Comprehensive information on Nitrogen Use Efficiency for cereal crop production, N use Efficiency

  

Research Methods in Agriculture

Stability Analysis
Definitioon of Environment?

4 sites (locations), 20 varieties
4 sites planted at different times, 20 varieties
4 years, same location, 20 varieties

Article Combining Sites (class project)  (current H index) 6 years CIMMYT

Stability Analysis (treatment by environment interactions)

Does stability analysis allow us to compensate for the enivionment?

Stability Analysis (excel) (Step by Step)

Sarah Stability Analysis (Genotype by Environment interactions, plant Breeding)

 Magruder excel file (first page)
Use of Stability Analysis for Long-Term Soil Fertility Experiments
(pdf, Agron J. 85:159-167)


 2. Stability Analysis (excel) (Treatment by environment interactions, N Rate Example) READ (AGRONOMY)

(example for agronomic experiments, Use of Stability Analysis for Long-Term Soil Fertility Experiments.  Agron J. 85:159-167)

3. Magruder excel file (2018)
STABILITY1 (2019)

Transpose Function, OUTPUT DATA (2 examples)

data one;
input yr trt yield;
cards;
88        1          1000
88        2          2000
88        3          2400
89        1          4000
89        2          3200
89        3          3500
92        1          6000
92        2          7200
92        3          8800
data two; set one;
proc sort; by trt yr;
proc transpose data = two out = three prefix = y ;
id yr;
var yield;
by trt;
proc print;
run;

