Previsão de produtividade anual de café arábica por meio do deficit hídrico

O objetivo deste trabalho foi desenvolver modelos agrometeorológicos para a previsão da produtividade anual de café arábica (Coffea arabica), por meio dos deficits hídricos (DEFs) durante o ciclo do café, em importantes locais do Estado de Minas Gerais, Brasil. Para a construção dos modelos, foram utilizados um conjunto de dados meteorológicos com abrangência de 18 anos e regressões lineares múltiplas. Os modelos foram calibrados em anos de alta e baixa produtividade, em razão de a bienalidade da cultura ser elevada no Brasil. Todos os modelos calibrados para anos de alta e baixa produtividade foram acurados e significativos a 5% de probabilidade, com média de erros percentuais absolutos ≤2,9%. O período mínimo de previsão da produtividade é de seis meses para o Sul de Minas Gerais e para o Cerrado Mineiro. Em anos de alta produtividade, os deficits hídricos afetam mais o estádio reprodutivo do café, enquanto, em anos de baixa produtividade, afetam mais os estádios vegetativos da cultura.

Termos de indexação:
Coffea arabica; agrometeorologia; clima; previsão; modelo; balanço hídrico

Autoria

Lucas Eduardo de Oliveira Aparecido

Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Departamento de Economia, Administração e Educação, Via de Acesso Prof. Paulo Donato Castellane, s/no, CEP 14884-900 Jaboticabal, SP, Brazil. E-mail: lucas.aparecido@ifms.edu.br, rolim@fcav.unesp.brUniversidade Estadual PaulistaBrazilJaboticabal, SP, BrazilUniversidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Departamento de Economia, Administração e Educação, Via de Acesso Prof. Paulo Donato Castellane, s/no, CEP 14884-900 Jaboticabal, SP, Brazil. E-mail: lucas.aparecido@ifms.edu.br, rolim@fcav.unesp.br

Glauco de Souza Rolim

SCIMAGO INSTITUTIONS RANKINGS

Figuras | Tabelas | Fórmulas

Figuras (8)
Tabelas (1)
Fórmulas (6)

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Figure 1.
Main regions for coffee production in the state of Minas Gerais, Brazil. Municipalities in southern Minas Gerais state: GXP, Guaxupé; MSM, Monte Santo de Minas; and SSP, São Sebastião do Paraíso. Municipalities in the Cerrado Mineiro region: CRD, Coromandel; SDS Serra do Salitre; and TRS, Tiros.

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Figure 2.
Phenology of Coffea arabica (modified from Camargo & Camargo, 2001CAMARGO, Â.P. de; CAMARGO, M.B.P. Definição e esquematização das fases fenológicas do cafeeiro arábica nas condições tropicais do Brasil. Bragantia, v.60, p.65-68, 2001. DOI: 10.1590/S0006-87052001000100008.
https://doi.org/10.1590/S0006-8705200100... ). Indexes: y-1, first phenological year, y, second phenological year; i-2, first chronological year; i-1, second chronological year; and i, third chronological year.

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Figure 3.
Coffee phenology: A, plant development; B, plagiotropic branch development of coffee.

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Figure 4.
Relation between water deficit and coffee yield, in southern Minas Gerais (A), and in Cerrado Mineiro region (B), Minas Gerais state, Brazil; and coffee yields of these regions (C). Municipalities in southern Minas Gerais state (SO_MG): GXP, Guaxupé; MSM, Monte Santo de Minas; SSP, São Sebastião do Paraíso. Municipalities in the Cerrado Mineiro region (CE_MG): CRD, Coromandel; SDS, Serra do Salitre; and TRS, Tiros. The linear regression has 95% confidence interval.

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Figure 5.
Total number of generated models (A): models with multicollinearity and viable models for one region; and model classification (B), according to criteria of accuracy (lowest MAPE), precision (greater R² adj), and reliability (p-value). VM, viable models; MC, models with multicolinnearity; and T, total number of models.

