Cassava Crop Research Articles

Characterization of xanthan gum–metal complexes biosynthesized using a medium containing produced water and cassava processing residues

The use of residues from petroleum and crop industries is a feasible and sustainable alternative approach for the production of xanthan gum (XG). This study aimed to evaluate the biosynthesis of XG and the resulting final product obtained using Xanthomonas axonopodis pv. manihotis 1182 in a medium containing produced water (PW) and cassava processing residues. The combined use of PW and cassava crop residues was beneficial for XG production, achieving a product yield of 6.80 g L−1. The micrographs of recovered XG revealed the presence of elongated fiber-like microstructures rather than large agglomerates. The X-ray diffraction profiles of recovered xanthan comprised well-defined peaks rather than an amorphous halo. The thermogravimetry profiles revealed the presence of approximately 60 % of remaining solids in recovered xanthan, in contrast to 30 % in the commercial sample. All the samples demonstrated a pseudoplastic behavior; however, the consistency indices of the recovered samples were approximately 50-times lower than those of commercial XG. The emulsification indices of the recovered XG were > 50 % and comparable to those of commercial xanthan. In this study, for the first time, we obtained a complex XG–metal structure possessing a high emulsification capacity and low viscosity.

Forecast Of Rainfed Agricultural Production In The State Of Pernambuco, Brazil

This research assesses rainfed agricultural production in the state of Pernambuco, which has 137 of its 185 municipalities officially characterized as being part of the semi-arid climate regime. The study classified rainfall periods in Pernambuco between 1944 and 2022 and investigated rainfall instability and its impact on aggregate productivity, aggregate harvested area and production value per hectare of bean, cassava and maize crops. The Auto-Regressive Integrated Moving Average model with Exogenous Variable Inputs (ARIMAX) was used, considering rainfall as an exogenous variable. The results showed that rainfall has a direct effect on the variables investigated, especially the harvested area. It was proven that in periods classified as normal and rainy, productivity, harvested area and production value per hectare showed higher results than those observed in the dry periods of, as was the assumption of the research. The study also confirmed that the models developed were parsimonious and capable of predicting the variables investigated. The results showed that productivities, harvested areas and production values per hectare for beans, cassava and corn experienced greater instability during periods of drought. The research also shows that the aggregated production values per hectare for the three crops are very low. In dry years, they are even lower than the minimum wage. This result confirms that the rural areas of Pernambuco where these crops are mostly grown are very poor

Cassava disease detection using a lightweight modified soft attention network.

Cassava is a high-carbohydrate crop that is at risk of viral infections. The production rate and quality of cassava crops are affected by several diseases. However, the manual identification of diseases is challenging and requires considerable time because of the lack of field professionals and the limited availability of clear and distinct information. Consequently, the agricultural management system is seeking an efficient and lightweight method that can be deployable to edged devices for detecting diseases at an early stage. To address these issues and accurately categorize different diseases, a very effective and lightweight framework called CDDNet has been introduced. We used MobileNetV3Small framework as a backbone feature for extracting optimized, discriminating, and distinct features. These features are empirically validated at the early intermediate stage. Additionally, we modified the soft attention module to effectively prioritize the diseased regions and enhance significant cassava plant disease-related features for efficient cassava disease detection. Our proposed method achieved accuracies of 98.95%, 97.03%, and 98.25% on Cassava Image Dataset, Cassava Plant Disease Merged (2019-2020) Dataset, and the newly created Cassava Plant Composite Dataset, respectively. Furthermore, the proposed technique outperforms previous state-of-the-art methods in terms of accuracy, parameter count, and frames per second values, ultimately making the proposed CDDNet the best one for real-time processing. Our findings underscore the importance of a lightweight and efficient technique for cassava disease detection and classification in a real-time environment. Furthermore, we highlight the impact of modified soft attention on model performance. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Early Detection of Cassava Vascular Bacteriosis (Xanthomonas Axonopodis pv. Manihotis) by Visible Near-infrared Spectroscopy Before the Appearance of Critical Symptoms

