Survival Analysis of Flower and Fruit Abortion in Sweet Pepper

Abstract

In order to obtain a crop growth model that can simulate inter-and intra-plant variation in fruit set, fruit abortion times in sweet pepper were analysed by means of survival analysis. Survival analysis is a statistical technique dealing with the timing of events. The Cox proportional hazards model estimates the instantaneous baseline probability of abortion per time (hazard rate), given that the fruit has not aborted yet. It also estimates the effect of explanatory factors (covariates) on the abortion rate. Two important factors known to influence abortion in sweet pepper are the supply and demand for assimilates (source and sink strength, respectively). A plant density experiment was analysed, as density influences plant source and indirectly also sink strength. Flowering as well as abortion or harvest dates were recorded for all individual flowers and fruits. LAI was measured to calculate the source strength with a photosynthesis-based simulation model. Empirical curves showed that survival of flowers and fruits (per plant) was higher at 1.6 plants/m 2 than at 3.1 or 4.6 plants/m 2 . Plant density, source strength and source/sink ratio all correlated with the treatment plant density, but source/sink ratio explained most of the variation in the data in a Cox proportional hazards model. Averaging the source/sink ratio over seven days gave the best fit. Adding the position within the node (main or side branch) improved the fit; flowers from the side branch had a higher probability of abortion per unit time than flowers from the main branch. The susceptibility for fruit abortion differed among plants. The baseline hazard rate indicated that between 0 and 13 days after anthesis, flowers were most susceptible for abortion. INTRODUCTIONIn general, process-based crop growth models simulate the growth of average plants. However, in reality a lot of variation exists in growth and development between plants and between similar organs within one plant. A crop growth model taking this variation into account, for example by using a stochastic function, can predict variations in crop growth more realistically. Because the output of such a model is different for every model run, confidence intervals for expected yield or crop growth can be obtained. One of the possibilities to include this variation is by implementing results of a survival analysis into a crop growth model. Survival analysis is a statistical technique for the analysis of timing of events (Kleinbaum, 1995).

Modelling Dry Matter Production and Partitioning in Sweet Pepper

“…Furthermore, individual plants show quite some variation and there seems to be variation among individual flowers and fruits. Current research aims at obtaining a crop growth model that can also simulate inter-and intra-plant variation in fruit set by using the statistical technique of survival analysis (Wubs et al, 2007).…”

Plants make smart decisions in complex environments

“…There is extensive scientific literature on the physiology of abortion of reproductive structures, particularly on the role played by genes regulation, hormones, carbohydrates, source-sink ratio, and environmental conditions. [51][52][53][54] Seed abortion was chosen to illustrate the benefit/cost analysis influencing plant's decisions, and the same reasoning may be employed for the abscission and abortion of all reproductive structures (flowers, pods, young fruits, and seed).…”

“…56,61 Once the seed initiates Phase 2, it can no longer be aborted. 53,57,[61][62][63][64] The number of seeds to be produced is also a decision made by the plant, and it can vary in a wide range. 51,54,65,66 The plant assesses how much reserve (assimilated carbon and nutrients) it has stored, decides on the amount reserves that will be allocated to seed (or for reproduction in the broad sense), and then it defines how many seeds it can produce.…”

“…51,54,65,66 The plant assesses how much reserve (assimilated carbon and nutrients) it has stored, decides on the amount reserves that will be allocated to seed (or for reproduction in the broad sense), and then it defines how many seeds it can produce. 48,53,67,68 The concept of benefit/cost is employed along Phase 1. The plant has many benefits at a low cost by initiating seeds in excess of its actual capacity (Figure 2), and that is the decision often made in most plant species.…”

Pengaruh Jumlah Cabang per Tanaman terhadap Pertumbuhan dan Hasil Tiga Varietas Paprika

“…Pada sistem tiga cabang per tanaman, tanaman paprika dibiarkan dahulu untuk membentuk tanaman dengan cabang yang kuat sebelum tanaman tersebut menghasilkan buah, sedangkan pada sistem dua cabang per tanaman, tanaman paprika lebih cepat menghasilkan buah. Pembentukan buah (fruit set) pada tanaman paprika berkorelasi positif dengan kekuatan sumber (source strength) dan berkorelasi negatif dengan kekuatan penyimpanan (sink strength), sehingga berkorelasi positif dengan nisbah sumber:penyimpanan (source:sink ratio) (Heuvelink et al 2002, Marcelis et al 2004, Wubs et al 2007.…”