data one;
title 'Experiment 502';
input YR rep TRT buac ndvi;
cards;
2015 1 1 21.28178 0.36554
2015 1 2 12.36091 0.328445
2015 1 3 40.42274 0.31176
2015 1 4 26.82709 0.321575
2015 1 5 50.87466 0.382535
2015 1 6 50.00752 0.471955
2015 1 7 39.30216 0.35562
2015 1 8 36.33251 0.345845
2015 1 9 49.64076 0.32486
2015 1 10 47.74287 0.32503
2015 1 11 43.06957 0.395175
2015 1 12 43.06297 0.273865
2015 1 13 34.36974 0.338985
2015 1 14 47.73111 0.34379
2015 2 1 22.88433 0.34787
2015 2 2 24.69396 0.57251
2015 2 3 37.14757 0.48158
2015 2 4 34.68026 0.42269
2015 2 5 38.79577 0.484865
2015 2 6 37.21916 0.430585
2015 2 7 33.50571 0.5693
2015 2 8 14.00024 0.505865
2015 2 9 42.94052 0.50887
2015 2 10 44.13895 0.51408
2015 2 11 46.24279 0.431535
2015 2 12 38.71681 0.503365
2015 2 13 32.77249 0.47516
2015 2 14 38.82273 0.48257
2015 3 1 14.61918 0.514895
2015 3 2 35.14829 0.48562
2015 3 3 37.23976 0.47294
2015 3 4 29.93098 0.52958
2015 3 5 38.26039 0.41382
2015 3 6 38.66656 0.31307
2015 3 7 38.01788 0.49686
2015 3 8 30.47627 0.42585
2015 3 9 59.24651 0.43845
2015 3 10 41.84519 0.428305
2015 3 11 41.94684 0.441545
2015 3 12 44.23168 0.541045
2015 3 13 31.30745 0.439865
2015 3 14 29.37541 0.48239
2015 4 1 26.78909 0.41866
2015 4 2 41.85602 0.381125
2015 4 3 21.9037 0.38491
2015 4 4 39.64286 0.37452
2015 4 5 28.60002 0.279015
2015 4 6 47.06229 0.41004
2015 4 7 49.55126 0.399475
2015 4 8 40.6654 0.538765
2015 4 9 44.77015 0.39631
2015 4 10 49.58968 0.37811
2015 4 11 54.64815 0.44202
2015 4 12 51.95082 0.382965
2015 4 13 43.45964 0.409785
2015 4 14 56.00162 0.4493
2016 1 1 31.48766 0.462855
2016 1 2 11.34634 0.262175
2016 1 3 48.28937 0.540995
2016 1 4 41.90057 0.516977
2016 1 5 68.84554 0.678345
2016 1 6 68.22326 0.68275
2016 1 7 78.1176 0.720275
2016 1 8 38.89286 0.435065
2016 1 9 64.05394 0.621515
2016 1 10 62.60194 0.681395
2016 1 11 77.55754 0.680885
2016 1 12 77.12194 0.67568
2016 1 13 79.134 0.73458
2016 1 14 63.3072 0.67168
2016 2 1 23.35646 0.40803
2016 2 2 22.98309 0.49642
2016 2 3 40.34486 0.461225
2016 2 4 35.73994 0.552975
2016 2 5 47.6256 0.64803
2016 2 6 81.14606 0.725165
2016 2 7 80.586 0.681715
2016 2 8 48.82869 0.5676
2016 2 9 76.91451 0.703635
2016 2 10 76.45817 0.691615
2016 2 11 72.99411 0.679335
2016 2 12 77.30863 0.738825
2016 2 13 82.74326 0.72568
2016 2 14 81.85131 0.667615
2016 3 1 33.41674 0.476655
2016 3 2 39.99223 0.50729
2016 3 3 57.43697 0.55544
2016 3 4 64.80069 0.657595
2016 3 5 70.7124 0.74145
2016 3 6 74.07274 0.70844
2016 3 7 79.17549 0.72553
2016 3 8 65.94154 0.57041
2016 3 9 73.20154 0.71721
2016 3 10 71.31394 0.737585
2016 3 11 78.57394 0.72922
2016 3 12 73.49194 0.66059
2016 3 13 78.2628 0.728505
2016 3 14 71.99846 0.677075
2016 4 1 33.04337 0.41561
2016 4 2 39.61886 0.47183
2016 4 3 41.92131 0.479685
2016 4 4 52.16829 0.63576
2016 4 5 72.72446 0.643305
2016 4 6 77.49531 0.779375
2016 4 7 77.41234 0.768505
2016 4 8 60.65211 0.615025
2016 4 9 69.05297 0.68568
2016 4 10 76.06406 0.71884
2016 4 11 62.06263 0.728405
2016 4 12 79.09251 0.744165
2016 4 13 79.03029 0.818825
2016 4 14 73.59566 0.70691
2017 1 1 23.85717 0.314629
2017 1 2 12.68483 0.257307