Cassava is a crucial crop for food and nutritional security. It is an important source of carbohydrates in African countries. Cassava crops can sometimes be infected by leaf diseases, affecting overall production and reducing farmers' incomes. Early detection is therefore essential to reduce the impact of these diseases. Light reflections from leaves are known to convey information about plant health. In this study, healthy and inoculated cassava were detected from the reflections obtained from the leaves using a USB 4000 spectrometer with a spectral range of (350-1050) nm. Artificial neural networks (ANNs) and nearest neighbours (KNNs) were used with principal components and vegetation indices as input for classification. Various performance metrics, i.e. Precision, Recall, Accuracy and F1_score for KNN, Accuracy, RMSE and R2 for ANN were calculated to evaluate the different established models. Using the principal components (PC1, PC2) we obtained the best models with the ANNs with the following metrics (R2=0.9678; RMSE=0.0146; Accuracy =98.30%) for the variety IM 84 and (R2=0.9291; RMSE=0.0354 Accuracy=91.30%) for the Yacé variety. With vegetation indices, the best performing models were obtained with KNN whose input parameters are RatiodRE_703 ((Accuracy =92.50% and F1-score=0.9449) and fWBI ((Accuracy =90% and F1-score=0.9326) for Yacé and vog 3 (Accuracy=100% and F1-score=1), DD (Accuracy=100% and F1_score=1) and dNIRmin920_980 (Accuracy=95% and F1_score=0.9373) for the IM 84. Overall, the results showed that leaf spectral reflectance can be used successfully for the early detection of cassava bacterial blight.

Selectivity of pre-emergent herbicides in cassava (Manihot esculenta Crantz) and its relationship with the stem cutting planting system

Cassava (Manihot esculenta Crantz, Euphorbiaceae), an important source of food for millions of people in the world, is distributed mainly in Asia, Africa, Latin America, and the Caribbean. Weeds are important biotic constraints on cassava production, and herbicide application can provide effective weed control in this crop. However, the different possibilities of herbicide selectivity (factors associated and not associated with the plants) must be studied before implementation. The aim of this study was to evaluate the effects of the combination of different pre-emergence herbicides and two stem cutting planting systems (vertical and horizontal) on phytotoxicity and several agronomic traits of the cassava crop. The experiment was conducted through a factorial arrangement in a completely random design in Corrientes, Argentina. The factors studied were planting systems (horizontal and vertical position), weed control methods (hoeing or application of diuron, S-metolachlor, pendimethalin or clomazone, 625; 1920; 900 and 1000 g a.i. ha−1, respectively), and cropping seasons (2018–2019 and 2019–2020). The following variables were measured: phytotoxicity, plant height, relative plant stand, total weight of tuberous roots per plant, starch concentration of tuberous roots, and starch production per ha. The highest precipitations occurred in the 2018–2019 cropping season. The vertical planting system in combination with herbicides showed lower phytotoxicity values and higher values of plant height, starch concentration, and starch production per ha than the horizontal planting system. The highest phytotoxicity values were recorded with the application of diuron combined with the horizontal planting system and in the 2018–2019 season, with a 33.33% decrease in relative plant stand compared to the use of hoeing. Starch concentration remained unchanged with the use of clomazone and pendimethalin, whereas the effect of these herbicides on starch production varied with the cropping season, decreasing only in 2019–2020. Starch production was significantly lower with the use of S-metolachlor (up to 55.29% in 2018–2019) and of diuron (up to 60.57% in 2019–2020) than with the use of hoeing. In conclusion, phytotoxicity values were higher for the horizontal planting system than for the vertical system. The herbicide with the highest phytotoxic effect on the cassava crop was diuron; the effect increased when combined with the horizontal planting system in the cropping season with higher rainfall. This work provides the basis for integrated weed management concerning the use of herbicides and their selectivity according to planting systems for cassava crops.

