Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

The “Majes Valley” in the province of Castilla – Arequipa Region, with a tradition in the production of wine and pisco, from grapevines introduced in the mid-sixteenth century, which are still preserved by some producers, with little knowledge of the varietal richness they possess, generating confusion in the identification of varieties and devaluing their winegrower potential. In this work, a varietal survey was carried out by wine-growing areas, characterizing the local varieties of old vineyards, with 14 primary descriptors recommended by the OIV-2009 and genetically identifying a sample of 11 phenotypes with the use of 9-SSR molecular markers when compared in the VIVC international database record. Seven wine-growing areas of the valley and 39 varieties with local names were identified, initially forming 13 groups of different names, which when analyzed by means of the canonical discriminant analysis and of main components, high inter- and intra-group phenotypic variability is evidenced due to the influence of some characters. In the analysis of the berry color the blue-black coloration predominates. Four varieties registered in the VIVC were genetically identified, corresponding to ´Listan Prieto` (syn. Negra Criolla and Moscatel), ´Quebranta` (syn.Vinera), ´Muscat Hamburg` (syn.Italia Negra) and ´Jacquez` (syn. Borgoña Majeña) and 2 unregistered varieties “Cantarita” and “Aceituna de Cotahuasi”. A varietal diversity with characteristics of interest in viticulture and plant breeding is observed, with contribution to the varietal identity of known and new creole varieties, contributing to the heritage value of the vine.

Cocoa (Theobroma cacao L.) is one of the main crops in Latin American and African countries, its almonds being marketed to produce chocolate. However, different biotic factors can negatively affect the crop production, especially on small farms where management by farmers is scarce or nonexistent. Lethal wilt (Ceratocystis cacaofunesta Engelbrecht & Harrington) together with beetle borers (Coleoptera: Curculionidae: Scolytinae), continue to be the main problems affecting cocoa. It has been observed that both organisms interact intrinsically inside the trunks of cacao trees. Despite the importance of this interaction, in general, the countless research and review articles carried out to date have focused mainly on studying each biotic factor separately or have been addressed in a general way. Thus, in this review we mainly focus on the interaction between the Lethal wilt and the borer beetles, especially how and which is the insect that transmits the disease in cocoa plants. Additionally, an exhaustive characterization of Xyleborus ferrugineus as a possible vector of C. cacaofunesta in cacao trees has been made. From this review, we can say that Ceratocystis species still need to be fully identified and differentiated, a deeper understanding of the ecology of the scolithid X. ferrugineus, to study the interaction between C. cacaofunesta and vectors from the host response and generate new studies, and the chemical ecology of the fungus-vector-tree still needs to be understood.

The globally distributed necrotrophic fungus Macrophomina phaseolina is the causal agent of economically important crop diseases such as soybean charcoal rot. This fungus secretes a wide variety of proteins and metabolites that allow it to invade the plant and initiate the infection process. The role of fungi secreted proteins with hydrolytic activity in the infection process has been extensively studied; proteins without enzymatic activity could also play an important role in this process. The analysis of total proteins would allow to broaden the knowledge about this pathogen and establish more efficient strategies for its control. The objective of the present work was to evaluate three methods for the extraction of proteins secreted by M. phaseolina. The fungus was grown in potato dextrose broth (PDB) and Czapek-Dox (CZP) with and without soybean leaf supplementation. Proteins were extracted from the lyophilized filtrate of PDB medium using three extraction methods and analyzed by SDS-PAGE. The protein precipitation with trichloroacetic acid in acetone was selected because it showed a better resolution of the protein profile. The filtrate of M. phaseolina grown in PDB supplemented with soybean (MpPDBs) presented the highest yield of protein extraction of secreted proteins among all conditions evaluated. The protein profiles of PDB medium with and without supplementation showed seven differential bands, one of the specific, detected in MpPDBs. These results constitute a basis for studies on the implication of proteins secreted by the fungus in the infection process.

