Rice Land Conversion into Plantation Crop and Challenges on Sustainable Land Use System in the East Tanjung Jabung Regency

Daulay, Asnelly Ridha; Intan, K.P. Eka; Barus, Baba; Pramudya, N. Bambang

doi:10.1016/j.sbspro.2016.06.059

Cited by 22 publications

(17 citation statements)

References 7 publications

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“…This proposition is based on a previous study done at the same location where economic returns was identified as one of the reasons farmers have shifted from rice production to brick making [12,17] and to key lime production [32]. This result also corroborates the findings reported by Yusuf et al [37], David [38], Daulay et al [39] and Feintrenie et al [40] that economic returns is an essential reason for farmers or villagers to shift to new crops or livelihoods.…”

Section: Differences In Economic Returnssupporting

confidence: 88%

Comparative Profitability of Melon and Watermelon Production in South Konawe District of Southeast Sulawesi

Saediman

Ode

Rianse

et al. 2020

Wseas Transactions on Business and Economics

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Melon and watermelon are two high-value crops that have been commercially cultivated recently inSoutheast Sulawesi. The objective of the study was to examine and compare the cost and returns of melon andwatermelon production. The study was conducted in Abenggi village in South Konawe district of SoutheastSulawesi. Twenty melon farmers and 20 watermelon farmers were selected as respondents. Data collection wasdone using a questionnaire-based interview method. Data and information were analyzed using cost and returnsanalysis and independent sample t-test. Results of the study revealed that both melon and watermelonproduction were profitable as indicated by their revenue-cost ratio being higher than 1. Due to small size offarming, difference in net returns per farm from melon and watermelon was not statistically significant. Perhectare net returns from melon farming were statistically significantly higher than that of watermelon farming.Net returns from either melon or watermelon farming were higher than that of many other crops in theprovince. Farmers should continue to focus on the cultivation of the crops as they can increase their income andpromote rural economy. The local government should assist the development of the two crops by ensuringavailability of farm inputs and improving provision of weather forecast results to the farmers.

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Section: Differences In Economic Returnssupporting

confidence: 88%

Comparative Profitability of Melon and Watermelon Production in South Konawe District of Southeast Sulawesi

Saediman

Ode

Rianse

et al. 2020

Wseas Transactions on Business and Economics

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show abstract

“…This condition threatens the species in forest and shrubland by reducing the suitable area for species to survive. Other studies have demonstrated that changes in forest and crop area into oil palm plantation is higher in Indonesia, in particular on Sumatra Island [40,41]. The differences between the land use map from 2000 and those of 2050 and 2070 illustrate the high increases in plantation area of more than 4%, while the other classifications show changes of approximately 0%-1.8%.…”

Section: Resultsmentioning

confidence: 85%

Prediction of Land Use and Land Cover Changes for North Sumatra, Indonesia, Using an Artificial-Neural-Network-Based Cellular Automaton

2019

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Land use and land cover (LULC) form a baseline thematic map for monitoring, resource management, and planning activities and facilitate the development of strategies to balance conservation, conflicting uses, and development pressures. In this study, changes in LULC in North Sumatra, Indonesia, are simulated and predicted using an artificial-neural-network-based cellular automaton (ANN-CA) model. Five criteria (altitude, slope, aspect, distance from the road, and soil type) are used as exploratory data in the learning process of the ANN-CA model to determine their impacts on LULC changes between 1990 and 2000; among the criteria, altitude and distance from the road have strong impacts. Comparison between the predicted and the real LULC maps for 2010 illustrates high agreement, with a Kappa index of 0.83 and a percentage of correctness of 87.28%. Then, the ANN-CA model is applied to predict LULC changes in 2050 and 2070. The LULC predictions for 2050 and 2070 demonstrate high increases in plantation area of more than 4%. Meanwhile, forest and crop area are projected to decrease by approximately 1.2% and 1.6%, respectively, by 2050. By 2070, forest and crop areas will decrease by 1.2% and 1.7%, respectively, indicating human influences on LULC changes from forest and cropland to plantations. This study illustrates that the simulation of LULC changes using the ANN-CA model can produce reliable predictions for future LULC.Simulation of LULC changes provides the baseline scenario for use when predicting future scenarios and patterns in future development. Simulation of LULC changes can indicate anthropogenic impact, identify land use problems, such as the degradation and deforestation, and be used in land use planning [2]. Land use changes have been important aspects for regional and urban planning for centuries. Most of the research predicts land use changes using the independent variable with the highest correlation to those changes. Verburg et al. [3] illustrated that the multiscale characteristics of land use systems require new techniques to quantify neighborhood effects. Furthermore, Verburg et al.[3] also explicitly dealt with temporal dynamics and achieved a higher level of integration among disciplinary approaches and between models studying urban and rural land use changes. Multivariate spatial models [4], Markov analysis [5], cellular automata (CA) [3,6-9], neural-network-based CA [2], empirical-statistical models [10,11], optimization models [12], and agent-based models [13,14] have all been used in the simulation of land use change. More details on each method can be found in [15].The CA is a common method for simulating the LULC change spatial evolution by estimating the state of a pixel according to its initial state, surrounding neighborhood effects and transition rules. A CA model can generate rich patterns and effectively represent nonlinear spatially stochastic LULC change processes [16,17]. The applications of CA models have been growing in urban development studies, with strong capabilities for si...

