin → wheat → rapeseed (OA1), lupin → potato → wheat (OA2), and lupin → wheat → rapeseed ‖ maize (OA3). For a robust assessment, three functional units were applied: land management (ha), economic indicator (gross margin in euros) and protein content (1 kg of protein-corrected grain). Moreover, the environmental profiles were compared with rotation systems without lupin crop in a conventional regime. In terms of Global Warming, impacts of about 2214, 3119 and 766 kg CO2eq·ha−1 were obtained for OA1, OA2 and OA3, respectively. Moreover, OA1 is the best rotation in terms of land and protein. Meanwhile, OA2 rotation is the best choice in the economic function, as it obtained the highest level of gross margin (5708 €·ha−1). Furthermore, with the exception of acidification, organic systems are less impactful than conventional systems. Ammonia emissions from the use of manure are the reason for these higher impacts. Organic rotations OA1 and OA2 have about 6 % or 15 % less gross margin than their conventional counterparts, respectively, however, an increase of 28 % was obtained for rotation OA3. This study helps decision-makers to implement environmentally and economically viable strategies

Avaliación da resposta do trigo autóctono (Triticum aestivum L.) en rotación con Lupinus albus L. doce incluíndo un ano de barbeito fronte ao monocultivo, na localidade de Tabeaio, concello de Carral, na Provincia da Coruña. Os resultados mostraron como a rotación influíu no rendemento de gran, nas impurezas en forma de sementes doutras especies, no peso hectolitro e no peso de mil sementes. O monocultivo afectou negativamente ás variables anteriores. Por outro lado, contribuíuse a avaliación do perfil ambiental de diferentes rotacións con variedades locais de trigo. Os resultados mostraron o efecto positivo destas variedades nas rotacións e na produción de pan. A menor dependencia de agroquímicos sumada ao beneficio da maior achega de residuos ao solo, confírenlle un mellor perfil ambiental.

El trabajo de Tesis Doctoral, La identidad cultural del cultivo de maíz en México: importancia y retos ante la apertura comercial de transgénicos, se basa en la aplicación de técnicas bibliométricas, análisis de productividad agrícola y herramientas de sistemas de información geográfica, orientadas a delimitar áreas con alta diversidad de razas de maíz nativas y asociar su cultivo con la riqueza etnográfica de las regiones, con el objetivo de establecer regiones prioritarias de conservación in situ de razas de maíz nativas donde se restrinja el cultivo de variedades transgénicas.

Mexico, as a center of origin of maize, presents a high diversity of maize races. With the objective of spatially demarcating regions with high concentration of intraspecific diversity in Mexico, as a fundamental measure for the in situ conservation of their agrobiodiversity, Geographic Information Systems (GIS) tools have been used to generate diversity and richness indexes for 64 maize races cultivated in Mexico, using indexes to demarcate relationships to environmental factors such as temperature, precipitation, and altitude; the presence of indigenous groups; and the type of maize used. These relations allowed defining seven environmental units spatially, with characteristic maize races in each of them, which constitute priority areas for in situ conservation. In addition, a close relationship was found between the diversity of maize races and of ethnic groups, from the center to the south of the country, associated with the differences in maize use in different ethnic groups. This geographical demarcation of races and uses of maize will favor food security through specific measures of in situ conservation, as well as an increase in added value of maize by-products based on specific maize races conserved by local ethnic groups

Maize is the grain cereal that is the basis of human and animal diets in Mexico and Latin America; it constitutes an essential crop for global food security. The objective of this study was to analyze the spatial–temporal evolution of scientific production on the theme of GMO maize, through a bibliometric analysis of the texts available in the main editorial houses (Elsevier, Scopus, and Springer), open access journal articles database (Conricyt, Scielo, Redalyc, Latindex, Claryvate Analytics, Periodica, and DOAJ), and freely accessible web search engine Google Scholar, to determine the factors that influence the impact of the studies. From 1991 to 2019, 917 texts were found whose spatial–temporal evolution showed a linear growth that concentrated in Latin America (58.56%). The low impact (measured by the number of bibliographic citations) of scientific studies developed in countries of Latin America was related to their publication in journals edited in their own countries and in Spanish, which restricts the constructive criticism of peer review. For the case of Mexico, a spatial discrepancy was also found between research centers and production areas, which limits the transference of technology; and no specialized author in theme of GMO maize was found; the researchers responded to “scientific trends” in agreement with the agrarian policies of the time

This work investigated the genetic diversity of 134 Castanea sativa Mill. accessions present in the Italian region of Emilia-Romagna. Samples were taken from three collection fields (Granaglione, Zocca and Paloneta) in the Tuscan-Emilian Apennines. The accessions were analyzed by using 16 microsatellite markers (SSR). Genetic distances among accessions, calculated through the DICE coefficient, were used to construct an UPGMA cluster analysis. One major genotype (named “Marroni”) was identified across the three investigated collection fields; this variety corresponds to a sweet chestnut cultivar that has been propagated and widely diffused in the Emilia-Romagna region. Other genotypes were represented by different varieties of Italian chestnuts. The results of this study will be used to define and share guidelines for the characterization and varietal certification of the chestnut varieties in the Emilia-Romagna region