Agriculture and water resource are highly threatened due to climate change, increasing the probability of backsliding on almost every aspect of sustainable development worldwide. For instance, water resource distribution throughout the Peruvian territory is not homogeneous. Hydrometeorological phenomena also threaten it, so it is crucial for the agriculture sector and water management to increase resilience against climate change. The study aims to understand the Peruvian conduct under the United Nations Framework Convention on Climate Change (UNFCCC) regime. Its influence in the Peruvian adaptation regulation and public institutions over the years and the interaction with the latest commitment to the UNFCCC related to climate change agriculture - water resources. The methodology used for the study was qualitative, delivered throughout a documentary analysis, and narrative design among scientific papers, UNFCCC documentation, and Peruvian regulation to weave the experience occurred and the sequences of the events to set up a general narrative. The results show that Peru has active participation in the UNFCCC, particularly under a neoliberalism approach. The convention pushed institutional and regulatory development of the Peruvian Government constantly. Also, after the Paris Agreement, one of the most important influences was the implementation of Law N° 30754 on climate change, which articulates all the regulations related to it, providing a national, more substantial legally-binding commitment. Finally, it is important for Peru to analyze the achievement of current adaptation actions and keep studying the impacts of climate change at a local level to develop a bottom-up approach for an effective policy formulation-implementation.

Quinoa (Chenopodium quinoa) is an Andean pseudocereal produced in countries such as Bolivia, Peru, Ecuador and southern Colombia, with more than 3,000 varieties, distinguished by their nutritional properties and adaptation to different agro-ecological zones. Quinoa's nutritional profile stands out for its protein, carbohydrate, lipid and gluten-free content; it is rich in vitamins; and it is an excellent source of minerals, such as calcium, magnesium, iron and phosphorus. It is one of the few foods that have in its composition all the essential amino acids, standing out from other cereals such as rice or wheat. It is an excellent source of bioactive compounds, which have antioxidant, cytotoxic, antidiabetic and anti-inflammatory properties. With respect to quinoa leaves, several studies have indicated that they have higher protein content than grains, as well as inorganic nutrients such as calcium, phosphorus, iron and zinc. In addition, they can potentially serve as a rich source of phenolic compounds and carotenoids. Conventional heat treatments greatly or slightly affect the composition of the food, including bioactive compounds and antioxidant capacity. Germination provides the product with greater bioavailability and an increase in bioactive compounds. The purpose of this work was to document research on quinoa and its leaves, the effect of thermal treatments and germination on its bioactive compounds, in order to promote the creation and innovation of products based on its bioactive compounds, thus combating malnutrition in our population.

Chia seeds are nutritious food because they have a high content of protein, polyunsaturated fatty acids (omega-3 and omega-6) and phenolic compounds. During storage, fatty acids are degraded, by oxidative and hydrolytic reactions, forming free fatty acids (FFA). In this work, we used Near Infrared Hyperspectral Imaging (NIR- HSI) and chemometrics to predict FFA acid value and fatty acids concentrations in chia seeds during storage. First, we explore the hyperspectral images by Fuzzy c-means (FCM), where it is possible to observe as chemical compounds are formed or degraded during storage. Second, PLSR models were developed to predict FFA value and fatty acids concentration. RPD values reached values higher then 2.0, indicating a good ability to estimate these chemical compounds, especially polyunsaturated fatty acids omega-3 and omega-6. Finally, NIR-hyperspectral imaging coupled with chemometrics allowed us to show the chemical degradation process of chia seeds during storage, mainly associated with polyunsaturated fatty acids degradation. Besides NIR-HSI showed to be a powerful technique to quantify the main fatty acids with high accuracy.