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“…Changes in land-use have been altering ecosystems and livelihoods throughout history. Recent years have witnessed a massive expansion of oil palm monocultures in the tropics of Asia, mainly at the expense of rainforests, agroforests (timber and jungle rubber), and traditional crops such as rubber and rice (Daulay et al, 2016;Drescher et al, 2016;Byerlee et al, 2017). Although large-scale commercial plantations used to dominate this massive expansion, farm households are also adopting intensively managed oil palm monocultures at a high rate (Byerlee and Viswanathan, 2018).…”

Section: Introductionmentioning

confidence: 99%

Oil Palm Boom and Farm Household Diets in the Tropics

Sibhatu

2019

Front. Sustain. Food Syst.

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Farm households in the tropics are rapidly expanding oil palm monocultures, mainly at the expense of rainforests, agroforests, and traditional croplands. Although monetary gains and ecological consequences of such changes in land-use have been extensively documented, little is known about nutritional and dietary impacts on farm households despite those households being the most affected by nutritional problems. Here, this research gap is addressed with a 2-year panel data of farm households from Jambi province in Indonesia, a hot spot of tropical rainforest conversion into oil palm plantation. I use endogenous switching regression to better account for selection bias and obtain counterfactual outcomes. Results show high levels of undernourishment and micronutrient inadequacy in farm households in Jambi. Non-adopters are more likely to be undernourished and micronutrients deficient, consume less diverse foods, and eat low quantities of fruits and vegetables. The counterfactual analysis shows that oil palm adoption leads to significantly greater household dietary diversity, higher calorie consumption, more fruit and vegetable consumption, and higher food expenditure in farm households. These positive dietary impacts are observed irrespective of whether households belong to transmigrant or local communities. Panel regression results further show that oil palm cultivation reduces the prevalence of undernourishment and, at the same time, increases the mean probability of adequacy of consumed fruits and vegetables and micronutrients. This impact, leading to better diets, however, is complex and not straightforward; several socioeconomic, demographic, and farm factors have different dietary impacts for adopters and non-adopters. The findings highlight important policy implications: farm households adopt and expand land-uses that provide greater dietary benefits. Thus, policy-makers interested in maintaining the tropical rainforests, regulating oil palm plantations, and tackling nutritional deficiencies in the rural tropics should not overlook these dietary benefits for farm households.

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Rice Land Conversion into Plantation Crop and Challenges on Sustainable Land Use System in the East Tanjung Jabung Regency

Cited by 22 publications

References 7 publications

Comparative Profitability of Melon and Watermelon Production in South Konawe District of Southeast Sulawesi

Comparative Profitability of Melon and Watermelon Production in South Konawe District of Southeast Sulawesi

Prediction of Land Use and Land Cover Changes for North Sumatra, Indonesia, Using an Artificial-Neural-Network-Based Cellular Automaton

Oil Palm Boom and Farm Household Diets in the Tropics

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