Cassava Production Research Articles

Proteomic analysis reveals dynamic expression related to malondialdehyde in cassava in response to cassava bacterial blight

Cassava bacterial blight (CBB) significantly affects cassava production in Thailand. Understanding tolerant cultivar responses can reveal key disease resistance mechanisms. This study identified differentially abundant proteins between the tolerant ‘Rayong72’ (R72) and susceptible ‘Hanatee’ (HN) cassava cultivars, with quantitative PCR validating mRNA-level changes. Several upregulated proteins in the R72 cultivar were linked to disease progression and defense mechanisms. Correlations between phenotypic symptoms, including malondialdehyde (MDA) levels and protein expression trends, were observed. A higher MDA level, associated with cell damage, correlated with severe symptoms in the HN at the infection site. However, in R72, despite higher MDA levels in leaves compared to HN, oxidative stress-related proteins were also upregulated. Notably, proteins involved in NAD/NADP biosynthesis (QNS), glutathione-based redox regulation (GSS), and MAPK signaling (MAPKKK18) were enriched in the tolerant cultivar, suggesting distinct reactive oxygen species (ROS) regulation and contributing to differential resistance. Taken together, these findings highlight the role of MDA and coenzyme-related proteins in cassava’s defense responses to bacterial infections, emphasizing their importance in stress regulation. This study provides molecular insights into cassava-CBB interactions and underscores the potential of proteomic analysis in advancing plant disease resistance research as well as aiding breeding programs.

Behavioural and physiological responses of whitefly, Bemisia tabaci, to virus infection in cassava (Manihot esculenta)

Abstract Mosaic disease, caused by Cassava mosaic virus and transmitted by cassava whitefly, Bemisia tabaci (Gennadius; Hemiptera: Aleyrodidae), is the main threat to cassava production. Various genotypes with various degrees of resistance were employed to study the interactions between the whitefly and virus. These interactions included dispersal, feeding, fecundity, adult longevity and the life cycle. Virus acquisition in whiteflies altered their dispersal and settling behaviour. For the non‐viruliferous whiteflies that fed on resistant cassava genotypes, the speed of movement between leaves was higher compared to the viruliferous ones that fed on susceptible genotypes. Viruliferous whiteflies on susceptible genotypes fed more efficiently compared to non‐viruliferous ones on resistant genotypes, but fecundity was lowest in viruliferous whiteflies on resistant genotypes. The presence of virus in the system reduced adult longevity but extended the total life cycle. This study provides insights into how the virus modulates the behaviour and physiology/biology of the vector for enhanced transmissibility.

Curah Hujan Terhadap Produktivitas Padi Dan Ubi Kayu: Analisis Statistik Di Kabupaten Serdang Bedagai

Rainfall is one of the climatic factors that influences the productivity of food crops. This study aims to analyze the relationship between rainfall and the productivity of rice and cassava in Serdang Bedagai Regency. The data used are annual secondary data for the period 2013–2024, consisting of rainfall records and the productivity of rice and cassava commodities. The relationship was analyzed using Pearson correlation and simple linear regression methods. The results show that rainfall has a positive and significant relationship with rice productivity, with a correlation coefficient of 0.70 and an R² value of 0.489, indicating that nearly 49% of the variation in rice productivity can be explained by rainfall. Meanwhile, the relationship between rainfall and cassava productivity is positive but not statistically significant (r = 0.60; R² = 0.37; p 0.05), indicating a weaker influence. The effect of rainfall is more evident on rice productivity compared to cassava. These findings highlight the need for improved water management and climate adaptation strategies, particularly in the rice farming systems of Serdang Bedagai Regency.

Optimizing resource utilization and productivity in cassava farming: A case study of Ogun State, Nigeria

This study aimed to improve resource utilization and productivity among cassava farmers in Ogun State, Nigeria. Using a multi-stage sampling technique, 90 cassava farmers were selected from diverse agricultural zones in Ogun State, chosen for its significant cassava production and varied agroecological conditions to ensure a representative sample. Data collection involved structured questionnaires to gather socio-economic characteristics, farming practices, input usage, challenges, and productivity outcomes related to cassava cultivation. Descriptive statistics analyzed farmers’ profiles, including age, education, farm size, and resource access. Inferential statistics like linear regression and probit models examined relationships between these factors and cassava output. Results highlighted farm size, labor input, and access to planting materials as positively influencing cassava yield, whereas fertilizer use showed a negative impact, suggesting inefficiencies in its application. Key challenges identified include limited financial services, inadequate farming resources, and technical knowledge gaps, hindering optimal input utilization and productivity. Recommendations include initiatives to improve access to agricultural credit, expand extension services, and implement educational programs aimed at promoting modern farming techniques. By adopting these measures, policymakers and stakeholders can support the adoption of sustainable agricultural practices, thereby fostering increased cassava yields and overall agricultural development in the region.

