Este experimento teve como objetivo relacionar a epidemia de mancha alvo por estrato dentro do período crítico da soja (R3 a R6) com o rendimento em grãos da cultura.

Para isso foram feitas inoculações em R1 com inóculo produzido in vitro com mistura de isolados provenientes de diferentes regiões do Brasil.

Dataset

##    inoc rep parcela est 29-dez 09-jan 16-jan 22-jan 02-fev 10-fev
## 1     0   1     0.1   i    0.0    0.7    3.5   10.0   12.3   20.0
## 2     0   1     0.1   m    0.0    0.1    1.0    9.0    9.0   15.0
## 3     0   1     0.1   s    0.0    0.0    0.0    0.0    0.0    5.0
## 4     1   1     1.1   i    5.2   10.0   25.0   26.7   29.8   39.1
## 5     1   1     1.1   m    0.0    0.6   10.0   19.0   25.0   35.0
## 6     1   1     1.1   s    0.0    0.1    0.5    3.0    3.0    5.0
## 7     1   2     1.2   i    6.4   17.5   40.0   43.0   45.0   46.0
## 8     1   2     1.2   m    0.0    2.3   12.5   18.0   30.0   30.0
## 9     1   2     1.2   s    0.0    0.0    2.5    2.5    2.0    8.0
## 10    1   3     1.3   i    1.0    5.0   15.0   25.0   35.0   35.0
## 11    1   3     1.3   m    0.0    1.0   12.5   20.0   26.0   32.0
## 12    1   3     1.3   s    0.0    0.2    1.0    4.0    5.0    5.0
## 13    2   1     2.1   i    5.1    7.9   17.5   21.9   40.0   45.8
## 14    2   1     2.1   m    0.0    2.7   17.5   17.5   35.0   40.0
## 15    2   1     2.1   s    0.0    0.2    0.2    1.5    2.5    4.0
## 16    2   2     2.2   i    8.4   27.8   35.0   44.4   47.0   50.0
## 17    2   2     2.2   m    0.0    5.8   21.5   21.5   22.5   35.0
## 18    2   2     2.2   s    0.0    0.0    1.0    1.0    1.0    3.0
## 19    2   3     2.3   i   12.6   28.7   40.0   49.7   60.0   62.0
## 20    2   3     2.3   m    0.0   13.1   32.5   32.5   33.0   33.0
## 21    2   3     2.3   s    0.0    0.0    1.0    3.0    3.0    4.0
## 22    3   1     3.1   i   18.0   25.0   30.0   55.0   65.0   67.0
## 23    3   1     3.1   m    0.0   15.0   25.0   25.0   42.5   45.0
## 24    3   1     3.1   s    0.0    0.4    1.0    2.0    3.5    7.0
## 25    3   2     3.2   i   22.7   36.0   38.0   38.8   45.0   47.0
## 26    3   2     3.2   m    0.0    6.0   17.5   19.0   37.5   37.5
## 27    3   2     3.2   s    0.0    0.0    0.5    1.0    3.5    5.0
## 28    3   3     3.3   i   16.8   37.5   42.0   44.0   47.7   50.4
## 29    3   3     3.3   m    0.0    6.4   30.0   30.0   28.5   35.0
## 30    3   3     3.3   s    0.0    0.0    1.5    3.0    3.0    5.0
## 31    4   1     4.1   i   12.4   54.0   60.0   76.8   78.0   80.0
## 32    4   1     4.1   m    0.0    8.8   38.5   38.5   42.5   45.0
## 33    4   1     4.1   s    0.0    0.1    1.0    3.0    3.5    7.0
## 'data.frame':    198 obs. of  6 variables:
##  $ inoc   : int  0 0 0 1 1 1 1 1 1 1 ...
##  $ rep    : int  1 1 1 1 1 1 2 2 2 3 ...
##  $ parcela: Factor w/ 11 levels "0.1","1.1","1.2",..: 1 1 1 2 2 2 3 3 3 4 ...
##  $ est    : Factor w/ 3 levels "i","m","s": 1 2 3 1 2 3 1 2 3 1 ...
##  $ day    : Factor w/ 6 levels "1","11","18",..: 1 1 1 1 1 1 1 1 1 1 ...
##  $ sev    : num  0 0 0 5.2 0 0 6.4 0 0 1 ...

Progresso da severidade

Área abaixo da curva do progresso da severidade (por estrato)

##    plot inoc rep estrato     auc
## 1   0.1    0   1       i  310.55
## 2   0.1    0   1       m  229.35
## 3   0.1    0   1       s   20.00
## 4   1.1    1   1       i  939.95
## 5   1.1    1   1       m  609.10
## 6   1.1    1   1       s   78.10
## 7   1.2    1   2       i 1417.75
## 8   1.2    1   2       m  658.80
## 9   1.2    1   2       s   88.50
## 10  1.3    1   3       i  830.00
## 11  1.3    1   3       m  634.75
## 12  1.3    1   3       s  109.70
## 13  2.1    2   1       i  955.75
## 14  2.1    2   1       m  777.95
## 15  2.1    2   1       s   55.50
## 16  2.2    2   2       i 1529.70
## 17  2.2    2   2       m  725.55
## 18  2.2    2   2       s   36.50
## 19  2.3    2   3       i 1807.40
## 20  2.3    2   3       m 1044.35
## 21  2.3    2   3       s   76.50
## 22  3.1    3   1       i 1850.50
## 23  3.1    3   1       m 1086.25
## 24  3.1    3   1       s   88.15
## 25  3.2    3   2       i 1611.80
## 26  3.2    3   2       m  832.50
## 27  3.2    3   2       s   65.00
## 28  3.3    3   3       i 1704.50
## 29  3.3    3   3       m  915.15
## 30  3.3    3   3       s   83.75
## 31  4.1    4   1       i 2624.80
## 32  4.1    4   1       m 1236.05
## 33  4.1    4   1       s   94.10
##    plot     auc
## 1   0.1  559.90
## 2   1.1 1627.15
## 3   1.2 2165.05
## 4   1.3 1574.45
## 5   2.1 1789.20
## 6   2.2 2291.75
## 7   2.3 2928.25
## 8   3.1 3024.90
## 9   3.2 2509.30
## 10  3.3 2703.40
## 11  4.1 3954.95