Cassava crop disease prediction and localization using object detection

In agriculture, early detection and localization of plant diseases in time using deep learning techniques can help farmers contain the spread of plant diseases. In this work, we apply object detection models to identify and localize various categories of cassava plant leaf diseases. These include You Only Look Once (YOLO) as well as Generalized Efficient Layer Aggregation Network(GELAN) models. We applied YOLO v9-e, YOLO v9-c, as well as GELAN-e and GELAN-c models. The models were successfully trained using a custom cassava dataset. Several evaluation indicators that include precision, recall and mean average precision(mAP) were analysed result. The results have been compared with an earlier version of YOLO model and show an improvement in evaluation indicators reaching above 80% in the majority of diseases.

Machine Learning Monitoring Model for Fertilization and Irrigation to Support Sustainable Cassava Production: Systematic Literature Review

The manual and time-consuming nature of current agronomic technology monitoring of fertilizer and irrigation requirements, the possibility of overusing fertilizer and water, the size of cassava plantations, and the scarcity of human resources are among its drawbacks. Efforts to increase the yield of cassava plants > 40 tons per ha include monitoring fertilization approach or treatment, as well as water stress or drought using UAVs and deep learning. The novel aspect of this research is the creation of a monitoring model for the irrigation and fertilizer to support sustainable cassava production. This study emphasizes the use of Unnamed Aerial Vehicle (UAV) imagery for evaluating the irrigation and fertilization status of cassava crops. The UAV is processed by building an orthomosaic, labeling, extracting features, and Convolutional Neural Network (CNN) modeling. The outcomes are then analyzed to determine the requirements for air pressure and fertilization. Important new information on the application of UAV technology, multispectral imaging, thermal imaging, among the vegetation indices are the Soil-Adjusted Vegetation Index (SAVI), Leaf Color Index (LCI), Leaf Area Index (LAI), Normalized Difference Water Index (NDWI), Normalized Difference Red Edge Index (NDRE), and Green Normalized Difference Vegetation Index (GNDVI).

Computational models for improving surveillance for the early detection of direct introduction of cassava brown streak disease in Nigeria.

Cassava is a key source of calories for smallholder farmers in sub-Saharan Africa but its role as a food security crop is threatened by the cross-continental spread of cassava brown streak disease (CBSD) that causes high yield losses. In order to mitigate the impact of CBSD, it is important to minimise the delay in first detection of CBSD after introduction to a new country or state so that interventions can be deployed more effectively. Using a computational model that combines simulations of CBSD spread at both the landscape and field scales, we model the effectiveness of different country level survey strategies in Nigeria when CBSD is directly introduced. We find that the main limitation to the rapid CBSD detection in Nigeria, using the current survey strategy, is that an insufficient number of fields are surveyed in newly infected Nigerian states, not the total number of fields surveyed across the country, nor the limitation of only surveying fields near a road. We explored different strategies for geographically selecting fields to survey and found that early and consistent CBSD detection will involve confining candidate survey fields to states where CBSD has not yet been detected and where survey locations are allocated in proportion to the density of cassava crops, detects CBSD sooner, more consistently, and when the epidemic is smaller compared with distributing surveys uniformly across Nigeria.

Analysis of Fluorescently Labeled ISSR Markers to Reveal the Genetic Diversity of Cassava Varieties (Manihot esculenta Crantz) in the Kerala’s Tribal Area of India

The study Inter Simple Sequence Repeat (ISSR) molecular markers to genotype distinct cassava (Manihot esculenta Crantz) cultivars within tribal communities in Kerala, India. Fluorescent ISSR primers were labelled with 6-carboxyfluorescein and used for PCR amplification. The total number of bands produced was 72, of which 49 were found to be polymorphic markers; an average of 17 polymorphic bands was obtained per primer. The manuscript is a scientific validation of the traditional knowledge of tribal people regarding the diversity and wealth of cassava crops in the region, and this validation can therefore help in protecting the farmers right on a particular landrace that they cultivate. The technique used in the diversity analysis is a time-saving process as compared to conventional breeding programs for crop improvement. The data in the manuscript also supports similarity and differences of each variety to one another, which is analysed statistically with the molecular marker-based data generated. By examining genetic diversity at a high resolution, ISSR markers can provide valuable insights into the evolutionary dynamics of these cassava populations. This research contributes to the broader goal of enhancing agricultural sustainability and food security in tribal communities.