A novel approach to strengthen maize breeding strategies is the use of the multi-trait stability index (MTSI), this index allows the identification of more stable and high-yielding genotypes with greater reliability than previous methods. To select outstanding purple popcorn S1 lines based on the MTSI, 80 purple popcorn S1 lines were evaluated in three environments. 11 characteristics were studied: expansion volume (VE), pigmented pericarp (PP), grain yield (GY), expansion percentage (PE), male flowering (FM), ear length (LM), grain moisture (HG), plant height (AP), weight of 100 grains (PG), volume of 100 grains (VG) and expanded grain size (TG). The results indicated that the environmental differences contributed to a greater extent to the total variation, followed by the genotypic differences, both were significant for all the variables, in addition, the genotype x environment interaction was significant in 10 of 11 characteristics evaluated. According to the MTSI and with a selection pressure of 15%, 12 purple popcorn S1 lines were selected as the most stable and high yielding among the 80 genotypes evaluated. The selected S1 lines will be converted into double haploid lines and evaluated for their general and specific combinatorial abilities, likewise, the unknown antioxidant capacity will be determined.

The objective of this study was to evaluate the quality of surface water used for irrigation in the Huallaga basin. We worked with water quality monitoring data in the basin conducted by the National Water Authority (ANA) counting 139 monitoring points, evaluating 41 parameters for the period 2014 - 2019, the Peruvian Water Quality Index (ICA - PE) intended for irrigation was calculated, using as reference values the Environmental Quality Standard (ECA) for surface water in category 3 D1 (irrigation water). Of the 139 monitoring points, 26 (18.71%) were of excellent quality, 62 (44.60%) of good quality, 35 (25.18%) of fair quality, 13 (9.35%) of poor quality and 3 (2.16%) of very poor quality. The main contaminants found were thermotolerant coliforms, Escherichia coli, which on average exceeded the ECA by 606 and 288 times and by 53.4% (1029/1927) and 38.9% (701/1803) respectively. Contamination by organochlorine pesticides, in 100% (10/10) of the chlordane measurements the RCT was exceeded and with respect to Endrin, Aldrin and DDT the RCT was exceeded in 40% (10/25). The pH, in 25.6% of the measurements the water was outside the ranges tending to alkalinity and for manganese, iron and aluminum, exceeded the ECAs in 17.7%, 13.3% and 11.2% respectively. The main contaminant sources are agricultural and municipal wastewater and the presence of critical points of solid waste.

Advances in data management technologies are being adapted to resolve difficulties and impacts that aquaculture manifests, some aspects that over the years have not been fully managed, are now more feasible to solve, such as the optimization of variables that intervene in the growth and increase of biomass, the prediction of water quality parameters to manage and make decisions during farming fish, the evaluation of the aquaculture environment and the impact generated by aquaculture, the diagnosis of diseases in aquaculture fish to determine more specific treatments, handling, management and closure of aquaculture farms. The objective of this article was to review within the last 20 years the various techniques, methodologies, models, algorithms, software, and devices that are used within artificial intelligence, machine learning and deep learning systems, to solve in a simpler way, quickly and precisely the difficulties and impacts that aquaculture manifests. In addition, the fundamentals of artificial intelligence, automatic learning and deep learning are explained, as well as the recommendations for future study on areas of interest in aquaculture, such as  the reduction of production costs through the optimization of feeding based on good aquaculture practices and parameters of water quality, the identification of sex in fish that do not present sexual dimorphism, the determination of quality attributes such as the degree of pigmentation in salmon and trout.

Fish larvae counting is a technique applied in aquaculture to determine the efficiency of the induction stage and to know the number of fertilized larvae. For this reason, the research aims to improve the count of larvae under 3 fundamental pillars: precision, error and time. For this, we carried out an experimental investigation under a completely randomized design with two counting systems: traditional and artificial vision; each one with 10 repetitions, with 2000 larvae; Later, we carried out the count by means of artificial vision using a camera that captured images of a fish tank with moving fish. The results show that the proposed method is feasible for counting larvae, with 92.65% accuracy, 7.41% error and an average time of 61 seconds per repetition in relation to the traditional counting system: accuracy 64.44%, error 35.61% and time 2009.3 s. The developed system can be replicated in the aquaculture sector due to its effectiveness and cost.