2017 1 3 38.1755 0.356038
2017 1 4 36.44117 0.323612
2017 1 5 66.913 0.392922
2017 1 6 67.78017 0.394358
2017 1 7 83.732 0.299841
2017 1 8 47.1295 0.229693
2017 1 9 55.68017 0.365919
2017 1 10 60.8025 0.354267
2017 1 11 71.6925 0.393567
2017 1 12 83.77233 0.424359
2017 1 13 89.7215 0.388614
2017 1 14 55.9625 0.353884
2017 2 1 15.22583 0.265396
2017 2 2 16.698 0.242109
2017 2 3 29.50383 0.299444
2017 2 4 35.25133 0.267222
2017 2 5 52.97783 0.269743
2017 2 6 79.71883 0.355203
2017 2 7 83.0665 0.297053
2017 2 8 44.1045 0.284164
2017 2 9 71.34967 0.344706
2017 2 10 73.3865 0.372434
2017 2 11 59.97567 0.402907
2017 2 12 78.2265 0.329102
2017 2 13 73.084 0.289019
2017 2 14 77.88367 0.346586
2017 3 1 9.357333 0.239116
2017 3 2 18.25083 0.30686
2017 3 3 33.31533 0.390128
2017 3 4 56.18433 0.42831
2017 3 5 65.86433 0.372521
2017 3 6 71.16817 0.310582
2017 3 7 75.54433 0.413622
2017 3 8 64.45267 0.33567
2017 3 9 65.29967 0.397245
2017 3 10 70.46233 0.346632
2017 3 11 67.78017 0.436423
2017 3 12 64.41233 0.452181
2017 3 13 78.32733 0.400514
2017 3 14 58.03967 0.41715
2017 4 1 15.28633 0.27869
2017 4 2 23.61517 0.309064
2017 4 3 22.748 0.274233
2017 4 4 41.382 0.3178
2017 4 5 58.58417 0.35771
2017 4 6 66.71133 0.358414
2017 4 7 76.5325 0.375097
2017 4 8 48.01683 0.294
2017 4 9 60.78233 0.315517
2017 4 10 73.81 0.399386
2017 4 11 59.99583 0.401855
2017 4 12 73.8705 0.389664
2017 4 13 81.09017 0.379349
2017 4 14 56.18433 0.357562
2018 1 1 25.35127 0.350835
2018 1 2 21.24677 0.30902
2018 1 3 28.09376 0.38557
2018 1 4 33.89079 0.38648
2018 1 5 29.10124 0.374735
2018 1 6 29.28866 0.367505
2018 1 7 32.68307 0.265335
2018 1 8 22.95312 0.30112
2018 1 9 27.48733 0.348665
2018 1 10 28.26005 0.38271
2018 1 11 39.28575 0.3974
2018 1 12 34.50802 0.325165
2018 1 13 36.663 0.36565
2018 1 14 27.66738 0.382625
2018 2 1 23.55393 0.330865
2018 2 2 25.86312 0.38425
2018 2 3 28.66589 0.37975
2018 2 4 24.02724 0.41409
2018 2 5 35.79521 0.453455
2018 2 6 33.0427 0.29724
2018 2 7 31.03131 0.2848
2018 2 8 24.15685 0.335965
2018 2 9 36.50079 0.33095
2018 2 10 38.62329 0.414735
2018 2 11 30.76594 0.41802
2018 2 12 36.84715 0.37037
2018 2 13 35.04635 0.36169
2018 2 14 36.0845 0.319475
2018 3 1 25.23253 0.36541
2018 3 2 26.4264 0.380965
2018 3 3 28.12653 0.38771
2018 3 4 32.85669 0.424475
2018 3 5 20.37083 0.385495
2018 3 6 28.0802 0.325365
2018 3 7 30.97489 0.255205
2018 3 8 33.10883 0.29562
2018 3 9 26.02556 0.370545
2018 3 10 35.99467 0.37038
2018 3 11 36.61985 0.3283
2018 3 12 22.60888 0.40417
2018 3 13 32.21117 0.306895
2018 3 14 26.31142 0.408225
2018 4 1 28.32409 0.37795
2018 4 2 27.14981 0.39102
2018 4 3 30.40958 0.3913
2018 4 4 32.24415 0.455195
2018 4 5 27.11506 0.390775
2018 4 6 30.71747 0.34089
2018 4 7 29.21818 0.318405
2018 4 8 37.87698 0.385275
2018 4 9 37.71674 0.38376
2018 4 10 32.61109 0.403655
2018 4 11 36.16417 0.395455
2018 4 12 35.91522 0.36857
2018 4 13 30.10266 0.375965
2018 4 14 38.75564 0.38987
proc print;
/* data two; set one;
proc sort; by yr trt;
proc means noprint data = two; var yield ndvi;
output out = new2 mean = myield mndvi; by yr trt;
proc print data = work.new2;
run;

