To gain a deep understanding of maintenance and repair planning, investigate the weak points of the distribution network, and discover unusual events, it is necessary to trace the shutdowns that occurred in the network. Many incidents happened due to the failure of thermal equipment in schools. On the other hand, the most important task of electricity distribution companies is to provide reliable and stable electricity, which minimal blackouts and standard voltage should accompany. This research uses seasonal time series and artificial neural network approaches to provide models to predict the failure rate of one of the equipment used in two areas covered by the greater Tehran electricity distribution company. These data were extracted weekly from April 2019 to March 2021 from the ENOX incident registration software. For this purpose, after pre-processing the data, the appropriate final model was presented with the help of Minitab and MATLAB software. Also, average air temperature, rainfall, and wind speed were selected as input variables for the neural network. The mean square error has been used to evaluate the proposed models’ error rate. The results show that the time series models performed better than the multi-layer perceptron neural network in predicting the failure rate of the target equipment and can be used to predict future periods.

The xanthorrhiza species of the genus Arracacia belongs to the Apiaceae family and is known for its ability to generate tuberous reservoir roots that are harvested annually and marketed fresh in South American countries such as Colombia, Brazil, Venezuela, Peru, Bolivia and Ecuador. In Colombia, arracacha is planted mainly in 15 departments and the regional cultivars are differentiated by the color of the leaves, petiole and tuberous root, the best known being amarilla común or paliverde, yema de huevo, and cartagenera. There are studies that have characterized regional materials by applying a limited number of descriptors, but they do not allow knowing the morphology and phenotypic differentiation of each one; therefore, their definition and characterization constitute a support in breeding programs that allow the efficient use of the genetic potential and increase the knowledge about the diversity of cultivars. Phenotypic characterization and description of three cultivars was performed during two production cycles (2016 and 2018) in two phases (vegetative and productive) applying 74 morphological variables (42 qualitative and 32 quantitative) organized in seven groups of variables: plant, leaf, leaflet, petiole, propagule, stock and tuberous root. A factorial analysis for mixed data (FAMD) was performed, which incorporated a multivariate analysis with all variables and identified 11 discriminant variables, 8 qualitative and 3 quantitative, which can be used in processes of characterization of arracacha materials. A morphological description of each cultivar was made, which means that this is the first complete characterization study of regional arracacha materials in Colombia.

The market demand for uniformity and productivity of commercial carrot roots has prioritized hybrid materials over open-pollinated varieties. In this sense, the objective of this work was to estimate the combining ability of carrot genitors for root productivity and resistance to leaf scorch. The experiments were conducted in Gama, DF, in the agricultural years 2012/13 and 2013/14. We evaluated 33 carrot hybrids, originated from crosses between three male-sterile populations, with 11 male-fertile S2 lines, all the genitors being of tropical origin. At 90 days after sowing, the severity of the leaf blight disease was estimated in the plots. At 100 days after sowing, harvesting was performed and root yield characters were evaluated. Analysis of variance and partial diallel analysis were performed for each year and jointly for both years. It was found that additive and non-additive genes are important in the manifestation of root yield and leaf blight resistance traits in carrot hybrids. The male-sterile parents with higher overall combining ability for root productivity are strains LM-649 and LM-650 and, among the male-fertile, strain LM-555-2-2. The best hybrids for root yield and leaf blight resistance are LM-649 × LM-555-11-1, LM-650 × LM-555-7-1 and LM-650 × LM-554-8-1.

The agronomic and oenological behavior of the Pinot noir grape variety was studied in relation to different rootstocks on the Agroscope estate in Leytron (VS): 3309 C, 5 BB, Fercal, 41 BMGt, Riparia Gloire, 420 AMGt, 101-14 MGt and 161-49 C. Rootstock primarily influenced vigor, speed of vine establishment, and mineral nutrition of the graft. Riparia Gloire, 41 BMGt, 420 AMGt and 161-49 C rootstocks were less vigorous and, for the last three, induced a lower nitrogen and potassium supply leading to the production of slightly more acidic wines. The less vigorous rootstocks and 101-14 MGt were slightly more sensitive to water stress.