试验设计试验设计时农业中比较核心的技能, 关系着试验数据的好坏, 关系着后续分析的模型, 关系着效率的高低. 兵马未动, 粮草先行. 好的试验设计, 事半功倍. 一个简单的试验: RCBD小师妹来信:
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品种: 郑单958, 先玉335, 登海605, 豫玉22, 浚单20. 代码 library(agricolae)
cul = c( "郑单958", "先玉335", "登海605", "豫玉22", "浚单20")
rep = 3
exp = design.rcbd(cul,rep)
exp$book
exp$sketch
write.csv(exp$book,"d:/book.csv") 结果 拉丁方小师妹:
exp = design.lsd(cul)
exp$book
exp$sketch
write.csv(exp$book,"d:/book.csv") 田间种植图 Latin和Lattice什么区别啊师妹来信:
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alpha-lattice怎么设计师妹来信:
代码: cul = paste0("cul",1:100)
exp = design.alpha(1:120,10,3)
exp$sketch
write.csv(exp$book,"d:/book.csv") 田间种植图: $`rep1`
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "48" "12" "82" "63" "56" "54" "2" "50" "53" "68"
[2,] "86" "100" "43" "4" "61" "70" "89" "57" "91" "81"
[3,] "52" "90" "26" "42" "46" "67" "71" "66" "79" "5"
[4,] "98" "107" "51" "45" "72" "75" "18" "65" "73" "49"
[5,] "41" "104" "27" "19" "11" "34" "44" "85" "69" "92"
[6,] "24" "38" "118" "30" "83" "113" "8" "95" "33" "119"
[7,] "80" "58" "55" "17" "25" "106" "16" "9" "60" "37"
[8,] "101" "3" "78" "120" "84" "35" "1" "88" "99" "96"
[9,] "13" "6" "21" "108" "22" "117" "105" "32" "111" "102"
[10,] "31" "28" "62" "87" "36" "64" "93" "39" "97" "23"
[11,] "59" "112" "47" "115" "76" "29" "114" "15" "103" "94"
[12,] "74" "109" "10" "7" "77" "40" "20" "110" "116" "14"
$rep2
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "65" "8" "15" "22" "42" "25" "99" "50" "110" "39"
[2,] "3" "52" "86" "54" "60" "119" "93" "117" "20" "49"
[3,] "56" "44" "98" "83" "90" "70" "74" "87" "114" "111"
[4,] "82" "96" "51" "38" "46" "106" "112" "62" "11" "105"
[5,] "33" "5" "12" "1" "29" "104" "100" "7" "102" "107"
[6,] "31" "75" "118" "26" "53" "84" "69" "94" "16" "4"
[7,] "43" "79" "35" "109" "68" "32" "76" "37" "85" "30"
[8,] "21" "73" "47" "88" "36" "61" "2" "55" "41" "14"
[9,] "71" "24" "40" "58" "45" "78" "103" "64" "57" "27"
[10,] "6" "89" "77" "23" "19" "48" "17" "113" "72" "59"
[11,] "67" "10" "92" "63" "28" "9" "120" "18" "81" "13"
[12,] "95" "97" "80" "66" "115" "116" "101" "91" "108" "34"
$rep3
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "17" "90" "18" "34" "57" "36" "33" "76" "54" "22"
[2,] "59" "109" "44" "108" "99" "31" "52" "100" "106" "45"
[3,] "3" "19" "75" "47" "7" "62" "25" "70" "67" "32"
[4,] "107" "37" "112" "81" "101" "14" "71" "6" "56" "118"
[5,] "38" "10" "26" "80" "15" "86" "21" "98" "78" "48"
[6,] "92" "96" "12" "16" "119" "77" "64" "61" "42" "111"
[7,] "49" "50" "30" "55" "27" "28" "115" "105" "5" "4"
[8,] "43" "9" "113" "116" "65" "82" "88" "104" "93" "114"
[9,] "23" "110" "63" "117" "11" "35" "73" "24" "94" "66"
[10,] "13" "2" "72" "79" "69" "20" "95" "103" "1" "87"
[11,] "68" "97" "74" "89" "84" "58" "41" "8" "102" "46"
[12,] "85" "40" "60" "53" "83" "91" "29" "51" "39" "120" alpha-lattice VS RCBD1、 什么是完全随机区组试验? 2、 什么是alpha-格子试验设计? 3、两者比较,完全随机区组的区组数不能大于10个品种,否则区组内均一性受到影响,区组设置失效。另外对于处理因素(品种)较多的试验,完全随机区组不适合,而alpha-格子试验设计,其区组内的品种可以控制较小的个数,因此总处理个数不受限制,完全随机区组适合处理数小于10个的试验,处理较多时用alpha-格子试验设计更好。 增广试验设计师妹来信:
# augmented design
cul = paste0("cul",1:200)
ck = paste0("ck",1:2)
exp = design.dau(ck,cul,20)
exp$parameters
exp$book
write.csv(exp$book,"d:/book.csv") 结果 和传统间比法不一样的是, 对照是随机的, 品种也是随机的. 优势在于分析时更精确. 还有没有更好的试验设计?师妹来信:
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agricolae包中有但是没有介绍的试验设计
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