data three; set new2;
proc sort; by trt yr;
proc transpose data = three out = four prefix = y ;
id yr;
var myield;
by trt;
proc print;
run; */

data two; set one;
proc sort; by yr trt;
proc means noprint; by yr trt; var buac ndvi;
output out = new mean = ybuac yndvi;
data new1; set new; proc sort; by yr;
proc transpose data = new1 out = three prefix = trt;
by yr;
id trt;
var ybuac yndvi;
proc print;
run;

/* POPULATION MEANS */

data three; set one;
if yr>2016 then delete; /*CAN ONLY HAVE 2 */
proc ttest data = three;
class yr;
var buac ndvi;
run;

Procedure for Determining Differences in Population Means
data one; input sample time $ ph P oc k;
cards;
1          A         6.17    21.47  0.924  150
2          A         6.27    18.69  0.939  139
3          A         6.31    19.01  0.920  140
4          B         6.16    21.20  1.042  142
5          B         5.65    41.74  1.054  144
6          B         5.40    42.14  1.061  145

proc ttest;
class time;
var ph oc;
run;

A.  Proc Corr (r values)   (see added proc procedures that go with this data set)

data one;
input ndvi buac gn ph sn sp;
cards;

0.6205 34.42627 2.5107 6.39 0.10469 32.80725
0.294 18.51818 2.59762 5.54 0.0788 2.52685
0.429 24.41195 2.2206 5.40 0.0756 42.48705
0.4335 35.67636 2.6788 5.00 0.09356 28.1535
0.413 37.01768 2.8313 4.79 0.08893 44.907
0.5675 39.72107 2.8135 4.99 0.09549 35.04105
0.62347 19.14847 2.2536 6.48 0.08441 35.6701
0.290535 6.427076 2.1697 5.43 0.0715 6.8042
0.31301 8.449443 1.9589 5.44 0.06613 46.92191
0.684435 23.14757 2.5939 4.86 0.08623 50.63324
0.713725 23.81803 2.5314 4.75 0.07685 56.93661
0.7247 24.93252 2.8309 5.14 0.07576 46.68627
0.736 39.52 1.9444 6.55 0.08145 43.52569
0.286 15.22 1.7883 5.40 0.052864 7.91341
0.389 19.41 1.5578 5.32 0.05636 68.54739
0.661 44.37 1.7588 4.72 0.08549 56.56025
0.666 46.67 1.7828 4.64 0.06896 51.67229
0.740 44.76 1.9573 5.18 0.07717 43.06017
0.490 42.56 1.791567 6.19 0.096 81.34
0.227 15.32 1.674467 5.3 0.063 10.47
0.302 22.68 1.562867 5.18 0.073 76.86
0.417 52.08 1.670433 4.75 0.098 79.98
0.392 49.43 1.608467 4.57 0.095 88.72
0.441 53.15 1.674 5.12 0.101 73.85
0.44595 33.38476 . 6.61 0.146 104.96
0.24467 17.2852 . 5.56 0.123 21.45
0.29489 17.78717 . 5.39 0.136 119.75
0.33835 32.95005 . 4.91 0.16085 99.12
0.31672 31.94973 . 4.74 0.18162 88.43
0.38775 35.20741 . 5.44 0.16518 110.3

data one; (use above)
proc corr;
var ndvi buac gn ph sn sp;
run;


B.  coefficient of determination (R2), correlation coefficient (R)

data one; (use above)
proc glm;
model buac = ndvi;
run;

C.  r versus R (simple regression versus multiple regression)

data one; (use above)
proc glm;
model buac = ndvi ph sn;
run;


R2  (percent of the variability in y explained by x)

D. GO To 502 Surface Response Model (zz_502_surface.sas )  "R "


Applied Procedures

proc sort; by ______;
    Proc Plot (proc plot; plot y * x = "*"); by _____
    Proc Means (var statement) ; by ______  
    Proc corr (var statement); by ______

 RCBD vs CRD
Contrasts (orthogonal contrast coefficients)
Contrasts for Unequal Treatment Spacing


E. Covariance and Autocorrelation (go to Covariance Page)
use Mead soil test P example

Regression Analysis

Proc Mixed Example Using 502 Data

(PPT file, WEB analysis of Proc Mixed)

