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.
## 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 ...
## 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
## 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
## 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).