Analysis of MSMEs' Cassava Production Efficiency Using a Comparison of Machine Learning Models in Jember Regency

Cassava is one of Indonesia's agro-industrial commodities, but many Micro, Small, and Medium Enterprises (MSMEs) in the cassava processing industry face difficulties in achieving optimal production efficiency. This study aims to evaluate the efficiency of cassava processing production systems in MSMEs in Jember by comparing machine learning algorithms (Linear Regression, Random Forest, Support Vector Regression (SVR), and XGBoost) to predict output and key efficiency factors. The data used consists of 250 data points: 80% for model training and 20% for testing to build a machine learning-based prediction model, with input features production processing as the X-axis, and output in the form of production volume as the Y-axis. Data preprocessing, exploratory data analysis, and modeling were conducted using Python, with evaluation based on MAE, RMSE, and R² metrics. Among the tested models, Random Forest demonstrated the best performance with an R² value of 0.990. Sensitivity analysis revealed that production output increases significantly with the addition of labor and machines, with an optimal configuration of 15–20 workers and 2–3 machines per batch. The study concludes that focusing on overall production efficiency rather than merely increasing resources is the most effective strategy.

Genetic mapping and validation of QTL for whitefly resistance in cassava (Manihot esculenta Crantz)

Key messageQTL associated with whitefly resistance were identified in a cassava F2 population and KASP markers applicable in selection for the trait were validated.Whitefly species pose a major threat to cassava production in tropical regions causing direct plant damage and transmitting viruses that lead to devastating cassava diseases. Aleurotrachelus socialis whitefly is one of the pests that affect cassava in South America. Developing resistant cassava varieties is the most sustainable control strategy for managing whiteflies. This study aimed to map the quantitative trait loci (QTL) associated with resistance to A. socialis and develop molecular markers to facilitate marker-assisted selection. An F2 cassava population (N = 183) was generated by selfing a highly resistant F1 derived from a cross between ECU72 (resistant) and COL2246 (susceptible) landraces. Phenotyping was performed using an efficient glasshouse screening method and high throughput image analysis of infested leaves (Nymphstar). We identified QTL on chromosomes 1, 2, 5, 6, 8, 9, and 14, with a stable and highly significant QTL on chromosome 8 (MeF2WFly8.1), explaining 35.44% of the phenotypic variation. To enable efficient selection, high-throughput KASP markers were developed and validated across diverse genetic backgrounds. Three SNPs displayed the highest association with whitefly resistance, with Chr08_6483145 as the most effective marker for selection in diverse backgrounds. These markers are provided for improving the efficiency of whitefly resistance breeding in the global cassava community.

Building Climate Resilience Using Improved Cassava Planting Materials Among Stallholder Cassava Producers in Cameroon

Climate change represents one of the most pressing challenges of the 21st century, disproportionately affecting rural communities reliant on agriculture for their livelihoods. To address the urgency of climate change in SSA, the technologies used must be accessible and easy to adopt. This study, based on a survey of 1,233 cassava producers in Cameroon, analyzes the effect of adopting improved cassava planting material (ICPM) on climate resilience. The econometric approach employed is a recursive bivariate probit model, which allows for the estimation of marginal effects and treatment effects. The results reveal a positive effect of ICPM adoption on resilience to drought and flood shocks. To be precise, it emerges that the probability of farmers in the sample being affected by floods decreased by an average of 30% due to ICPM adoption in anticipation of drought. The probability of farmers who adopted ICPM being affected by floods decreased by an average of over 35% due to their adoption of ICPM in anticipation of drought. The probability of farmers in the sample being affected by drought decreased by nearly 15% due to ICPM adoption in anticipation of floods. The probability of farmers who adopted ICPM being affected by drought decreased by an average of over 10% due to their adoption of ICPM in anticipation of floods. Access to electricity and the producer's experience in agriculture are identified as the main factors influencing ICPM adoption. Consequently, several recommendations are made to improve the adoption of quality seeds and mitigate the impacts of climate change-related shocks.