TEST of Differences in Slope and Intercept Two Independent Regressions

data one;
input exp a1 a2 x y;
if exp = 2015 then intc_dif = 0;
if exp = 2016 then intc_dif = 1;
slop_dif = intc_dif*x;
cards;
2015 1 1 21.28178 0.36554
2015 1 2 12.36091 0.328445
2015 1 3 40.42274 0.31176
2015 1 4 26.82709 0.321575
2015 1 5 50.87466 0.382535
2015 1 6 50.00752 0.471955
2015 1 7 39.30216 0.35562
2015 1 8 36.33251 0.345845
2015 1 9 49.64076 0.32486
2015 1 10 47.74287 0.32503
2015 1 11 43.06957 0.395175
2015 1 12 43.06297 0.273865
2015 1 13 34.36974 0.338985
2015 1 14 47.73111 0.34379
2015 2 1 22.88433 0.34787
2015 2 2 24.69396 0.57251
2015 2 3 37.14757 0.48158
2015 2 4 34.68026 0.42269
2015 2 5 38.79577 0.484865
2015 2 6 37.21916 0.430585
2015 2 7 33.50571 0.5693
2015 2 8 14.00024 0.505865
2015 2 9 42.94052 0.50887
2015 2 10 44.13895 0.51408
2015 2 11 46.24279 0.431535
2015 2 12 38.71681 0.503365
2015 2 13 32.77249 0.47516
2015 2 14 38.82273 0.48257
2015 3 1 14.61918 0.514895
2015 3 2 35.14829 0.48562
2015 3 3 37.23976 0.47294
2015 3 4 29.93098 0.52958
2015 3 5 38.26039 0.41382
2015 3 6 38.66656 0.31307
2015 3 7 38.01788 0.49686
2015 3 8 30.47627 0.42585
2015 3 9 59.24651 0.43845
2015 3 10 41.84519 0.428305
2015 3 11 41.94684 0.441545
2015 3 12 44.23168 0.541045
2015 3 13 31.30745 0.439865
2015 3 14 29.37541 0.48239
2015 4 1 26.78909 0.41866
2015 4 2 41.85602 0.381125
2015 4 3 21.9037 0.38491
2015 4 4 39.64286 0.37452
2015 4 5 28.60002 0.279015
2015 4 6 47.06229 0.41004
2015 4 7 49.55126 0.399475
2015 4 8 40.6654 0.538765
2015 4 9 44.77015 0.39631
2015 4 10 49.58968 0.37811
2015 4 11 54.64815 0.44202
2015 4 12 51.95082 0.382965
2015 4 13 43.45964 0.409785
2015 4 14 56.00162 0.4493
2016 1 1 31.48766 0.462855
2016 1 2 11.34634 0.262175
2016 1 3 48.28937 0.540995
2016 1 4 41.90057 0.516977
2016 1 5 68.84554 0.678345
2016 1 6 68.22326 0.68275
2016 1 7 78.1176 0.720275
2016 1 8 38.89286 0.435065
2016 1 9 64.05394 0.621515
2016 1 10 62.60194 0.681395
2016 1 11 77.55754 0.680885
2016 1 12 77.12194 0.67568
2016 1 13 79.134 0.73458
2016 1 14 63.3072 0.67168
2016 2 1 23.35646 0.40803
2016 2 2 22.98309 0.49642
2016 2 3 40.34486 0.461225
2016 2 4 35.73994 0.552975
2016 2 5 47.6256 0.64803
2016 2 6 81.14606 0.725165
2016 2 7 80.586 0.681715
2016 2 8 48.82869 0.5676
2016 2 9 76.91451 0.703635
2016 2 10 76.45817 0.691615
2016 2 11 72.99411 0.679335
2016 2 12 77.30863 0.738825
2016 2 13 82.74326 0.72568
2016 2 14 81.85131 0.667615
2016 3 1 33.41674 0.476655
2016 3 2 39.99223 0.50729
2016 3 3 57.43697 0.55544
2016 3 4 64.80069 0.657595
2016 3 5 70.7124 0.74145
2016 3 6 74.07274 0.70844
2016 3 7 79.17549 0.72553
2016 3 8 65.94154 0.57041
2016 3 9 73.20154 0.71721
2016 3 10 71.31394 0.737585
2016 3 11 78.57394 0.72922
2016 3 12 73.49194 0.66059
2016 3 13 78.2628 0.728505
2016 3 14 71.99846 0.677075
2016 4 1 33.04337 0.41561
2016 4 2 39.61886 0.47183
2016 4 3 41.92131 0.479685
2016 4 4 52.16829 0.63576
2016 4 5 72.72446 0.643305
2016 4 6 77.49531 0.779375
2016 4 7 77.41234 0.768505
2016 4 8 60.65211 0.615025
2016 4 9 69.05297 0.68568
2016 4 10 76.06406 0.71884
2016 4 11 62.06263 0.728405
data two; set one;
proc sort; by exp;
proc reg data = two;
model y = x intc_dif slop_dif;
run;
proc reg;
by exp;
model y = x;
run;

