A Case Study of Fruit Set in Sweet Pepper
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Towards stochastic simulation of crop yield: a case study of fruit set in sweet pepper Ageeth Maaike Wubs Thesis committee Thesis supervisor Prof. dr. ir. L.F.M. Marcelis Professor of Crop Production in Low-energy Greenhouses, Wageningen University Thesis co-supervisors: Dr. ir. E. Heuvelink Associate professor, Horticultural Supply Chains Group, Wageningen University Dr. L. Hemerik Associate professor, Biometris, department of Mathematical and Statistical Methods, Wageningen University Other members: Prof. dr. ir. P.C. Struik, Wageningen University Prof. dr. ir. G. van Straten, Wageningen University Dr. O. Körner, AgroTech, Taastrup, Denmark Dr. P. Haccou, Leiden University This research was conducted under the auspices of the C.T. de Wit Graduate School for Production Ecology and Resource Conservation. ii Towards stochastic simulation of crop yield: a case study of fruit set in sweet pepper Ageeth Maaike Wubs Thesis submitted in fulfilment of the requirements for the degree of doctor at Wageningen University by the authority of the Rector Magnificus Prof. dr. M.J. Kropff, in the presence of the Thesis Committee appointed by the Academic Board to be defended in public on Wednesday 6 October 2010 at 1.30 p.m. in the Aula. iii Ageeth Maaike Wubs Towards stochastic simulation of crop yield: a case study of fruit set in sweet pepper Thesis, Wageningen University, Wageningen, the Netherlands (2010) With references, summaries in English and Dutch ISBN 978-90-8585-699-3 iv Abstract Crop growth simulation models are widely used in research and education, and their use in commercial practice is increasing. Usually these models are deterministic: one set of input values always gives the same output of the model. In reality, however, variation exists between plants of the same crop. A simulation model taking this variation into account is therefore more realistic. The aim of this thesis is to introduce a stochastic component into a dynamic crop simulation model. As case study, fruit set in sweet pepper was used, because large variation in fruit set between the plants exists. Competition with fast growing fruits causes abortion of flowers and young fruits, which results in periods with high and low fruit set, and consequently periods of high and low fruit yield. A literature review showed that most factors influencing fruit abortion can be expressed in the terms source and sink strength. Source strength is the supply of assimilates; a higher source strength increases fruit set. Source strength takes into account leaf area, radiation, and CO2 level and temperature. Sink strength is the demand for assimilates of the fruits and vegetative parts. It is quantified by the potential growth rate, i.e. the growth rate under non-limiting assimilate supply. Assimilate demand of the fruits depends on their number, age, and cultivar. If the total fruit sink strength of a plant is low, fruit set is high. Vulnerable for abortion were very small buds, buds close to anthesis and flowers and young fruits up to 14 days after anthesis. An experiment with six Capsicum cultivars with fruit sizes ranging between 20 and 205g fresh weight showed that variation in weekly fruit yield is highly correlated with variation in weekly fruit set. Fruit yield patterns resembled fruit set patterns, with a lag time being equal to the average fruit growth duration. Further investigation showed that the cultivars not only differed in sink strength of the individual fruits, but also that the source-sink ratio above which fruit set occurred was higher in cultivars with larger fruits. In the second half of the thesis, flower and fruit abortion was modelled. Survival analysis was used as the method to derive the abortion function. Source and sink strength were used as the factors influencing abortion. Their effect on the probability of abortion per day was non-linear: at high values of source and sink strength an increase did not further decrease or increase the probability of abortion, respectively. Flowers on the side shoots turned out to have a higher probability of abortion than flowers on the main shoot. Most flowers and young fruits aborted around 100°Cd after anthesis. The obtained function was used in a crop simulation model for sweet pepper. After calibration the model was able to simulate the observed fruit set pattern, although fruit abortion was not properly simulated when low source strength was combined with high sink strength. Validation with three independent data sets gave reasonable to good results. Survival analysis proved to be a good method for introducing stochasticity in crop simulation models. A case study with constant source strength showed asynchronisation of fruit set between the plants, indicating that fluctuations in source strength are an important factor causing synchronisation between individual plants. Key words: fruit abortion, fruit set, Capsicum, survival analysis, crop simulation model, source