Cassava Root Rot in Côte d'Ivoire: Farmer Perceptions, Indigenous Control Methods, and Production Typologies

This study aims to understand cassava producers' perceptions of the disease and to identify the endogenous control methods used by producers. Cassava is a crop of great socio-economic importance in Côte d'Ivoire. However, this crop faces major constraints, particularly tuber rot. The search for sustainable control methods requires an in-depth understanding of the factors responsible and producers' perceptions of this problem. The study is based on a survey conducted in 13 cassava-growing localities, including Aboisso, Abengourou, Adzopé, Agboville, Bouaké, Dabou, Toumodi, Yamoussoukro, Daloa, San Pédro, Man, Katiola and Ferkessédougoud in the main cassava-growing areas throughout Côte d'Ivoire. The questionnaire developed took into account the typology of producers. Questionnaires were submitted to 285 cassava growers. Cultivation practices were assessed during the survey by field observation in 320 plots with a view to describing the cultivation practices employed, their level of knowledge of the disease and endogenous control methods. The results showed that cassava is grown throughout Côte d'Ivoire, with a high proportion of women among producers. This crop is a very important source of income. From an organisational point of view, most producers are not grouped into cooperatives, have a very low level of education and do not receive any support. In terms of farming practices, the results showed that the cuttings used are mostly of variable quality and are not disinfected. Rot is widespread in the plots and the symptoms of the disease are well known to growers. There are no effective control methods. Supervising producers would be an effective and sustainable way of combating tuber rot and would help guarantee cassava production.

Enhancing Farmers’ Capacity for Sustainable Management of Cassava Mosaic Disease in Côte d’Ivoire

Cassava Mosaic Disease (CMD) is a major constraint to cassava production in Côte d’Ivoire, causing significant yield and income losses for smallholder farmers. Despite its high prevalence, farmers’ knowledge and understanding of the disease remain limited. To address this issue, the Central and West African Virus Epidemiology (WAVE) Regional Center of Excellence provided capacity building for farmers in the major cassava growing regions. This study assesses the impact of the WAVE’s trainings and awareness campaigns on farmers’ knowledge of the disease and the management methods they adopted. Mixed socio-agronomic data were collected from 290 farmers, and CMD epidemiological parameters were assessed in 82 farms. Data were analysed using propensity score matching (PSM), followed by a Tobit regression model to assess the determinants and intensity of adoption of CMD management practices, using Stata. The results showed that trained farmers had a better understanding of CMD compared to untrained farmers. On average, trained farmers adopted 2.36 disease management practices (DMPs) compared to 1.55 DMPs for untrained farmers. Participation in WAVE’s training sessions and a sound knowledge of CMD positively influenced both the adoption and intensity of adoption of DMPs. However, there was no significant difference in CMD incidence between beneficiary areas (54.55%) and non-beneficiary areas (54.95%), likely due to the unavailability of disease-free planting material, inadequate agricultural practices, and high populations of whiteflies (Bemisia tabaci). This study shows the importance of awareness campaigns in the sustainable management of crop diseases in general and CMD in particular and suggests the need to train farmers on disease management and provide them with healthy planting materials.

Detection of Cassava Mosaic Disease and Assessment of Selected Agronomic Traits of Cassava (Manihot esculenta)

A study was conducted in Sierra Leone to identify cassava plants that are asymptomatic and symptomatic to cassava mosaic disease (CMD) and collect planting materials for field trial establishment; determine the prevalence of CMD caused by African cassava mosaic virus (ACMV) and East African cassava mosaic virus (EACMV) using the Nuru App and virus indexing techniques; and assess selected agronomic traits in cassava. A total of 80 cassava farms spanning four provinces (Southern, Eastern, Northern, and North-West) were surveyed in April 2022. Findings showed that the cassava variants of the experiment and locations significantly (p < 0.001) affected CMD incidence, severity, growth, and fresh storage root yield traits. The CMD incidence (87.0%) and whitefly abundance (144.8) were highest, and the CMD severity was moderate (4.0) for the plants derived from cuttings obtained from symptomatic Cocoa mother plants, while plants derived from cuttings of improved mother plants exhibited no visible symptoms of the disease and the lowest population (45.1) of whiteflies. The Nuru app is inefficient for phenotypically detecting CMD at 3 months after planting (MAP), while at 6, 9 and 12 MAP, the app efficiently detected the disease using a molecular analysis technique. Resistant, non-diseased plants derived from cuttings obtained from SLICASS 4 mother plants produced the highest fresh storage root yield (54.9 t ha−1). The highest storage root yield loss was recorded in the plants obtained from cuttings of symptomatic variety Cocoa mother plants harvested at Matotoka grassland ecology, Bombali District (90.2%), while those harvested from cuttings of asymptomatic variety Cocoa mother plants grown at the four test environments had a similar storage root yield loss ranging from 40.3 to 46.2%. Findings suggest the importance of genetic variability, environmental adaptation, utilization of diseased-free materials, and phytosanitation as disease management strategies for increased production. These findings provide important insights into the distribution, impact, and spread of CMD and whitefly abundance in the studied areas in Sierra Leone that could be exploited for cassava production, productivity, conservation, and population improvement.