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Figure 6.
Frequency and correlation of the monthly water deficiency with coffee yield of the selected 20 best models: high-yield (A) and low-yield (B) seasons. Municipalities in southern Minas Gerais state (SO_MG), Brazil: GXP, Guaxupé; MSM, Monte Santo de Minas; and SSP, São Sebastião do Paraíso. Municipalities in the Cerrado Mineiro (CE_MG) region, MG, Brazil: CRD, Coromandel; SDS, Serra do Salitre; and TRS, Tiros.

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Figure 7.
Agrometeorological models using monthly water deficiency to forecast high-yield seasons of arabica coffee. Municipalities in southern Minas Gerais state (SO_MG), Brazil: GXP, Guaxupé; MSM, Monte Santo de Minas; and SSP, São Sebastião do Paraíso. Municipalities in the Cerrado Mineiro (CE_MG) region, MG, Brazil: CRD, Coromandel; SDS, Serra do Salitre; and TRS, Tiros. BF, bud formation; BG, bud growth; FL, flowering; PH, pinhead; GE, grain expansion; GF, grain formation; and MT, maturation.

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Figure 8.
Agrometeorological models using monthly water deficiency to forecast low-yield seasons of arabica coffee. Municipalities in southern Minas Gerais (SO_MG) state, Brazil: GXP, Guaxupé; MSM, Monte Santo de Minas; and SSP, São Sebastião do Paraíso. Municipalities in the Cerrado Mineiro (CE_MG) region, MG, Brazil: CRD, Coromandel; SDS, Serra do Salitre; and TRS, Tiros. BF, bud formation; BG, bud growth; FL, flowering; PH, pinhead; GE, grain expansion; GF, grain formation; and MT, maturation.

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Table 1.
Geographic and climatic description of the regions.

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Figure 1. Main regions for coffee production in the state of Minas Gerais, Brazil. Municipalities in southern Minas Gerais state: GXP, Guaxupé; MSM, Monte Santo de Minas; and SSP, São Sebastião do Paraíso. Municipalities in the Cerrado Mineiro region: CRD, Coromandel; SDS Serra do Salitre; and TRS, Tiros.

Figure 2. Phenology of Coffea arabica (modified from Camargo & Camargo, 2001CAMARGO, Â.P. de; CAMARGO, M.B.P. Definição e esquematização das fases fenológicas do cafeeiro arábica nas condições tropicais do Brasil. Bragantia, v.60, p.65-68, 2001. DOI: 10.1590/S0006-87052001000100008.
https://doi.org/10.1590/S0006-8705200100... ). Indexes: y-1, first phenological year, y, second phenological year; i-2, first chronological year; i-1, second chronological year; and i, third chronological year.

Figure 3. Coffee phenology: A, plant development; B, plagiotropic branch development of coffee.

Figure 4. Relation between water deficit and coffee yield, in southern Minas Gerais (A), and in Cerrado Mineiro region (B), Minas Gerais state, Brazil; and coffee yields of these regions (C). Municipalities in southern Minas Gerais state (SO_MG): GXP, Guaxupé; MSM, Monte Santo de Minas; SSP, São Sebastião do Paraíso. Municipalities in the Cerrado Mineiro region (CE_MG): CRD, Coromandel; SDS, Serra do Salitre; and TRS, Tiros. The linear regression has 95% confidence interval.

Figure 5. Total number of generated models (A): models with multicollinearity and viable models for one region; and model classification (B), according to criteria of accuracy (lowest MAPE), precision (greater R² adj), and reliability (p-value). VM, viable models; MC, models with multicolinnearity; and T, total number of models.

Figure 6. Frequency and correlation of the monthly water deficiency with coffee yield of the selected 20 best models: high-yield (A) and low-yield (B) seasons. Municipalities in southern Minas Gerais state (SO_MG), Brazil: GXP, Guaxupé; MSM, Monte Santo de Minas; and SSP, São Sebastião do Paraíso. Municipalities in the Cerrado Mineiro (CE_MG) region, MG, Brazil: CRD, Coromandel; SDS, Serra do Salitre; and TRS, Tiros.