Farmers’ perceived rating and usability attributes of agricultural mobile phone apps

Cassava crop is in the forefront among the arable crops mostly cultivated in Nigeria. It is a crop that International Institute of Tropical Agriculture (IITA) have invested more efforts to develop mobile digital solutions for farmers to address some of the agronomic issues threatening its productivity. The ultimate aim of the digital solution is to bring innovations closer to farmers as well as to bring about the transformation needed to achieve food security in Africa. However, farmers’ (users) quality rating and usability of agricultural mobile apps remains uncertain thereby, creating knowledge gap. Feedbacks of users are critical to inform developers of the apps about necessary modifications. This study therefore examined the usability attributes of Agricultural Mobile Phone Applications (AMPAs) among cassava farmers in South-west Nigeria using users-centered approach. Because of the selected crop, apps evaluated in this study were Akilimo App, Airtel 4-21 call App and IITA herbicide calculator App. Akilimo App is an advisory tool that provides site-specific recommendations to cassava farmers in order to increase their cassava-based cropping systems; Airtel 4-2-1 call App provides a voice-based tutorial on cassava production, weather, education, rice amongst others by simply dialing 4-2-1 on any mobile phone with an Airtel sim card; while IITA herbicide is a mobile application developed to prevent herbicide abuse, such as over-dosing and/or under-dosing. Four hundred and ten (410) cassava farmers were recruited as respondents for the study. Data were analyzed using both descriptive and inferential statistics, including frequency counts, percentages, means and standard deviation. As the major contribution, it was shown for the first time, how users (farmers) rated the three Apps in terms of engagement, functionality, aesthetics, information quality, and subjective quality while usability of the Apps were rated for efficiency, effectiveness, satisfaction, learnability, memorability, cognitive load, accuracy and error. Similarly, pattern of usage, benefits of usage and constraints to usage of the Apps were further investigated.

Assessing the Impact of Gas Flaring Activities in Ebedei, Southern Nigeria

The study looked at how gas flaring affects development and sustainable growth. While the availability of natural gas and crude oil is expected to serve as a socioeconomic stimulus for faster, more sustainable growth, the current situation in Nigeria's oil-producing regions is significantly worse than expected. Eleven (11) experimental locations, including Obinomba (control site), which lacks a gas flaring station, provide data for the collections. The air quality indices concentrations and various temperatures were measured. At a starting location that was 50 meters distant from the flare's bund wall, assessments of the location temperature and also air quality in Ebedei were taken at intervals of 50 meters. The statistics indicate that both the temperature and the quantity (content) of gases (CO, NO2, SO4, and CH4) have increased. Thus, a rise in temperature is proportional to a rise in flared gases. It is imperative that no agricultural crops be planted in this area that react adversely to high temperature variation, such as cassava, palm trees, rubber trees, bananas, and other crops. It can be suggested that the extracted gas be liquefied and bottled for usage in home and industrial settings, as well as being heavily utilized by a gas turbine to generate electricity. Residential buildings should be constructed at least 0.5 kilometers away from the flare point, and water samples should be analyzed to determine the level of contamination and water portability. To maintain adherence and keep the blessed environment, it is totally crucial to urge that FEPA continuously track and assess the degree of damages attributed to gas flaring.