Effect of planting distances on yield and quality of cassava cultivars and production of pasta from mixture of cassava flour and soft wheat flour.

Effect of planting distances on yield and quality of cassava cultivars and production of pasta from mixture of cassava flour and soft wheat flour.

Crescimento e desempenho produtivo da mandioca em diferentes épocas de plantio no Agreste de Alagoas, Nordeste do Brasil

ABSTRACT The aim of this study was to evaluate the influence of different planting times and meteorological variables on the productive performance of industrial cassava in the Agreste region of Alagoas state, Brazil. The treatments were five planting dates, 25 days apart: D1 - April 10, D2 - May 5, D3 - May 30, D4 - June 24 and D5 - July 19. The experiment was conducted from April 2021 to September 2023 (two cultivation cycles), using randomized blocks, with four replicates. The variables analyzed were agrometeorological data, crop growth and yield. In the Agreste region of Alagoas, the average daily ET0 varies from 2.9 to 4.7 mm between the rainy and dry seasons, respectively. The average temperature of 24.3 °C meets the thermal demands of cassava cultivation. Although annual rainfall is sufficient to guarantee cassava production, it is seasonal, with a dry period from spring to summer, which compromises subsequent plantings. In the Agreste region of Alagoas, the best time to plant cassava is from April 10 to May 5, which is the beginning of the rainy season and ensures better vegetative canopy height (3.2 m), stem diameter (2.8 cm), leaf area index (3.0), maximum root length (43.1 cm), number (6.6) and yield (72.8 t ha-1), total biomass (145 t ha-1) and starch content (34.3%).

Agronomic and Social Effects of 2022 Flooding on Cassava Production in Delta State, Nigeria

This study investigated the agronomic and social effects of flooding in 2022 on cassava production in Delta State, Nigeria. A descriptive survey research design was used and data collected from 250 cassava farmers in six flood-risk Local Government Areas through structured questionnaires. The research showed major agronomic impacts such as issues with planting stems as cuttings (mean = 2.6), transportation delays (mean = 2.6) and higher occurrences of cassava diseases (mean = 2.9). Research showed social well-being sustained major impacts as participants rated mobility troubles (mean=3.3) as well as psychological trauma (mean=3.0) and interrupted social activities (mean=3.0) as most detrimental. There was no significant difference (t = 1.879, p = 0.063) between agronomic and social effects indicated by a t-test, reflecting their symbiotic relationship. The study recommends joint flood mitigation strategies with agricultural support and psychosocial interventions to enhance farmers' resilience.

Measuring the Effect of Climate Change and Productivity Factors on Cassava Production in Nigeria

Agriculture is one of the sectors that are greatly affected by climate. A change in climate would in no small measure impact on agriculture, location notwithstanding. This study examined the effect of climate change and productivity factors on cassava yields in Nigeria. Data were obtained from World Bank’s World Development Indicator (WDI), Food and Agricultural Organisation (FAO) and IMF. ARDL method of data analysis was used to analyse the data. The Results showed that TEMP, Rf, LF, CS and AF are statistically significant at 5% and has positive effects on cassava yield. The paper concluded that cassava significantly depended on temperature, rainfall, labour force, capital stock, and availability of fertilizer. Based on the findings, the study recommends the need for national agricultural policy to prioritize cassava as a climate-resilient crop, Policies to support irrigation infrastructure and rainwater harvesting, inclusive financial policies, such as subsidized agricultural loans for smallholder cassava farmers, Establishing agricultural credit guarantee schemes and Encouraging microfinance institutions and cooperatives to offer targeted support for cassava producers, It also recommends for more extension officers in order to spread best practices and improve technical efficiency at the farm level, as well as investments in training programs and mechanization instruments for rural workers. Lastly, further analysis using mixed-methods approach (quantitative econometric modelling with qualitative insights) to better explain how farmers perceive and respond to climate impacts should be carried out.

