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A comprehensive dataset of observed plant growth metrics, including organ biomass and dry matter samplings. These measurements are integral for crop modeling and physiology studies, offering insights into the development and health of different cultivars under varying conditions.

Usage

plant

Format

A data.frame with 77 rows and 22 columns:

ID

Trial ID - (character). A unique identifier for each trial. Example: "LOC1T1PROJ1".

LOC_ID

Locality ID - (character). Indicates the location of the trial. Example: "LOC1".

CULTIVAR

Cultivar name - (character). Specifies the plant cultivar used in the trial. Example: "CULTIVAR1".

SAMPLING_DATE

Sampling date - (date). The date when the plant sampling was conducted, in MM/DD/YYYY format.

LAI_OBS

Leaf Area Index observed - (numeric). Measures the area of leaves per unit area of ground, in m² leaf/m² ground.

LAI_SE

Leaf Area Index standard deviation - (numeric). The standard deviation of the Leaf Area Index, in m² leaf/m² ground.

WLVG_OBS

Green leaf dry weight - (numeric). The dry weight of green leaves, in kg/ha.

WLVG_SE

Green leaf dry weight standard error - (numeric). The standard error of green leaf dry weight, in kg/ha.

WLVD_OBS

Dead leaf dry weight - (numeric). The dry weight of dead leaves, in kg/ha.

WLVD_SE

Dead leaf dry weight standard error - (numeric). The standard error of dead leaf dry weight, in kg/ha.

WST_OBS

Stem dry weight - (numeric). The dry weight of stems, in kg/ha.

WST_SE

Stem dry weight standard error - (numeric). The standard error of stem dry weight, in kg/ha.

WSO_OBS

Panicle dry weight - (numeric). The dry weight of panicles, in kg/ha.

WSO_SE

Panicle dry weight standard error - (numeric). The standard error of panicle dry weight, in kg/ha.

WAGT_OBS

Total dry weight - (numeric). The total plant dry weight, including all sampled organs, in kg/ha.

WAGT_SE

Total dry weight standard error - (numeric). The standard error of total dry weight, in kg/ha.

NLV_OBS

Number of green leaves - (numeric). The number of green leaves per square meter, in number/m².

NLV_SE

Number of green leaves standard error - (numeric). The standard error of the number of green leaves, in number/m².

NST_OBS

Number of stems - (numeric). The number of stems per square meter, in number/m².

NST_SE

Number of stems standard error - (numeric). The standard error of the number of stems, in number/m².

NP_OBS

Number of panicles - (numeric). The number of panicles per square meter, in number/m².

NP_SE

Number of panicles standard error - (numeric). The standard error of the number of panicles, in number/m².

Source

Rodriguez-Espinoza J, (2024) and CIAT-MADR-FEDEARROZ, (2016)

Details

Observed Plant Growth Data

This dataset contains observed plant growth data, including organ biomass or dry matter samplings, crucial for modeling and crop physiology studies. It provides a detailed view of plant growth dynamics across various trials, facilitating the analysis of crop development, yield potential, and the effects of agronomic treatments on plant growth.

Examples

# Assuming `plant` is your dataset name
summary(plant)
#>       ID               LOC_ID            CULTIVAR         SAMPLING_DATE       
#>  Length:77          Length:77          Length:77          Min.   :2013-05-21  
#>  Class :character   Class :character   Class :character   1st Qu.:2014-02-13  
#>  Mode  :character   Mode  :character   Mode  :character   Median :2014-05-29  
#>                                                           Mean   :2014-09-27  
#>                                                           3rd Qu.:2015-07-23  
#>                                                           Max.   :2016-02-26  
#>                                                                               
#>     WLVG_OBS         WLVG_SE         LAI_OBS          LAI_SE      
#>  Min.   :  68.0   Min.   :  4.0   Min.   :0.200   Min.   :0.0000  
#>  1st Qu.: 683.6   1st Qu.: 79.2   1st Qu.:1.175   1st Qu.:0.1000  
#>  Median :1665.3   Median :122.4   Median :2.200   Median :0.2000  
#>  Mean   :1713.3   Mean   :152.6   Mean   :2.506   Mean   :0.2365  
#>  3rd Qu.:2512.0   3rd Qu.:219.0   3rd Qu.:3.500   3rd Qu.:0.3250  
#>  Max.   :4261.5   Max.   :523.0   Max.   :6.200   Max.   :0.8000  
#>                                   NA's   :25      NA's   :25      
#>     WLVD_OBS         WLVD_SE          WST_OBS            WST_SE      
#>  Min.   :   0.0   Min.   :  0.00   Min.   :   80.5   Min.   :   3.6  
#>  1st Qu.:  71.3   1st Qu.: 16.40   1st Qu.: 1554.2   1st Qu.: 122.4  
#>  Median : 268.0   Median : 58.00   Median : 4400.5   Median : 236.8  
#>  Mean   : 630.8   Mean   : 86.47   Mean   : 3894.7   Mean   : 365.9  
#>  3rd Qu.:1059.2   3rd Qu.:113.60   3rd Qu.: 5421.8   3rd Qu.: 430.4  
#>  Max.   :2761.2   Max.   :468.00   Max.   :10214.0   Max.   :2927.2  
#>                                                                      
#>     WSO_OBS         WSO_SE          WAGT_OBS          WAGT_SE      
#>  Min.   :   0   Min.   :   0.0   Min.   :  148.5   Min.   :  11.2  
#>  1st Qu.:   0   1st Qu.:   0.0   1st Qu.: 2909.0   1st Qu.: 171.2  
#>  Median :   0   Median :   0.0   Median : 9106.9   Median : 478.0  
#>  Mean   :2139   Mean   : 190.1   Mean   : 8377.4   Mean   : 597.1  
#>  3rd Qu.:4507   3rd Qu.: 295.2   3rd Qu.:13291.2   3rd Qu.: 875.2  
#>  Max.   :8663   Max.   :1361.0   Max.   :24570.7   Max.   :3142.8  
#>                                                                    
#>  NLV_OBS         NLV_SE        NST_OBS         NST_SE         NP_OBS       
#>  Mode:logical   Mode:logical   Mode:logical   Mode:logical   Mode:logical  
#>  NA's:77        NA's:77        NA's:77        NA's:77        NA's:77       
#>                                                                            
#>                                                                            
#>                                                                            
#>                                                                            
#>                                                                            
#>   NP_SE        
#>  Mode:logical  
#>  NA's:77       
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