Transcriptome analysis reveals potential genes associated with glyphosate resistance in cassava

Glyphosate, widely used to manage weeds in cassava crops, simultaneously inhibits cassava growth, necessitating the development of herbicide-tolerant cassava varieties. In this study, screened 262 cassava varieties, identifying the glyphosate-resistant (GR) variety ZM8701 and the glyphosate-sensitive (GS) variety SC9. Transcriptomic analysis via Illumina sequencing revealed differentially expressed genes associated with resistance, including Cytochrome P450, GST, GT, ABC transporters, and others such as MIOX1, LHCA1, PPH, HSP26, HSP83A, and UGT73C5. Notably, the EMB3004 gene, involved in the biosynthesis of aromatic amino acids, was significantly upregulated in resistant varieties, suggesting a key role in countering glyphosate’s inhibition of the shikimic acid pathway. These genes are pivotal in enhancing cell wall biosynthesis, optimizing photosynthesis, and improving detoxification processes. This research elucidated the molecular mechanisms underlying cassava’s resistance to glyphosate, thereby laying the groundwork for breeding programs aimed at developing herbicide-resistant varieties.Graphical

Diaporthe ueckeri causing cassava root rot in Pernambuco, Brazil

Cassava root rot is a highly destructive disease that causes great damage in Brazil. Identification of the causal agents is essential for the management of this disease. Roots of cassava plants (Manihot esculenta Crantz) with symptoms of root rot were collected from a cassava crop in the municipality of Garanhuns, Pernambuco State, Brazil. This study aimed to identify a Diaporthe species isolated from cassava root rot in Brazil and evaluate pathogenicity in cassava plants and roots. At 7 days after inoculation (DAI), tuberous roots showed necrotic lesions, a soft appearance, and pink color in the center and brown to greenish at the edges, while seedlings showed root rot, wilting, yellowing, drying out, and leaf fall at 66 DAI in the soil. All plants in the control group were asymptomatic. After reisolations and confirmation of Koch's postulates, the causal agent was conclusively identified as Diaporthe ueckeri through the multilocus phylogenetic analyses involving the ITS, TEF1-α, TUB2, CAL, and HIS genes. The results showed that the morphological characteristics, such as colonies with abundant aerial mycelium, formation of pycnidia and alpha conidia, were consistent with those described for species of the genus Diaporthe. This is the first report of D. ueckeri causing cassava root rot in Brazil and worldwide.

Overexpression of cassava melatonin receptor PMTR1 plays dual roles in development under light and dark conditions in Arabidopsis.

MePMTR1 is involved in plant development and production as well as photosynthesis in plant. Melatonin is widely involved in plant growth and development as well as stress responses. Compared with the extending studies of melatonin in stress responses, the direct link between melatonin and plant development in the whole stages remains unclear. With the identification of phytomelatonin receptor PMTR1 in plants, melatonin signalling is becoming much clearer. However, the function of MePMTR1 in tropical crop cassava remains elusive. In this study, we found that overexpression of MePMTR1 showed larger biomass than wild type (WT), including higher number and area of leaves, weight, and accompanying with higher photosynthetic efficiency. Consistently, exogenous melatonin accelerated photosynthetic rate in Arabidopsis. In addition, MePMTR1-overexpressed plants exhibited more resistance to dark-induced senescence compared with WT, demonstrated by higher chlorophyll, lower hydrogen peroxide and superoxide content. In summary, this study illustrated that melatonin and its receptor regulate growth, development and senescence in plants, highlighting the potential application of melatonin and its receptor in improving crop yield and photosynthesis.

Diversity, Prevalence and Virulence of Colletotrichum Species Causing Anthracnose on Cassava Leaves in the Northern Region of Brazil.