Figure 7. Agrometeorological models using monthly water deficiency to forecast high-yield seasons of arabica coffee. Municipalities in southern Minas Gerais state (SO_MG), Brazil: GXP, Guaxupé; MSM, Monte Santo de Minas; and SSP, São Sebastião do Paraíso. Municipalities in the Cerrado Mineiro (CE_MG) region, MG, Brazil: CRD, Coromandel; SDS, Serra do Salitre; and TRS, Tiros. BF, bud formation; BG, bud growth; FL, flowering; PH, pinhead; GE, grain expansion; GF, grain formation; and MT, maturation.

Figure 8. Agrometeorological models using monthly water deficiency to forecast low-yield seasons of arabica coffee. Municipalities in southern Minas Gerais (SO_MG) state, Brazil: GXP, Guaxupé; MSM, Monte Santo de Minas; and SSP, São Sebastião do Paraíso. Municipalities in the Cerrado Mineiro (CE_MG) region, MG, Brazil: CRD, Coromandel; SDS, Serra do Salitre; and TRS, Tiros. BF, bud formation; BG, bud growth; FL, flowering; PH, pinhead; GE, grain expansion; GF, grain formation; and MT, maturation.

Table 1. Geographic and climatic description of the regions.

Municipalities	C/T⁽¹⁾	Latitude	Longitude	Altitude (m)	Climate⁽²⁾
		South of Minas Gerais
Guaxupé (GXP)	C	21º18'13"S	46º42'31"W	824	B₂rB’₄a’
Monte Santo de Minas (MSM)	C	21º11'44"S	46º57'46"W	892	B₃rB’₃a’
São Sebastião do Paraiso (SSP)	C/T	20º54'36"S	47º06'34"W	973	B₄rB’₂a’
		Cerrado Mineiro
Coromandel (CRD)	C	18º28'19"S	47º11'34"W	928	B₂wB’₃a’
Serra do Salitre (SDS)	C	19º05'50"S	46º40'25"W	1244	B₂wB’₃a’
Tiros (TRS)	C/T	18º59'53"S	45º58'11"W	977	B₂wB’₃a’

⁽¹⁾C and T are calibration and test, respectively. ⁽²⁾Following Thornthwaite's climatic classification (1948)THORNTHWAITE, C.W. An approach toward a rational classification of climate. Geographical Review, v.38, p.55-94, 1948. DOI: 10.2307/210739.
https://doi.org/10.2307/210739... .

{ALT}_{i} = {STO}_{I} - {STO}_{I - 1,} and

AET = {\begin{matrix} R + | ALT | & , if ALT < 0 \\ PET & , if ALT \geq 0 \end{matrix}},

M A P E = \frac{\sum_{i = 1}^{n} (| \frac{Y e s t_{i} - Y o b s_{i}}{Y o b s_{i}} | \times 100)}{n};

R^{2} a d j = [1 - \frac{(1 - R^{2}) \times (n - 1)}{n - k - a}],

M S M_{H i g h} = 4.55 \times D E F_{M a y_{(i - 1)}} + 0.779 \times D E F_{J u n e_{(i - 1)}} = 1.479 \times D E F_{J u l y_{(i - 1)}} - 0.585 \times D E F_{O c t ._{(i - 1)}} + 59.14,

G X P_{L O W} = - 0.503 \times D E F_{O c t ._{(i - 2)}} - 0.384 \times D E F_{A p r ._{(i - 1)}} + 0.106 \times D E F_{S e p t ._{(i - 1)}} + 0.014 \times D E F_{O c t .}_{_{(i - 1)}} + 34.5 .

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Previsão de produtividade anual de café arábica por meio do deficit hídrico

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[TFN1] ⁽¹⁾C and T are calibration and test, respectively. ⁽²⁾Following Thornthwaite's climatic classification (1948)THORNTHWAITE, C.W. An approach toward a rational classification of climate. Geographical Review, v.38, p.55-94, 1948. DOI: 10.2307/210739.
https://doi.org/10.2307/210739... .