Effect of proximity to Jujube (Ziziphus lotus and Ziziphus jujube) trees on medfly (Ceratitis capitata) populations in citrus orchards of Moulouya Perimeter

Moulouya Perimeter is one of the most important zones of Citrus production in Morocco, with an area of 22.000 ha and 360.000 tons of Citrus production. Medfly “Ceratitis capitata, Wiedemann 1824” is a pest with an important economic impact for Citrus, because of its impact on yield losses and phytosanitary concern linked to its presence. In Citrus orchards of Moulouya perimeter, adjacent wild jujube (Ziziphus lotus and Ziziphus jujuba) trees may have an impact on Medfly populations. The main objective of this study is to evaluate the influence of adjacent jujube trees, growing in windbreaks and noncommercial orchards, on medfly captures in the traps located in citrus orchards and to determine the amount of increase of punctured fruits caused by medfly oviposition considering the distance ranges to the jujube trees (10, 25, 50, 75, 100, 125, 150, 175, 200, 225, 250 and 275m).To achieve this purpose, 180 traps were placed in 15 orchards and monitored for medfly captures weekly, from April to November 2019, within three locations (Aklim, Chouihia, and Reggada) representing Citrus producing area of Moulouya Perimeter. The monitoring of C. capitata adults was conducted using “Maghreb med” traps with trimedlure (tbutyl-4(or5)-chloro-2-methyl-cyclohexane carboxylate) male-specific para-pheromone as attractant and dichlorvos as a toxicant. Five orchards per each location were selected and 12 traps were hung in every orchard in fixed distances from the jujube trees and fruits were checked for punctures. The influence of each jujube tree in citrus orchards in his vicinity is higher within distances inferior to 75 m. Then, its impact could approach 2,25 Ha on average, and in this area, C. capitata population densities were twice to five times as high as in other distances. Furthermore, Citrus trees located at distances inferior to 75m from the jujube trees showed an increase in the percentage of punctured fruits compared with distances higher than 75m

Assessment of the main causes of sorting gaps in the Citrus packinghouses of Berkane, Morocco

Sorting gaps are one of the main challenges that the Citrus industry is facing worldwide. In Morocco, the rates of sorting gaps reach levels exceeding 40% on average. In Berkane area, the rate of Clementine sorting gaps in packinghouses is an important concern to exporters and their characterization is not well studied. The present study covered five clementine packinghouses of Berkane area out of the 20 packinghouses inventoried in the zone during the 2019/2020 export campaign between October 20th, 2019, and January 20th, 2020. In each packinghouse, the sorting gaps were examined and characterized to separate the different categories of sorting gaps types and determine the sorting gaps rate. The objective of this study is to characterize the frequent causes of Clementine sorting gaps and analyze the effect of the packing period on the importance of the rate of different types of causes of sorting gaps. Also, the evolution of gap rates at the station level was analyzed to show the similarities and differences between the overall sorting gaps rates and the sorting gaps rates by type of defects per packinghouse. Results showed an average of sorting gaps rates of about 38.4% of total Clementine fruit received in packinghouses. Depending on the packaging period, the rates of sorting gaps varied from one packinghouse to another and from one type of gaps to another. The gaps caused by insects presented high levels in the area and at all Berkane studied packinghouses. Fruits processed in the period from October 20th to November 20th, 2019 recorded a very high rate of sorting gaps with 44.5% followed by the period from December 20th, 2019 to January 20th, 2020 with a rate of 40% and the period from October 20th to November 20th, 2019 with 31%. In quest of conceiving strategies to reduce Sorting gaps rates, it is of utmost importance to understand the main factors influencing these rates in all Clementine handling and producing stages. Keywords: Sorting gap, Citrus fruits, Packinghouse, Causes, Berkane

Key fruit flies species (Diptera, Tephritidae) reported in Africa and presenting a biosecurity concern in Morocco: An Overview

Fruit crop species are from the most widely cultivated crops in Morocco. However, the sustainability of this lucrative business is threatened by infestations of invasive fruit flies (Diptera: Tephritidae) that may inflict heavy economic losses to the country if their invasion occurs. At this time, Medfly is the main fruit fly which causes a high loss and is a phytosanitary concern to fruit species. The distribution and abundance of the major frugivorous tephritids are influenced by host presence, climatic factors, and their potential of invasion. Two types of economic impact of fruit flies are distinguished, direct losses in the yield and indirect losses due to the loss of markets caused by quarantine restrictions imposed by importing countries to prevent the entry of exotic flies in their territory. The most important invasive tephritid fruit flies present in Africa and that may constitute a risk of invasion into Morocco are Bactrocera dorsalis, Bactrocera zonata and Bactrocera cucurbitae. Also, the indigenous species within genera Ceratitis ((Ceratitis quinaria, C. anonae, C. catoirii, C. cosyra, C. silvestrii, C. ditissima, C. fasciventris, C. rosa, C. quilicii) and Dacus (Dacus latifrons, D.vertebratus, D.bivittatus, D.punctatifrons,  Dacus ciliates) may present a risk of introduction to Morocco. These fruit fly species are characterized by having a wide range of host plants and a wide distribution throughout Africa. The risk of spread is enhanced by the lack of control and the weakness of the identification process of the present and newly introduced species. This review presents the status and the distribution of major fruit fly species present in Africa, gives an overview of their host plants, new invasions and means of detection and phytosanitary measures to implement in Morocco to avoid any invasion originated from other African countries. Keywords: Africa, Fruit fly, Distribution, host plant, Invasion, biosecurity, and Morocco

