Measuring the impact of climate change on potato production in Bangladesh using Bayesian Hierarchical Spatial-temporal modeling

Salan, Md. Sifat Ar; Sumon, Imran Hossain; Rahman, Md. Mizanur; Kabir, M; Majumder, Ajit Kumar

doi:10.1371/journal.pone.0277933

Cited by 6 publications

(5 citation statements)

References 27 publications

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“…The analysis-of-variance method (ANOVA) was used to carry out the mathematical processing of the data. As previously demonstrated by Salvati et al [83], Kalivas and Kollias [84], Tao et al [85], and Salan et al [86], the ANOVA model produces reliable results for the spatial-temporal analysis of climate change effects on the productivity of crops.…”

Section: Methodological Frameworksupporting

confidence: 56%

Productivity of Winter Wheat Cultivated by Direct Seeding: Measuring the Effect of Hydrothermal Coefficient in the Arid Zone of Central Fore-Caucasus

et al. 2022

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In arid zones, the yields of soft winter wheat varieties are particularly affected by the variations of hydrothermal conditions. This especially applies to direct seeding practices, for which the understanding of the links between hydrothermal parameters of soil and the environment, on one side, and the productivity of winter wheat, on the other, is one of the founding pillars of stable agricultural systems. On the case of the arid zone of Central Fore-Caucasus, this study investigates changes in the duration of interphase periods of plant development, plant density, and yield. It is found that in 2019–2021, positive temperature shifts and drought resulted in an increase in the duration of the growing season of crop varieties, thinned plant density, and reduced productivity of drought-resistant varieties. Evaluation of indices, that determine the ecological and genetic variability of varieties in the “genotype-environment” system resulted in the establishment of models that described the effect of drought on crop yields by type of manifestation and forecrops (sunflower, chickpeas). It is shown that the average linear deviations improved phase techniques and changed the area of winter wheat cultivation. On the back of the further drought propagation, farmers in arid zones could benefit from breeding new varieties and hybrids of grain crop. These measures may increase or stabilize the productivity of winter wheat in arid environments. Specifically, for the arid zone of Central Fore-Caucasus, the study recommends reducing lands under grain crop and shifting the cultivation of winter wheat northward. This will reduce the impact of volatile climatic conditions on winter wheat productivity in the region.

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Section: Methodological Frameworksupporting

confidence: 56%

Productivity of Winter Wheat Cultivated by Direct Seeding: Measuring the Effect of Hydrothermal Coefficient in the Arid Zone of Central Fore-Caucasus

et al. 2022

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“…Economic development particularly in Bangladesh is hugely relied on the advancement of agricultural growth [27]. Researchers pointed out that different crops production in Bangladesh has risen significantly after 2010 [28][29][30][31][32][33][34][35], however, the distribution of natural resources and climate change impacted the sustainable agricultural production [36][37][38][39] that will be a cause of impact on the total reserve in future.…”

Section: Literature Reviewmentioning

confidence: 99%

Relationships between total reserve and financial indicators of Bangladesh: Application of generalized additive model

et al. 2023

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Background The reserve of a country is a reflection of the strength of fulfilling its financial liabilities. However, during the past several years, a regular variation of the total reserve has been observed on a global scale. The reserve of Bangladesh is also influenced by several economic and financial indicators such as total debt, net foreign assets, net domestic credit, inflation GDP deflator, net exports (% of GDP), and imports of goods and services (% of GDP), as well as foreign direct investment, GNI growth, official exchange rate, personal remittances, and so on. Therefore, the authors aimed to identify the nature of the relationship and influence of economic indicators on the total reserve of Bangladesh using a suitable statistical model. Methods and materials To meet the objective of this study, the secondary data set was extracted from the World Bank’s website which is openly accessible over the period 1976 to 2020. Moreover, the model used the appropriate splines to describe the non-linearity. The performance of the model was evaluated by the Akaike information criterion (AIC), Bayesian information criterion (BIC), and adjusted R-square. Results The total reserve of Bangladesh gradually increased since 2001, and it reached its peak in 2020 which was 43172 billion US dollars. The data were first utilized to build a multiple linear regression model as a base model, but it was later found that the model has severe multicollinearity problems, with a maximum value of VIF for GNI of 499.63. Findings revealed that total debt, inflation, import, and export are showing a non-linear relationship with the total reserve in Bangladesh. Therefore, the authors applied the Generalized Additive Model (GAM) model to take advantage of the nonlinear relationship between the reserve and the selected covariates. The overall response, which is linearly tied to the net foreign asset in the GAM model, will change by 14.43 USD for every unit change in the net foreign asset. It is observed that the GAM model performs better than the multiple linear regression. Conclusion A non-linear relationship is observed between the total reserve and different economic indicators of Bangladesh. The authors believed that this study will be beneficial to the government, monetary authorities also to the people of the country to better understand the economy.

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“…The potato (scientifically known as Solanum tuberosum L.) stands as the world's most widely cultivated crop, playing a pivotal role in addressing nutritional requirements as the third-largest contributor to the global food supply [1,2]. While Bangladesh is predominantly associated with rice consumption, it also showcases a substantial cultivation and consumption of potatoes annually, with their popularity steadily on the rise.…”

Section: Introductionmentioning

confidence: 99%

Potato Leaf Disease Detection Using MultiNet: A Deep Neural Network with Multi-Scale Feature Fusion

Islam,

Saha

2024

Preprint

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Potatoes play a significant role in Bangladesh’s agriculture, ranking third after rice and wheat, and contributing substantially to the nation’s economy. However, leaf diseases pose significant challenges to potato growth and quality despite Bangladesh being a major global potato producer. Detecting diseases in a timely manner is essential for enhancing productivity and advancing agricultural digitization. This study aims to utilize machine-learning algorithms on a limited dataset of potato leaf images for disease detection. The research focuses on classifying potato leaves into distinct disease groups using The Plant Village Dataset. A novel framework called “MultiNet” is introduced, which employs transfer learning to effectively categorize various potato leaf diseases. “MultiNet” facilitates rapid and accurate diagnostics through two multi-class classifications: (1) Early Blight, Late Blight, and Healthy (3 classes); and (2) Early Blight Normal, Early Blight Serious, Late Blight, Healthy, Insect infected, LeafRoll Virus infected, and Virus infected (7 classes). The system integrates three pre-trained models—ResNet50, DenseNet-201, and VGG16—to extract features from images, followed by concatenation to create a hybrid structure. The results demonstrate an impressive overall classification accuracy of 99.83% for three classes and 98% for seven classes. These findings underscore the potential impact and usefulness of the “MultiNet” framework in agriculture, suggesting promising applications within the sector.

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Measuring the impact of climate change on potato production in Bangladesh using Bayesian Hierarchical Spatial-temporal modeling

Cited by 6 publications

References 27 publications

Productivity of Winter Wheat Cultivated by Direct Seeding: Measuring the Effect of Hydrothermal Coefficient in the Arid Zone of Central Fore-Caucasus

Productivity of Winter Wheat Cultivated by Direct Seeding: Measuring the Effect of Hydrothermal Coefficient in the Arid Zone of Central Fore-Caucasus

Relationships between total reserve and financial indicators of Bangladesh: Application of generalized additive model

Potato Leaf Disease Detection Using MultiNet: A Deep Neural Network with Multi-Scale Feature Fusion

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