strength, sink strength, temperature. v vi Table of contents Chapter 1 General introduction 1 Chapter 2 Abortion of reproductive organs in sweet pepper (Capsicum annuum L.): a review 9 Chapter 3 Quantifying growth of sweet pepper fruits non-destructively 23 Chapter 4 Fruit Set and Yield Patterns in Six Capsicum Cultivars 39 Chapter 5 Genetic differences in fruit set patterns are determined by differences in fruit sink strength and a source:sink threshold for fruit set 51 Chapter 6 Survival analysis as a tool to quantify effects of factors on abortion rates of reproductive organs 67 Chapter 7 Stochastic simulation of flower and fruit abortion with a mechanistic model 85 Chapter 8 General discussion 111 References 119 Summary 135 Samenvatting 139 Dankwoord 143 Curriculum Vitae 146 List of publications 147 PE&RC PhD Education Certificate 148 Funding 149 vii viii General introduction Chapter 1 General introduction In this first chapter the background is given for the research presented in this thesis. The first part of this chapter focuses on the general principles of crop simulation models, and how fruit set is simulated in these models. In particular, attention is paid to models with a stochastic component. The second part focuses on variation in fruit set, especially on variation in fruit set in sweet pepper. Both parts lead to the aim of the thesis, given at the end of this chapter. Crop growth simulation models General description of simulated processes Crop growth simulation models are widely used in research. One of their functions is to help researchers answer questions which might otherwise require extensive experiments (Gary et al., 1998). Growers are also becoming more and more interested in the use of crop growth simulation models, for example for making decisions regarding crop management based on model calculations (Heuvelink and Kierkels, 2007). Leaf area is an important variable in crop growth models, as the leaves absorb radiation and CO2 resulting in photosynthesis, which is the basis for crop growth. Leaf area expansion depends on temperature and/or assimilate supply (Goudriaan and Van Laar, 1994). Based on leaf area, radiation levels, temperature and in some cases CO2 concentration, the daily growth of the whole crop is calculated. The growth of the individual organs or groups of similar organs can be calculated in different ways. In crops with determinate growth (where growth of the plants stops when the floral reproductive structure has been formed), the daily growth of the different organs is often calculated as a fraction of the daily growth of the total plant. This fraction varies with the developmental stage of the crop (Goudriaan and Van Laar, 1994). In crops with indeterminate growth (where new flowers are formed continuously) a more dynamic function for distribution of dry matter between the different organs is desirable. This is usually done based on the concept of sink strengths (Marcelis, 1996). The sink strength is the demand for assimilates which is often quantified by the potential growth rate. The total sink strength of the plant is the sum of the sink strengths of individual organs. The daily growth of one organ is calculated by its share in the total sink strength multiplied by the daily growth of the plant. Simulation of fruit abortion Plants with an indeterminate growth pattern can show strong fluctuations in fruit abortion over time. This makes it difficult to model abortion of flowers and fruit. Consequently, the abortion process is a less well-developed part of simulation models for these crops. Abortion of flowers and fruit is often modelled based on the balance between supply and demand of assimilates, the so-called source-sink ratio. In the tomato growth model TOMGRO (Bertin and Gary, 1993; Heuvelink and Bertin, 1994), fruit abortion increases 1 Chapter 1 linearly with decreasing source-sink ratio from 0% at a source-sink ratio of 0.42 up to 70% abortion at a source-sink ratio of zero (Bertin and Gary, 1993). Marcelis (1994) used the source-sink ratio and temperature to determine the number of young non-aborting fruit in cucumber. Schepers et al. (2006) simulated the abortion of sweet pepper fruit based on their fruit weight and the assimilate supply: above a certain threshold, a fruit would not abort any more. Buwalda et al. (2006) simulated fruit set in sweet pepper based on an empirical function where the difference between source and sink strength determined the number of newly set fruit. In the crop simulation model INTKAM, the number of flowers and young fruits a plant can sustain depends linearly on the gross assimilation of the plant, the total fruit sink strength and the temperature (Marcelis et al., 2006). If the number of young flowers and fruits is higher than the plants can sustain, the youngest ones abort. Simulation with variation Even when crop models simulate abortion of individual organs, it is assumed that each organ follows the same deterministic rule in relation to the factors influencing abortion.