Determinants of Cassava Production among Smallholder Farmers in Edo State, Nigeria

This study analyzed the determinants of cassava production among smallholder farmers in Edo State, Nigeria. Specifically, it estimated the profitability of cassava production, identified the factors affecting cassava output, and assessed the level of technical efficiency among the farmers. A multistage sampling technique was used to select 160 respondents, and data were collected using well-structured questionnaires. Analytical tools employed include descriptive statistics, the Cobb-Douglas production function, and the stochastic frontier production function. Results showed that 56% of the cassava farmers were male, with an average age of 45 years and an average farm size of 3 hectares. The total variable cost per hectare was ₦174,346.00, while total revenue was ₦990,826.67, yielding a gross margin of ₦816,480.67, a gross margin ratio of 0.82, and a rate of return on investment of 3.68. Cobb-Douglas analysis revealed that cassava cuttings, fertilizer, sex, age, household size, education, farm size and income significantly influenced cassava output (P<0.01). The stochastic frontier estimates also showed that planting material, fertilizer, herbicides, labour, and farm size significantly influenced production efficiency. However, inefficiency was significantly associated with age, sex, marital status, household size, extension contact, and access to credit. The average technical efficiency was 0.762, indicating a 24% efficiency shortfall. Major constraints faced by farmers included limited land access, weak land policies, insufficient finance, pest and disease infestations, and high labor costs. The study recommends the provision of subsidized inputs, access to credit, and greater inclusion of female farmers in cassava production in the study region.

Response of Soil-dwelling Insects and Weed Communities to Fertilizer Management in Cassava Production: A Site Comparison Study in Agusan Del Sur, Philippines

Aims: Intensification of cassava production through improved fertilizer management requires understanding its impacts on agricultural biodiversity. Study Design: A field experiment using a split-plot design with three replications. Place and Duration of the Study: The study was conducted at two sites (Research Station and farmer's field) from April 2021 to March 2022. Methodology: The study compared eleven fertilizer treatments across two cassava varieties (Lakan 1 and Golden Yellow). Soil-inhabiting insects and weed communities were assessed across all treatments. Results: Soil-inhabiting insects showed significantly higher populations in unfertilized control plots compared to fertilized treatments, with predatory ground beetles (Carabidae) dominating both sites. Shannon's diversity indices (1.58-1.62) indicated moderate insect diversity across sites, suggesting simplified but functional communities. Weed assessments revealed distinct community structures between sites, dominated by perennial grasses from the Poaceae family. While fertilizer treatments significantly influenced soil insect abundance, weed community composition was more strongly affected by site-specific conditions, as demonstrated through cluster analysis. Conclusion: The study demonstrates that agricultural intensification through fertilizer application may impact beneficial soil fauna while having limited effect on weed community structure. These findings suggest the need for integrated, site-specific management approaches that balance nutrient application with biodiversity conservation in cassava production systems.

PERTUMBUHAN DAN PRODUKSI TIGA KLON UBI KAYU GENJAH PADA TANAH ULTISOL YANG DIBERI CACAHAN BATANG SINGKONG DI LAHAN RISET PT GGP LAMPUNG TENGAH

Cassava is a plant that is ranked third as a source of food in Indonesia. Apart from that, cassava is also needed in industries such as making tapioca flour. In 2021, cassava production in Lampung will be around 20-25 t/ha, this amount is still below the potential of superior cassava which reaches 35-40 t/ha. Cassava growth and production depend on the variety and land where it is cultivated. This research aims to determine the differences in growth and production of several early maturing cassava clones tested, namely Vamas-1, Vati-1, and UTK on Ultisol soil in the PT GGP research area. This research was carried out on the land of the PT GGP research division, Central Lampung, Lampung. This research was carried out from August 2022 to February 2023. The research method used was a Randomized Block Design (RAK) with one treatment, namely clones. There are 3 clones used, namely Vamas-1, Vati-1, and UTK. The experiment on each clone consisted of 3 replications with 36 plants in each replication, but 5 plants were selected from each replication as samples, so that 45 experimental units were obtained. The observation data was analyzed and then compared with the UJ5 clone data based on the Standard Deviation to determine the early maturation characteristics of the three clones. The results showed that clone treatment had no significant effect on growth and production. The number of fresh sweet potatoes at 24 weeks after planting (WAP) in terms of the quantity of clones Vamas-1, Vati-1, UTK, and UJ5 respectively was 7.3; 6.6; 6.3; and 7.3 fruit/plant with a fresh sweet potato weight of 2316,7; 2183,3; 2150,0; and 1433,3 g/plant. The starch content of Vamas-1, Vati-1, UTK, and UJ5 clones was 26,2%; 25,2%; 25,8%; and 23.2%..Keywords : early, Manihot esculenta, UTK, Vamas-1, Vati-1,