Cassava (Manihot esculenta Crantz) is a staple crop widely cultivated by small farmers in tropical countries. However, despite the low level of technology required for its management, it can be affected by several diseases, with anthracnose as the main threat. There is little information about the main species of Colletotrichum that infect cassava in Brazil. Thus, the objective of this work was to study the diversity, prevalence and virulence of Colletotrichum species that cause anthracnose in cassava leaves in northern Brazil. Twenty municipalities of the Pará and Tocantins states were selected, and leaves with symptoms were collected in those locations. Pure cultures were isolated in the laboratory. Species were identified using phylogenetic analyses of multiple loci, and their pathogenicity, aggressivity and virulence levels were assessed. Our results showed the greatest diversity of Colletotrichum associated with anthracnose in cassava plants of the "Formosa" cultivar in the Tocantins and Pará states. We determined the presence of Colletotrichum chrysophilum, C. truncatum, C. siamense, C. fructicola, C. plurivorum, C. musicola and C. karsti, with C. chrysophilum as the most aggressive and virulent. Our findings provide accurate identifications of species of Colletotrichum causing anthracnose in cassava crops, which are of great relevance for cassava breeding programs (e.g., the search for genotypes with polygenic resistance since the pathogen is so diverse) and for developing anthracnose management strategies that can work efficiently against species complexes of Colletotrichum.

PRESENCIA DE DOS ESPECIES DE ÁCAROS (Prostigmata:Tetranychidae: Mononychellus) DE LA YUCA (Manihot esculenta Crantz), PROVINCIA DE COCLÉ, PANAMÁ

<p><strong>Background.</strong> Phytophagous mites of the Tetranychidae family (Prostigmata) have the potential to cause losses to the national production of cassava (<em>Manihot esculenta</em> Crantz), one of the important crops for food security in Panama. This is due to the high reproduction rate they have in short periods of time and the ease of dispersing in certain regions. <strong>Objetive.</strong> Report the presence of two species of phytophagous mites of the genus <em>Mononychellus </em>associated with cassava in the province of Coclé, Panama. <strong>Methodology. </strong>The information corresponds to a sampling of phytophagous mites associated with cassava plantations in seven locations in the province of Coclé. The study was carried out during the period from August 2023 to September 2023. In each location, five yucca plants were selected to verify the presence and damage to the foliage of phytophagous mites. For this, samples of four leaves from each plant were taken. The sampled plant material was taken to the Plant Protection Laboratory of the Divisa Agricultural Innovation Center of the Panamanian Institute of Agricultural Innovation. The samples of phytophagous mites were separated, and microslides were made to identify the species under a microscope. <strong>Results. </strong>Two species of the genus <em>Mononychellus</em> of the family Tetranychidae were identified as associated with damage to cassava plants. <strong>Implications</strong>: The identification of the phytophagous mite species and the damage caused in cassava is the first step to establish an integrated pest management program<strong>.</strong> <strong>Conclusions. </strong>The damages presented by the plants that are affected by the attack of the <em>Mononychellus </em>phytophagous mite complex in the cassava crop were identified.</p>

Development of portfolio management tools in crop breeding programs: a case study of cassava in sub-Saharan Africa

The response to the diverse needs along the cassava value chain, the urge to increase genetic gain, and the need for rapid varietal turnover will necessitate not only technological innovations but also transformation of public breeding programs in sub-Saharan Africa (SSA). We developed guiding, flexible and adaptative tools for portfolio management of cassava breeding. The cassava breeding and product development pipeline process was mapped to illustrate activities of each stage, as well as to clarify key decision points. Stakeholders involved at all stages of breeding were identified. This allowed for identification of gaps and new crucial functions. To clarify accountability and reduce complexity in the decision-making at key decision points, the roles were mapped against decision-rights at each stage-gate. Cassava crop calendars for the different regions in SSA were developed to facilitate better planning. A product advancement template was developed to guide product advancement. The tools that have been developed and stage-gate mapping, will support regional efforts to establish more structured, transparent, participatory, efficient, inclusive, and demand-driven cassava breeding in the region. These approaches could be customized to other commodities.

CRISPR/Cas9-generated mutations in a sugar transporter gene reduce cassava susceptibility to bacterial blight.

