Temperatura base inferior, soma térmica e fenologia de cultivares de videira e quivizeiro

Anzanello, Rafael; Christo, Mariane Castanho de

doi:10.5965/223811711832019313

Cited by 4 publications

(6 citation statements)

References 18 publications

(15 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thermal availability has a direct effect on plant growth and development. High temperatures accelerate the plant metabolism, while low temperatures reduce the plant growth and prolong the cycle of plants (Anzanello & De Christo, 2019;Proietti et al, 2022), especially in regions with marked annual thermal oscillation, such as in southern Brazil.…”

Section: Resultsmentioning

confidence: 99%

“…The growth and development of lisianthus are affected by different meteorological factors, such as temperature variation, solar radiation, seed vernalization, photoperiod, and light conditions (Oh, 2015). Temperature is one of the main agrometeorological parameters that directly influences the phenology of this species, as it is intrinsically associated with the photosynthetic rate, affecting the plant growth and development (Vaid et al, 2014;Freitas et al, 2017;Anzanello & De Christo, 2019). As temperature increases (up to a point), photosynthesis, transpiration, and respiration increase.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Base temperature estimates for lisianthus cultivars grown in different planting seasons

Höhn,

Peil,

Marchi

et al. 2023

Pesq. agropec. bras.

View full text Add to dashboard Cite

The objective of this work was to determine the base temperature of six lisianthus cultivars, grown at seven planting seasons in the municipality of Capão do Leão, in the state of Rio Grande do Sul, Brazil. The following cultivars were evaluated: DBL Echo Blue, Robella 2 Pink, Excalibur White, Excalibur 2 Blue Picotee, DBL Echo Champagne, and Arena III Red. Base temperature was determined from the air temperature data collected daily, in each planting season, fusing the lowest variability and development ratio methods. The base temperature for lisianthus cultivars is between 14.0 and 15.0ºC, by the lowest variability method, and between 13.9 and 15.0ºC by the development ratio method. The highest thermal accumulation was obseerved in the second planting season (from 11/23/2017 to 02/22/2018) for all cultivars, and lower air temperatures during the growing season resulted in longer production cycles. In the seven planting seasons, the highest base temperature is 15.0ºC, obtained for cultivar Arena III Red, and the is 14°C, for all lisianthus cultivars.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Base temperature estimates for lisianthus cultivars grown in different planting seasons

Höhn,

Peil,

Marchi

et al. 2023

Pesq. agropec. bras.

View full text Add to dashboard Cite

show abstract

“…For example, air temperature drives seedling development, influencing processes related to leaf appearance (Fagundes et al, 2023; Ferreira et al, 2019; Freitas et al, 2017; Freitas & Martins, 2019; F. B. Martins et al, 2022; F. B. Martins, Ferreira, et al, 2023; L. V. D. Silva et al, 2020). Exposure to optimal temperatures accelerates metabolic processes and leaf appearance, while supra‐optimal (or sub‐) temperatures reduce the emission of new leaves and seedling development speed (Anzanello & Christo, 2019; Fagundes et al, 2023; Hatfield & Prueger, 2015). Despite the dependence on meteorological conditions, the scarce existing studies focus on describing the phenological scale, disregarding the relationship between weather conditions, particularly air temperature.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, the relationship between phenological stages and the thermal requirement of the seedling phase are important steps in predicting (or projecting) phenological events (e.g. emergence, leaf emergence, budding, flowering, fruiting, and ripening), and assessing climate impacts on seedling production (Anzanello & Christo, 2019; Cavalcante et al, 2020; Kishore et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Phenological description and thermal time requirements for the seedling phase of three Brazilian native forest species

Martins,

Ferreira,

Xavier

et al. 2023

Annals of Applied Biology

View full text Add to dashboard Cite

Understanding the phenological stages and thermal requirements of the seedling phase of forest species is crucial for sustainable nursery management. This study proposed an adaptation of a phenological scale based on the basic Biologische Bundesanstalt, Bundessortenamt, and Chemical industry, associated with the thermal requirement to describe the phenological stages during the seedling phase of three forest species: Cybistax antisyphilitica, Libidibia ferrea, and Platycyamus regnellii. The phenological scale of C. antisyphilitica and L. ferrea was defined and described through 22 seedling development stages ranging from dry seed to 20th visible leaf emitted on the main stem (from 00 to 120) and P. regnellii for 12 leaf development stages, from dry seed to 10th visible leaf emitted on the main stem (from 00 to 110). In addition, the duration (days) and thermal time (°C day) were determined for each seedling development stage. C. antisyphilitica needs to accumulate more energy (and days) to finish the seedling phase (1551.9°C day or 261 days) compared to L. ferrea (1127°C day or 175 days) and P. regnellii (1109.7°C day or 193 days). However, the three forest species exhibit similar energy demands throughout most stages of seedling development, except code 09–12 for C. antisyphilitica. This study provides important information for optimizing silvicultural techniques, evaluating the response of temperature on phenological stages, and assessing the impacts of global warming on forest seedling development.

show abstract

Prediction of Harvest Time of Apple Trees: An RNN-Based Approach

et al. 2022

View full text Add to dashboard Cite

In the field of agricultural research, Machine Learning (ML) has been used to increase agricultural productivity and minimize its environmental impact, proving to be an essential technique to support decision making. Accurate harvest time prediction is a challenge for fruit production in a sustainable manner, which could eventually reduce food waste. Linear models have been used to estimate period duration; however, they present variability when used to estimate the chronological time of apple tree stages. This study proposes the PredHarv model, which is a machine learning model that uses Recurrent Neural Networks (RNN) to predict the start date of the apple harvest, given the weather conditions related to the temperature expected for the period. Predictions are made from the phenological phase of the beginning of flowering, using a multivariate approach, based on the time series of phenology and meteorological data. The computational model contributes to anticipating information about the harvest date, enabling the grower to better plan activities, avoiding costs, and consequently improving productivity. We developed a prototype of the model and performed experiments with real datasets from agricultural institutions. We evaluated the metrics, and the results obtained in evaluation scenarios demonstrate that the model is efficient, has good generalizability, and is capable of improving the accuracy of the prediction results.

show abstract

Temperatura base inferior, soma térmica e fenologia de cultivares de videira e quivizeiro

Cited by 4 publications

References 18 publications

Base temperature estimates for lisianthus cultivars grown in different planting seasons

Base temperature estimates for lisianthus cultivars grown in different planting seasons

Phenological description and thermal time requirements for the seedling phase of three Brazilian native forest species

Prediction of Harvest Time of Apple Trees: An RNN-Based Approach

Contact Info

Product

Resources

About