Incidence of Citrus exocortis viroid and Hop stund viroid in commercial citrus groves from Morocco

Viroids are the smallest known pathogens of plants. They are single-stranded, circular, rod-like RNAs with no protein capsid nor any detectable messenger activity. Citrus species are natural hosts of at least seven viroids of the Pospiviroidae family. Exocortis and cachexia are the most important viroid diseases of citrus in Morocco. In order to assess the incidence and distribution of Citrus exocortis viroid (CEVd) and Hop stunt viroid (HSVd), extensive surveys were conducted, between 2008 and 2018, in the main citrus growing areas of the country. A total of 100 commercial citrus groves of different varieties were inspected for symptoms of exocortis and cachexia, and 5390 samples were collected for laboratory analyses, using imprint hybridization. Representative positive and negative samples for each viroid were selected and submitted for additional confirmatory RT-PCR assays using specific primers. The incidence of infection by viroids was about 29.0 %, regardless of citrus species and location, although a slightly higher number of infected trees were located in the Gharb region (41.5 %). CEVd was detected in 11.3 -18.2% of the tested samples, while HSVd was detected up to 10.8 % of the samples tested. Since CEVd and HSVd are readily mechanically transmissible via working tools, they affect both old and young plantings in all the surveyed regions. Key words: Citrus exocortis viroid, Hop stunt viroid, citrus, survey, Morocc

University students' conceptions about the concept of gene: Interest of historical approach

International audienceConcepts of genetics are often difficult to teach, specifically the central concept of gene. Even the scientists disagree when defining this concept. This paper investigates university students' understanding about the gene and its functions. The results show the dominance of two conceptions of the gene: the Neoclassical model and the Mendelian model. The existence of hybrid conceptions and the lack of the modern model show that students are unable to mobilize the knowledge taught in biology. These results suggest to improve the teaching methods of genetics, for instance, by developing activities that bring students face to face with their conceptions

Multimodal Emotional Classification Based on Meaningful Learning

Emotion recognition has become one of the most researched subjects in the scientific community, especially in the human–computer interface field. Decades of scientific research have been conducted on unimodal emotion analysis, whereas recent contributions concentrate on multimodal emotion recognition. These efforts have achieved great success in terms of accuracy in diverse areas of Deep Learning applications. To achieve better performance for multimodal emotion recognition systems, we exploit Meaningful Neural Network Effectiveness to enable emotion prediction during a conversation. Using the text and the audio modalities, we proposed feature extraction methods based on Deep Learning. Then, the bimodal modality that is created following the fusion of the text and audio features is used. The feature vectors from these three modalities are assigned to feed a Meaningful Neural Network to separately learn each characteristic. Its architecture consists of a set of neurons for each component of the input vector before combining them all together in the last layer. Our model was evaluated on a multimodal and multiparty dataset for emotion recognition in conversation MELD. The proposed approach reached an accuracy of 86.69%, which significantly outperforms all current multimodal systems. To sum up, several evaluation techniques applied to our work demonstrate the robustness and superiority of our model over other state-of-the-art MELD models

Multimodal Emotional Classification Based on Meaningful Learning

Emotion recognition has become one of the most researched subjects in the scientific community, especially in the human–computer interface field. Decades of scientific research have been conducted on unimodal emotion analysis, whereas recent contributions concentrate on multimodal emotion recognition. These efforts have achieved great success in terms of accuracy in diverse areas of Deep Learning applications. To achieve better performance for multimodal emotion recognition systems, we exploit Meaningful Neural Network Effectiveness to enable emotion prediction during a conversation. Using the text and the audio modalities, we proposed feature extraction methods based on Deep Learning. Then, the bimodal modality that is created following the fusion of the text and audio features is used. The feature vectors from these three modalities are assigned to feed a Meaningful Neural Network to separately learn each characteristic. Its architecture consists of a set of neurons for each component of the input vector before combining them all together in the last layer. Our model was evaluated on a multimodal and multiparty dataset for emotion recognition in conversation MELD. The proposed approach reached an accuracy of 86.69%, which significantly outperforms all current multimodal systems. To sum up, several evaluation techniques applied to our work demonstrate the robustness and superiority of our model over other state-of-the-art MELD models