Bacteria from the genus Xanthomonas are prolific phytopathogens that elicit disease in over 400 plant species. Xanthomonads carry a repertoire of specialized proteins called transcription activator-like (TAL) effectors that promote disease and pathogen virulence by inducing the expression of host susceptibility (S) genes. Xanthomonas phaseoli pv. manihotis (Xpm) causes bacterial blight on the staple food crop cassava (Manihot esculenta Crantz). The Xpm effector TAL20 induces ectopic expression of the S gene Manihot esculenta Sugars Will Eventually be Exported Transporter 10a (MeSWEET10a), which encodes a sugar transporter that contributes to cassava bacterial blight (CBB) susceptibility. We used CRISPR/Cas9 to generate multiple cassava lines with edits to the MeSWEET10a TAL20 effector binding site and/or coding sequence. In several of the regenerated lines, MeSWEET10a expression was no longer induced by Xpm, and in these cases, we observed reduced CBB disease symptoms post Xpm infection. Because MeSWEET10a is expressed in cassava flowers, we further characterized the reproductive capability of the MeSWEET10a promoter and coding sequence mutants. Lines were crossed to themselves and to wild-type plants. The results indicated that expression of MeSWEET10a in female, but not male, flowers is critical to produce viable F1 seed. In the case of promoter mutations that left the coding sequence intact, viable F1 progeny were recovered. Taken together, these results demonstrate that blocking MeSWEET10a induction is a viable strategy for decreasing cassava susceptibility to CBB and that ideal lines will contain promoter mutations that block TAL effector binding while leaving endogenous expression of MeSWEET10a unaltered.

Participatory research processes for the production of plant material in food security context

The production of quality seed constitutes one of the main challenges for food security and sovereignty of both urban and rural populations, requiring processes that recognize not only the potential of the territories but also the diversity associated withpeasant communities and their forms of production. , so as to reduce the gaps resulting from the use of seeds of low or no physical, genetic, physiological and sanitary quality that reduce the impact on the yields of banana, pineapple and cassava crops. To this end, a participatory research process was carried out to meet the demand for projects that improve the food and nutritional security of the population of the department of Casanare -Colombia. As a result, the methodology was implemented based on meetings with producers of productive systems for the construction of knowledge from social cartography, the preparation of economic calendars and mappings of actors and needs. This reading of the environments allowed the development of activities for the participatory selection of planting materials, processes of intensive multiplication of materials, as well as the transformation and production of banana, pineapple and cassava derivatives. The conclusions have to do with the importance of considering the producer as an active participant in the research processes in the construction of knowledge that contributes to the generation and appropriation of solutions based on science, technology and innovation in favor of food security and with this the reduction of poverty. In the near future, it is planned to carry out a training process for trainers with allied universities to leave installed capacities and to promote access and availability of quality seed.

Cassava Brown Streak Disease Prevalence in Smallholder Cassava Cropping Systems in Northern Uganda: The Case of Acholi Sub-region

Cassava brown streak disease (CBSD) is a devastating disease of cassava in Uganda. Limited information exists on the incidence and severity of CBSD in Northern Uganda. The prevalence of CBSD in the eight (8) districts in the Acholi sub-region is also unknown. Therefore, the current study intended to: a) determine the prevalence and severity of CBSD in the Acholi sub-region, and b) identify the drivers of CBSD epidemics in smallholder cassava cropping systems in Acholi. An assessment of 120 cassava fields was conducted in the 2018b season. CBSD field incidence was highest in Nwoya District (51.3%) and lowest in Kitgum (6.4%), with severity ranging from 2.1 to 3.4 in the sub-region. CBSD prevalence was also highest in Nwoya (76.2%) and lowest in Kitgum and Pader Districts (30.8%). The use of CBSD-susceptible varieties (TME 14, TME 204, and NASE 12) was identified as the main driver of the epidemic. The result of the current study highlights the need for a wide-scale CBSD awareness creation and community-based cassava seed multiplication and distribution system in the Acholi sub-region to promote the up-take of CBSD-tolerant cassava varieties