Accurate prediction of vegetable growth will help the growers in planning of cultivation and production under protected facilities. To predict the yield of water dropwort (Oenanthe stolonifera DC.) diurnally, model was developed for predicting fresh w...
Accurate prediction of vegetable growth will help the growers in planning of cultivation and production under protected facilities. To predict the yield of water dropwort (Oenanthe stolonifera DC.) diurnally, model was developed for predicting fresh weight (FW) based on daily photosynthetic photon flux density (PPFD) and average daily temperature (ADT). Various growth parameters were examined to ascertain the allometric relationships with the FW. Dry weight and leaf area index (KAI) up to linear-growth phase had good linear relationships with FW, each showing determination coefficients of greater than 0.96. The maximum radiation use efficiency (maximum RUE, α_max) was found to be 0.0385 ㎏·mol^-1 for the FW of water dropwort. RUE followed beta distribution function in terms of ADT
, (α_ADT=α_max[(39.0-ADT)/15.0][(ADT-7.5)/16.5]^(15.0/16.5))
Minimum, optimum, and maximum temperatures for RUE were estimated as 7.5, 24.0, and 39.0℃, respectively. Therefore, FW was predicted well with the function of FW=0.0385∑[α_ADT(1-e^-KLAI)PPFD].