Good farm practices and improved processing technology of enset for sustainable hunger solution in Ethiopia

Kudama, Gezahagn; Tolera, Tadesse; Gebeyehu, Lemane

doi:10.1186/s13731-022-00210-x

“…From those factors, a disease that is caused by bacteria, fungi, viruses, and nematodes is the most severe biological problem. Among these, bacterial wilt of enset is the most determinant constraint on enset production (Kudama, Tolera, and Gebeyehu, 2022). Bacterial wilt of enset, caused by Xanthomonas campestris PV.…”

Section: Introductionmentioning

confidence: 99%

Batch size impact on enset leaf disease detection

Asfaw

2024

The Scientific Temper

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Enset, also known as the “false banana,” is a staple food in southern and southwestern Ethiopia that could potentially alleviate poverty among smallholders. Recently, a bacterial wilt disease that damages enset leaves has resulted in massive economic losses for farmers. The use of deep learning for automated plant leaf disease diagnosis in crops has grown in popularity in recent years; however, the impact of hyperparameter selection, particularly batch size, on model performance in the context of enset leaf disease detection remains unidentified. In this research, we looked at how batch size affects the effectiveness of a deep learning model to detect enset leaf disease. The study investigated how different batch size settings affected model performance during the detection of enset leaf disease. To confirm this, five commonly used batch sizes [16, 32, 64, 128, and 256] were combined in the proposed experiments. For the study, we have collected a total of 2132 infected and healthy leaves of enset from the south-west area of Ethiopia. Before training the convolutional neural network (CNN) model, the images in the dataset are preprocessed to enhance feature extraction and consistency. Based on the results of the experiments, we determined that the model’s efficiency was even better, but only when the batch size employed in the model was less than the size of the test dataset. The study uses deep learning to detect bacterial wilt in enset leaves and provides academics and practitioners with heuristic information to help boost enset production when CNN is used in agriculture

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“…But the development policy attention given to the commodity is weak that limits its optimal use. The listed constraints posing Enset cultivation to be underutilized and confined to the southwest part of the country were cultural perceptions, politics, historical reasons, and less research and policy support (Gezahagn et al, 2022). The table above illustrates that root and tuber crops are the cheapest source of energy for the farming community and needs policy support for further development and utilization.…”

Section: Introductionmentioning

confidence: 99%

Impact of level of Enset (Ensete ventricosum, Musaceae) Production on Food and Nutrition Security: Empirical Evidences from Wolaita and Kembata Tambaro Zones of Southern Ethiopia

Bassa,

Ketema,

Kuma

et al. 2024

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Enset is the only crop that can define food and nutrition security literally. Enset crop is closely related to food availability, access, use, stability, and nutrient balancing of densely populated communities in Wolaita and Kembata Tembaro zones. The climate smart, adaptive, productive, economical, and socially important Enset crop is the optimal way for ensuring food and nutrition security of communities. Hence, this study aims to estimate the causal effect of the level of Enset Production on farmers’ food and nutritional security in Southern Ethiopia. The survey applied structured and semi structured questionnaires for the collection of cross-sectional data from 374 sampled households in Wolaita and Kembata Tambaro Zones. Generalized Propensity Score (GPS) with multilevel treatment option was applied to deal with the impact evaluation of Production on food and nutrition security. Food and nutrition status of farming communities defined by calorie intake of households. The proxy measure of the level of Enset production was the number of Enset harvested across households in the last twelve months. The GPS method applied followed three estimation procedures such as modelling the conditional distribution of the treatment given the covariates, estimating the conditional expectation of the outcome given the treatment and GPS, and defining the dose response function. The results show that the small holder farmers that actively involved in harvesting Enset for food are significantly associated with increased level of daily energy intake. The implication of the study revealed that through the promotion level of Enset production, it is possible to have increased and balanced the energy intake of households in Southern Ethiopia. The empirical evidences illustrate that higher level of Enset harvesting is an optimal way for sustainable and better level of food and nutritious security for farming communities in southern Ethiopia.

show abstract

Impact of level of Enset (Ensete ventricosum, Musaceae) Production on Food and Nutrition Security: Empirical Evidences from Wolaita and Kembata Tambaro Zones of Southern Ethiopia

Bassa,

Ketema,

Kuma

et al. 2024

Preprint

0

View full text Add to dashboard Cite

Enset is the only crop that can define food and nutrition security literally. Enset crop is closely related to food availability, access, use, stability, and nutrient balancing of densely populated communities in Wolaita and Kembata Tembaro zones. The climate smart, adaptive, productive, economical, and socially important Enset crop is the optimal way for ensuring food and nutrition security of communities. Hence, this study aims to estimate the causal effect of the level of Enset Production on farmers’ food and nutritional security in Southern Ethiopia. The survey applied structured and semi structured questionnaires for the collection of cross-sectional data from 374 sampled households in Wolaita and Kembata Tambaro Zones. Generalized Propensity Score (GPS) with multilevel treatment option was applied to deal with the impact evaluation of Production on food and nutrition security. Food and nutrition status of farming communities defined by calorie intake of households. The proxy measure of the level of Enset production was the number of Enset harvested across households in the last twelve months. The GPS method applied followed three estimation procedures such as modelling the conditional distribution of the treatment given the covariates, estimating the conditional expectation of the outcome given the treatment and GPS, and defining the dose response function. The results show that the small holder farmers that actively involved in harvesting Enset for food are significantly associated with increased level of daily energy intake. The implication of the study revealed that through the promotion level of Enset production, it is possible to have increased and balanced the energy intake of households in Southern Ethiopia. The empirical evidences illustrate that higher level of Enset harvesting is an optimal way for sustainable and better level of food and nutritious security for farming communities in southern Ethiopia.

show abstract

Good farm practices and improved processing technology of enset for sustainable hunger solution in Ethiopia

Cited by 4 publications

References 41 publications

Batch size impact on enset leaf disease detection

Batch size impact on enset leaf disease detection

Impact of level of Enset (Ensete ventricosum, Musaceae) Production on Food and Nutrition Security: Empirical Evidences from Wolaita and Kembata Tambaro Zones of Southern Ethiopia

Impact of level of Enset (Ensete ventricosum, Musaceae) Production on Food and Nutrition Security: Empirical Evidences from Wolaita and Kembata Tambaro Zones of Southern Ethiopia

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