Modeling the Effect of Temperature on the Flower Development Rate of Hybrid Impatiens

Vargo, Mary; Faust, James E.

doi:10.21273/horttech04919-21

Cited by 2 publications

(7 citation statements)

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“…The average daily temperature (ADT), daily minimum and maximum temperatures, and daily light integral (DLI) at the GH and HT locations were measured using WatchDog 2400 Mini Stations (Spectrum Technologies, Aurora, IL, USA) placed just above the plant canopy. ADT refers to the daily 24 h temperature average, which has been shown to be highly correlated with plant development rates [16,17,20,[24][25][26][27].…”

Section: Methodsmentioning

confidence: 99%

“…Varying the length of cold storage and the environmental conditions during forcing, particularly air temperature, can be manipulated as a strategy for scheduling crops so that they finish (i.e., harvest) during important and off-season market weeks [12][13][14][15]. Scheduling crops requires the ability to predict the amount of time needed for production, which involves identifying how quickly plants progress (i.e., the rate of progress) towards desired stages of plant development [16,17]. The time needed to reach an important developmental stage, for example, the number of days to flowering or fruiting (DTF), is converted to a rate by calculating the reciprocal of the DTF (e.g., 1/DTF).…”

Section: Introductionmentioning

confidence: 99%

“…The time needed to reach an important developmental stage, for example, the number of days to flowering or fruiting (DTF), is converted to a rate by calculating the reciprocal of the DTF (e.g., 1/DTF). The influence of environmental factors, like temperature and light, on plant development rates can be quantified using mathematical functions [17]. These types of models can be used as decision-support tools, for example, for long-cane blackberry and raspberry, allowing growers to select the date at which dormant long-canes should be forced in a greenhouse or high tunnel and manipulate the production temperatures to schedule crops' off-season harvesting.…”

Section: Introductionmentioning

confidence: 99%

“…The rate of progress towards a development event, such as flowering or fruiting, is mostly a function of average daily temperature (or ADT) [18,19], as shown in Figure 2. Plant development rates increase from zero to a maximum value when the ADT increases from a base temperature to an optimum temperature for plant growth, respectively [20- Scheduling crops requires the ability to predict the amount of time needed for production, which involves identifying how quickly plants progress (i.e., the rate of progress) towards desired stages of plant development [16,17]. The time needed to reach an important developmental stage, for example, the number of days to flowering or fruiting (DTF), is converted to a rate by calculating the reciprocal of the DTF (e.g., 1/DTF).…”

Section: Introductionmentioning

confidence: 99%

“…The optimum temperature is the point where the rate of plant development is the highest, after which plant development rates decrease as the ADT exceeds the optimum temperature, and the critical temperature is where plant development ceases because of heat stress. Models describing plant development rates as a function of ADT have been developed for many species grown in soilless substrates and protected environments and allow users to predict the time needed for crop production based on anticipated temperatures [16,17]. Measuring ADT over time is also used to calculate the accumulation of heat units (e.g., thermal time or degree days or hours), wherein heat units are commonly used to estimate the developmental stage or forecast the date at which a plant will reach a predetermined developmental stage, for many field-grown specialty crops, including blackberry [18].…”

Section: Introductionmentioning

confidence: 99%

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Forcing Temperature Effects on Plant Development for Containerized Blackberry Grown Using Long-Cane Techniques

Dickson,

Machesney,

Henderson

2023

Horticulturae

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Dormant containerized blackberry plants grown as long canes are forced into protected environments, such as plastic tunnels or greenhouses, to schedule harvesting for important market weeks. The time needed to produce a crop is mainly a function of temperature. In this study, the objectives were to quantify the effects of temperature on plant development rates for long-cane blackberry and develop simple models predicting the time from forcing dormant plants to first open flowers and ripe fruit as a function of average daily temperature (ADT). The crop time and ADT at the first-flower and -fruit stages were measured for the cultivars ‘Loch Ness’, ‘Osage’, ‘Ponca’, and ‘Prime-Ark® 45′ grown as long canes during a greenhouse and high-tunnel experiment, and the days to flowering and fruiting were converted to rates by calculating the reciprocal. Nonlinear models relating flowering and fruiting rates to ADT were developed for each cultivar using a combination of the experimental data and base (6 °C), optimum (25 °C), and maximum (35 °C) temperature parameters derived from a previous blackberry heat unit study. Model accuracy was evaluated by comparing the predicted to observed times to first flower and fruit per cultivar. Average daily temperature was shown to have a main influence on crop timing, as shown by a strongly positive and near 1:1 relationship between predicted and observed days to flowering/fruiting. However, there was significant variability depending on the cultivar and model accuracy within ±7 days, ranging from 50% (‘Prime-Ark® 45) to 90% (‘Loch Ness’) for the flower models and from 60% (‘Prime-Ark® 45) to 100% (‘Loch Ness’) for the fruit models. To the best of our knowledge, this study is the first to characterize the relationship between temperature and crop timing for soilless long-cane blackberry, and it provides a framework for modeling temperature effects on crop timing for these systems. The authors discuss further methods to improve model accuracy and precision for commercial use. These models can also be used for general training purposes to help educate growers on how temperature influences crop scheduling during long-cane blackberry production.

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