 

 

Added Class Program

data one;
input year rep trt buac;
cards;
2011  1     1     29.13
2011  1     2     22.44
2011  1     3     37.07
2011  1     4     34.88
2011  1     5     38.15
2011  1     6     35.15
2011  1     7     34.83
2011  1     8     48.58
2011  1     9     35.77
2011  1     10    37.86
2011  1     11    47.26
2011  1     12    48.48
2011  1     13    47.89
2011  1     14    38.62
2011  2     1     25.52
2011  2     2     29.42
2011  2     3     30.32
2011  2     4     41.71
2011  2     5     45.88
2011  2     6     47.45
2011  2     7     48.13
2011  2     8     41.68
2011  2     9     49.90
2011  2     10    42.09
2011  2     11    47.43
2011  2     12    50.31
2011  2     13    46.97
2011  2     14    47.57
2011  3     1     33.32
2011  3     2     29.50
2011  3     3     24.72
2011  3     4     41.12
2011  3     5     23.69
2011  3     6     50.76
2011  3     7     54.57
2011  3     8     45.64
2011  3     9     24.64
2011  3     10    48.06
2011  3     11    53.34
2011  3     12    21.19
2011  3     13    17.13
2011  3     14    46.13
2011  4     1     29.12
2011  4     2     28.70
2011  4     3     29.06
2011  4     4     27.45
2011  4     5     33.33
2011  4     6     28.41
2011  4     7     41.24
2011  4     8     44.58
2011  4     9     48.67
2011  4     10    31.52
2011  4     11    46.24
2011  4     12    40.51
2011  4     13    33.24
2011  4     14    46.06
2012  1     1     23.96
2012  1     2     18.55
2012  1     3     37.45
2012  1     4     43.08
2012  1     5     54.32
2012  1     6     57.85
2012  1     7     63.22
2012  1     8     50.38
2012  1     9     49.44
2012  1     10    49.20
2012  1     11    62.95
2012  1     12    62.23
2012  1     13    61.34
2012  1     14    52.85
2012  2     1     22.94
2012  2     2     28.51
2012  2     3     31.36
2012  2     4     49.26
2012  2     5     57.01
2012  2     6     60.81
2012  2     7     56.56
2012  2     8     53.39
2012  2     9     55.71
2012  2     10    57.79
2012  2     11    57.23
2012  2     12    63.18
2012  2     13    59.13
2012  2     14    63.15
2012  3     1     27.02
2012  3     2     28.27
2012  3     3     39.78
2012  3     4     47.45
2012  3     5     61.44
2012  3     6     62.07
2012  3     7     62.97
2012  3     8     59.45
2012  3     9     60.86
2012  3     10    52.64
2012  3     11    56.36
2012  3     12    61.55
2012  3     13    64.25
2012  3     14    53.68
2012  4     1     29.34
2012  4     2     32.97
2012  4     3     32.03
2012  4     4     53.80
2012  4     5     48.77
2012  4     6     61.87
2012  4     7     62.15
2012  4     8     47.33
2012  4     9     53.83
2012  4     10    60.89
2012  4     11    57.85
data two; set one;
proc sort; by year;
proc glm; by year;
  class rep trt;
  model buac = rep trt;
  means trt/duncan;
proc glm;
  class year rep trt;
  model buac = year rep(year) trt year*trt;
  test h = year e = rep(year);
means year trt year*trt;
run;

data four; set one;  proc sort; by year rep trt;
data five; set three; proc sort; by year rep trt;

data six; merge four five; by year rep trt;
proc print;

502 Update Program (excel file) go to Mean_SD

Site from 2001  (added programs)