Sugarcane and Coffee in the Extreme Southern Region of Bahia, Brazil: A Spatio-Temporal Analysis and Socioeconomic Factors

Almeida, Regiane de Oliveira; Cruz, Thyane Viana da; Crepaldi, Maria Otávia; Silva, Leonardo Thompson da; Sousa, Ana Cristina de; Cerqueira, Everton Mateus dos Santos; Sena, Anderson

doi:10.14393/SN-v35-2023-66851x

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Papers • Soc. nat. 35 • 2023 • https://doi.org/10.14393/SN-v35-2023-66851x copy

Sugarcane and Coffee in the Extreme Southern Region of Bahia, Brazil: A Spatio-Temporal Analysis and Socioeconomic Factors

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

The região extremo sul da Bahia (RESB - Extreme Southern Region of Bahia) has agricultural aptitude for several crops and has already been subjected to the expansion of sugarcane and coffee. Thus, this work analyzes the spatial and temporal dynamics of sugarcane and coffee monocultures in the RESB and their relationship with socioeconomic indices. The methodology consists of collection and analysis of data from the Instituto Brasileiro de Geografia e Estatística (IBGE), which is the main provider of geographic information and statistics in Brazil, the Companhia Nacional de Abastecimento (CONAB), which is responsible for providing technical information to support decision-making regarding the elaboration of policies aimed at agriculture and the Atlas Brasil platform. Data were collected regarding the planted area and the amount of sugarcane and coffee produced in the region between 1988 and 2019. To understand the relationship between expansion and socioeconomic factors, data related to gross domestic product (GDP) and municipal human development index (MHDI) were collected. This study identified the main sugarcane-producing municipalities (Caravelas, Mucuri, Medeiros Neto, Nova Viçosa, Lajedão, Ibirapuã and Santa Cruz Cabrália) and coffee (Prado, Itamaraju, Porto Seguro, Eunapolis, Teixeira de Freitas and Itabela). The expansion of these crops presents economic importance for the region, but presents a little contribution to the improvement of the various factors that make up the MHDI of the municipalities. This study concluded that the expansion of these crops changed the agricultural matrix of the region due to its specialization in the production of these crops to the detriment of others such as cocoa, for example.

Keywords
Agricultural expansion; Monoculture; Agricultural frontier; Socio-economic indices

MUNICIPALITY	PRINCIPAL PRODUCT	MHDI 1991	MHDI 2000	MHDI 2010	GROWTH RATE (%)
Alcobaça	-	0.272	0.453	0.608	124
Belmonte	-	0.31	0.441	0.598	93
Caravelas	Sugarcane	0.271	0.473	0.616	127
Eunápolis	Coffee	0.392	0.54	0.677	73
Guaratinga	-	0.253	0.356	0.558	121
Ibirapuã	Sugarcane	0.358	0.488	0.614	72
Itabela	Coffee	0.291	0.445	0.599	106
Itagimirim	-	0.309	0.493	0.634	105
Itamaraju	Coffee	0.334	0.462	0.627	88
Itanhém	-	0.346	0.496	0.637	84
Itapebi	-	0.218	0.394	0.572	162
Jucuruçu	-	0.202	0.354	0.541	168
Lajedão	Sugarcane	0.382	0.496	0.632	65
Medeiros Neto	Sugarcane	0.374	0.516	0.625	67
Mucuri	Sugarcane	0.275	0.525	0.665	142
Nova Viçosa	Sugarcane	0.318	0.455	0.654	106
Porto Seguro	Coffee	0.367	0.495	0.676	84
Prado	Coffee	0.298	0.471	0.621	108
Santa Cruz Cabrália	Sugarcane	0.334	0.486	0.654	96
Teixeira de Freitas	Coffee	0.378	0.539	0.685	81
Vereda	-	0.29	0.405	0.577	99
Bahia	-	0.386	0.512	0.66	71
Brazil	-	0.493	0.612	0.727	47

Municipalities	1980					1991				2000				2010
Municipalities	Total	Urb.	Rur.		% urb	Total	Urb.	Rur.	% urb	Total	Urb.	Rur.	% urb	Total	Urb.	Rur.	% urb
Caravelas	41,170	7,105	34,065		17	19,763	8,932	10,831	45	20,103	10,332	9,771	51	21,414	11,309	10,105	53
Eunápolis	-	-	-		-	70,545	63,540	7,005	90	84,120	79,161	4,959	94	100,196	93,413	6,783	93
Ibirapuã	9,801	3,428	6,373		35	8,290	3,413	4,877	41	7,096	3,573	3,523	50	7,956	4,532	3,424	57
Itabela	-	-	-		-	20,848	13,577	7,271	65	25,746	18,837	6,909	73	28,390	21,384	7,006	75
Itamaraju	77,678	33,109	44,569		43	64,308	44,449	19,859	69	64,144	48,037	16,107	75	63,069	49,785	13,284	79
Lajedão	4,685	1,945	2,740		42	3,818	1,663	2,155	44	3,409	1,852	1,557	54	3,733	2,076	1,657	56
Medeiros Neto	27,460	14,770	12,690		54	23,059	15,704	7,355	68	21,235	16,027	5,208	75	21,560	17,064	4,496	79
Mucuri	15,144	2,827	12,317		19	17,606	4,810	12,796	27	28,062	18,685	9,377	67	36,026	27,492	8,534	76
Nova Viçosa	18,591	6,092	12,499		33	25,570	9,374	16,196	37	32,076	24,636	7,440	77	38,556	33,526	5,030	87
Porto Seguro	46,300	5,725	40,575		12	34,661	23,315	11,346	67	95,721	79,619	16,102	83	126,929	104,078	22,851	82
Prado	26,433	6,898	19,535		26	22,632	9,655	12,977	43	26,498	14,169	12,329	53	27,627	15,474	12,153	56
Santa Cruz Cabrália	49,375	1,546	47,829		3	6,535	3,197	3,338	49	23,888	13,527	10,361	57	26,264	19,002	7,262	72
Teixeira de Freitas	-	-		-	-	85,547	74,221	11,326	87	107,486	98,688	8798	92	138,341	129,263	9,078	93

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[1] AUTHORS CONTRIBUTION

Regiane de Oliveira Almeida conceived the study, collected and analyzed the data and wrote the text. Thyane Viana da Cruz conceived and outlined the research. Maria Otávia Crepaldi contributed to the collection of data for the elaboration of the maps. Leonardo Thompson da Silva contributed to the collection of data for the elaboration of the maps. Ana Cristina de Sousa contributed to the review of the research objectives. Anderson Sena contributed to data collection and processing. Everton Mateus dos Santos Cerqueira contributed to data collection and processing.