Trilha

##    plot auc_planta  auc_ei  auc_em auc_es kg_par hum_par kg_ha_brut
## 1   0.1     559.90  310.55  229.35  20.00  1.535   0.166     3837.5
## 2   1.1    1627.15  939.95  609.10  78.10  1.485   0.158     3712.5
## 3   1.2    2165.05 1417.75  658.80  88.50  1.320   0.166     3300.0
## 4   1.3    1574.45  830.00  634.75 109.70  1.925   0.149     4812.5
## 5   2.1    1789.20  955.75  777.95  55.50  1.390   0.162     3475.0
## 6   2.2    2291.75 1529.70  725.55  36.50  1.330   0.136     3325.0
## 7   2.3    2928.25 1807.40 1044.35  76.50  1.405   0.128     3512.5
## 8   3.1    3024.90 1850.50 1086.25  88.15  1.060   0.151     2650.0
## 9   3.2    2509.30 1611.80  832.50  65.00  1.535   0.143     3837.5
## 10  3.3    2703.40 1704.50  915.15  83.75  1.400   0.151     3500.0
## 11  4.1    3954.95 2624.80 1236.05  94.10  1.205   0.143     3012.5
##    kg_ha_13
## 1    3678.7
## 2    3593.0
## 3    3163.4
## 4    4707.4
## 5    3347.2
## 6    3302.1
## 7    3520.6
## 8    2586.0
## 9    3780.2
## 10   3415.5
## 11   2967.5

Análise de regressão linear para testar dano

## Analysis of Variance Table
## 
## Response: kg_ha_13
##            Df  Sum Sq Mean Sq F value  Pr(>F)  
## auc_planta  1  853706  853706  3.8263 0.08216 .
## Residuals   9 2008060  223118                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

##      StudRes       Hat     CookD
## 1 -0.9715977 0.4558373 0.6307646
## 4  3.5262106 0.1527577 0.7026416
## Analysis of Variance Table
## 
## Response: kg_ha_13
##            Df Sum Sq Mean Sq F value  Pr(>F)  
## auc_planta  1 364400  364400  3.7082 0.09032 .
## Residuals   8 786158   98270                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

##      StudRes       Hat     CookD
## 1 -0.2171322 0.5244718 0.1717989
## 8 -2.9223023 0.1590209 0.6447127

## Analysis of Variance Table
## 
## Response: kg_ha_13
##           Df  Sum Sq Mean Sq F value  Pr(>F)  
## auc_ei     1  919861  919861  4.2632 0.06895 .
## Residuals  9 1941904  215767                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

##      StudRes       Hat     CookD
## 4  3.3386384 0.1782124 0.7537374
## 11 0.2526956 0.4612523 0.1746663
## Analysis of Variance Table
## 
## Response: kg_ha_13
##           Df Sum Sq Mean Sq F value Pr(>F)
## auc_ei     1 339170  339170  3.3441 0.1048
## Residuals  8 811387  101423
## Analysis of Variance Table
## 
## Response: kg_ha_13
##           Df  Sum Sq Mean Sq F value Pr(>F)
## auc_em     1  729195  729195  3.0774 0.1133
## Residuals  9 2132571  236952

##      StudRes       Hat     CookD
## 1 -0.9848267 0.5118772 0.7143171
## 4  3.7433092 0.1248280 0.6392017
## Analysis of Variance Table
## 
## Response: kg_ha_13
##           Df Sum Sq Mean Sq F value Pr(>F)  
## auc_em     1 375513  375513   3.876 0.0845 .
## Residuals  8 775045   96881                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Analysis of Variance Table
## 
## Response: kg_ha_13
##           Df  Sum Sq Mean Sq F value Pr(>F)
## auc_es     1   19261   19261   0.061 0.8105
## Residuals  9 2842505  315834

##     StudRes       Hat     CookD
## 1 0.7403696 0.4867276 0.5231038
## 4 4.3016490 0.2924787 1.1396234
## Analysis of Variance Table
## 
## Response: kg_ha_13
##           Df Sum Sq Mean Sq F value Pr(>F)
## auc_es     1 292579  292579  2.7281 0.1372
## Residuals  8 857979  107247

Conclusão:

A área abaixo da curva do progresso da severidade de mancha alvo (AUC) dentro do período critico não teve relação direta com o peso dos grãos ao 5% de significância (P < 0,092), podendo considerar-se significativo com \(\alpha\) = 10%.

O mesmo ocorreu considerando apenas o estrato médio, que com menor desenvolvimento da severidade que o estrato inferior apresenta ter maior relevância para o rendimento (P < 0,0845).