The L-ALMOND model: a functional-structural virtual tree model of almond tree architectural growth, carbohydrate dynamics over multiple years

DeJong, Theodore M.; Silva, D. Da; Negrón, Claudia; Cieslak, Mikolaj; Prusinkiewicz, Przemysław

doi:10.17660/actahortic.2017.1160.7

Cited by 6 publications

(3 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The total accumulated stem biomass in carbohydrate equivalents per tree in simulated trees growing without water or nutrient stress were very similar to the total harvested biomass of almond trees growing under field conditions in the southern San Joaquin Valley of California. Simulated fruit yields and number of nuts per tree were also similar to what would be expected for comparable aged trees in the field (DeJong et al, 2017).…”

Section: Marchsupporting

confidence: 70%

See 1 more Smart Citation

Simulating fruit tree growth, structure, and physiology using L‐systems

DeJong

2022

Crop Science

View full text Add to dashboard Cite

Simulation modeling of perennial fruit tree growth, structure, and physiology over multiple years is particularly difficult and has lagged behind modeling of other crops because fruit trees are indeterminate organisms that grow over several growing seasons, vary widely among individuals, and have their structures modified by variable pruning practices. Nearly 30 yr of research have been devoted to developing a mechanistic, virtual tree model to simulate peach [Prunus persica (L.) Batsch] fruit tree growth, structure, and physiology. Details of much of this work have been published in several research papers in a variety of journals over a couple decades. The goal of this review is to report on the entire project and provide an overview of the approach we took in such an endeavor. This review contains excerpts of numerous previously published papers and some comments and conclusions about the value of the modeling that has occurred.

show abstract

Section: Marchsupporting

confidence: 70%

“…The most recent development in the L‐PEACH modeling project was to convert the model into an L‐ALMOND model (DeJong et al., 2017) to demonstrate the utility of the approaches used in functional–structural modeling of peach trees for modeling other tree species. Because almond [ Prunus dulcis Mill.…”

Section: Conversion Of L‐peach Into An L‐almond Modelmentioning

confidence: 99%

Simulating fruit tree growth, structure, and physiology using L‐systems

DeJong

2022

Crop Science

View full text Add to dashboard Cite

show abstract

“…Markov models and semi-Markov models are used to statistically assess the transitional probability between two zones [57]. Some of the examples in which Markov's models and semi-markov's is applied in fruit crops are GrapevineXL in grapevine [58], L-ALMOND in almond [59], [60], L-KIWI in Kiwi [61], L-PEACH in peach [30] and MappleT in Apple [62].…”

Section: Aerial Parts Of Perennial Fruit Treesmentioning

confidence: 99%

An Overview of Different Fruit Crop Models in the last 40 Years to Date with Their Main Uses

Shukoor,

Jain,

Maurya

et al. 2023

IJPSS

View full text Add to dashboard Cite

Horticulture is a versatile field which encompasses a plethora of day to day strategic decisions like varietal selection, optimisation of resources, understanding the mechanisms of the phenology, identification of plant invaders both in the micro and macro level, wise and judicious use of plant protectants, yield prediction & assessment, post harvesting & handling, strategic way of understanding the pulse of consumer’s popular demands and efficient way of marketing. Fruit trees are perennial unlike annual vegetable and cereal crops where there is a high prerequisite for efficient modelling of canopy architecture, photosynthesis, nutrient uptake, pest forecasting etc where the ill-effects of climate change are bringing out huge losses in the existing germplasm, annual turnover of the farmers and emergence of unheard pests and diseases. An invincible foresight or preparedness against such vagaries can be brought out by efficient modelling mechanisms combining the physiology, phenology and vital requirements of fruit trees with the interacting ecosystem of the land where it is present. Extrapolating such models from the local level to a general situations always gives fruitful results and it further aids in strengthening the present protocols. With the advancement of machine learning and deep learning in precision agriculture, problems of farmers and orchardists are being solved at a faster pace with the help of sensors in identification of problems and its alleviation using fast and error-free processing at pre-harvesting, harvesting and post-harvesting stages of fruit crops. In fact it is also one of the major concerns among people regarding the complete replacement of human power in the crucial decision support systems for agriculture and farming.

show abstract