Social – Economic and Management Practices of soil fertility that Affects Cassava production in the Central African Republic: Case Study in Savanna and Forest areas

Purpose: Cassava is an important root crop in maintaining food security for the population in the Republic of Centrafrique (CAR). Despite this socio-economic importance, yields obtained remain low and demands are not yet met. The aim of this study was to identify socio economic and management factors that determine cassava yields in two agroclimatic zones of CAR.Research Method: Socio-demographic characteristics, soil fertility management practices in cassava cropping systems and constraints related to cassava production in the CAR forest and savanna zones were collected using semi-structured interviews. Descriptive statistics, Student’s t test and ordinal logistic regression were used to analyze data collected.Findings: Cassava is the main crop in two agroclimatic zones. It is an activity carried out mainly by men. The areas sown for cassava vary between 0.45 and 0.85 ha. The main varieties grown were TMS 92/0329 (locally named Togo) and C96/OO5 (locally named Bobeketi). Disease resistance, high yield and organoleptic quality are the main criteria used for selecting varieties to grow. Cassava yields obtained for all varieties combined are significantly different (p = 0.0001) in the two zones, with an average of 4.41 t.ha-1 of root. These low yields were related to climatic constraints (violent wind and irregular rainfall) and a decline in soil fertility.Originality/ Value: It is proposed to implement integrated soil fertility management strategies by combining mineral and organic fertilizers available in climatic zones that optimize plants’ nutrient use efficiency in a context of climatic changes for sustainable cassava production.

ANALISIS PERAMALAN AGRIBISNIS PANGAN DI KABUPATEN SIMALUNGUN PROVINSI SUMATERA UTARA

North Sumatra Province is one of the food crop production centers in Indonesia, including Simalungun Regency. Fluctuations in food crop production from year to year experience ups and downs making food production forecasting quite important. This research aims to analyze food production forecasting, namely rice, corn, and cassava in 2023-2033 using the Eviews 13 software application. The research method used is the ARIMA method, then the best ARIMA method is used for forecasting food production in Simalungun Regency in the future. The data used in this research is secondary data from 1996 to 2022 obtained from the Central Bureau of Statistics and the Food Crops and Horticulture Office. The results showed that Simalungun Regency in 2023-2033 experienced an increase in rice and cassava production, while corn experienced a decrease.

Predicting the cassava economy in Lampung province: An ARIMA-based forecast of supply, demand, and price

Cassava productivity in Lampung Province experienced a decline from 2015 to 2019. This indicates that there are problems in cassava farming in Lampung Province. Apart from that, the tapioca industry in Lampung Province does not meet its need for fresh cassava as a raw material to produce around 9 million tons per year, so it can only produce around 7 million tons per year. This affects the price of cassava in Lampung Province. This research aims to predict the supply, demand, and price of cassava in Lampung Province, Indonesia. The utilized data type is secondary data with a time series of 14 years, from 2006 to 2019. The employed analytical technique is the forecasting method utilizing the ARIMA model. The research results obtained were that forecasting the supply of cassava in Lampung Province and forecasting demand for cassava for the gaplek industry and tapioca in Lampung Province experienced a decline in 2020-2025, while forecasting the price of cassava at the farmer level experienced an increase in 2020-2025. The government can anticipate this by investing in education, counseling, and infrastructure related to the cassava commodity, which currently provides very little outreach of counseling. Meanwhile, what the government can anticipate if there is a decline in cassava prices in the future is to increase the performance of cassava farmer groups so that they can sell their harvests collectively, giving farmers a higher bargaining power position in selling their production to industry.