Parthenocarpic Fruit Growth Reduces Yield Fluctuation and Blossom-end Rot in Sweet Pepper

Heuvelink, E.; Körner, Oliver

doi:10.1006/anbo.2001.1427

Cited by 68 publications

(54 citation statements)

References 25 publications

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“…This suggests that the cyclic nature of pepper yields is inherent in the pepper biology and the influence of environmental inputs is secondary. In reviewing the irregular patterns of yield for greenhouse sweet peppers, Heuvelink and Korner (2001) attributed flushing to the theory that increasing seed numbers in maturing fruit exerted an inhibitory effect on subsequent fruit set and development. This theory would coincide with our observation that cyclic pepper yields seem to be inherent in pepper biology.…”

Section: Results and Discussion Models To Predict Y1 Yieldsmentioning

confidence: 99%

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Neural network modelling to predict weekly yields of sweet peppers in a commercial greenhouse

Lin¹,

Hill²

2008

Can. J. Plant Sci.

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Lin, W. C. and Hill, B. D. 2008. Neural network modelling to predict weekly yields of sweet peppers in a commercial greenhouse. Can. J. Plant Sci. 88: 531Á536. The production of greenhouse-grown sweet pepper (Capsicum annuum L.) is irregular with a peak-and-valley pattern of weekly yields. We monitored the yields and environment in a commercial greenhouse in British Columbia over six (2000Á2005) growing seasons. Light was defined as cumulative light over the current week, with L_1, L_2, L_3, L_4, L_5 and L_6 representing light over previous weeks. Temperature (AvgT) was defined as the current weekly average of 24-h air temperatures, with T_1, T_2 and T_3 representing temperatures over previous weeks. Inputs were also created for the current weekly yield (Y) and previous weekly yields (Y_1, Y_2, Y_3 and Y_4). Neural network (NN) modelling with up to 21 inputs was used to predict yields 1 wk (Y'1) and 2 wk (Y'2) in advance of the actual fruit harvest. Data for five different years were combined for model training with the year to be predicted held separate as a validation set. The best models used 13 inputs to predict Y'1 with an average R 2 of 0.66 over the 6 yr. Y_4, Y-Y_1, Y_1, L_1, Y, Y_3, Y-Y_3 and wk (of the year) were important inputs. The environmental inputs were of lesser importance, which suggests that the cyclic nature of pepper yields is inherent in the pepper biology. Predicting Y'2 was more difficult with an average R 2 of 0.59 over the 6 yr. NN have good potential for predicting pepper yields.Key words: Capsicum annuum L., flushing, fruit, greenhouse production, neural networks Lin, W. C. et Hill, B. D. 2008. Pre´vision du rendement du poivron dans une serre commerciale par mode´lisation sur re´seau neuronal. Can. J. Plant Sci. 88: 531Á536. La culture du poivron (Capsicum annuum L.) en serre donne des re´sultats irre´guliers avec un rendement hebdomadaire en dents de scie. Les auteurs ont e´tudie´le rendement et l'environnement de cette culture dans une serre commerciale de la Colombie-Britannique durant six saisons ve´ge´tatives (de 2000 a`2005). Pour la lumie`re, les auteurs ont utilise´la luminosite´cumulative de la semaine courante, L_1, L_2, L_3, L_4, L_5 et L_6 correspondant a`cette valeur pour les semaines ante´rieures. La tempe´rature (AvgT) e´tait e´gale a`la moyenne de la tempe´rature ambiante pendant 24 h pour la semaine en cours, T_1, T_2 et T_3 correspondant a`cette valeur pour les semaines ante´rieures. Les auteurs ont aussi cre´e´des intrants pour le rendement de la semaine courante (Y) et de la semaine ante´rieure (Y_1, Y_2, Y_3 et Y_4). La mode´lisation sur re´seau neuronal avec un maximum de 21 parame`tres permet de pre´voir le rendement des poivrons une semaine (Y'1) et deux semaines (Y'2) avant la re´colte proprement dite. Les auteurs ont combine´les donne´es de cinq anne´es pour former le mode`le, l'anne´e pour lesquelles les pre´visions devaient eˆtre calcule´es servant a`la validation. Les meilleurs re´sultats sont obtenus avec 13 parame`tres et le mode`le a pre´vu Y'1 avec ...

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Section: Results and Discussion Models To Predict Y1 Yieldsmentioning

confidence: 99%

“…The production of greenhouse-grown sweet pepper (Capsicum annuum L.) is highly irregular (Heuvelink and Korner 2001) with a peak-and-valley pattern of weekly yields (Heuvelink et al 2004). The exact cause of this ''flushing'' is unknown.…”

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confidence: 99%

Neural network modelling to predict weekly yields of sweet peppers in a commercial greenhouse

Lin¹,

Hill²

2008

Can. J. Plant Sci.

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“…Parthenocarpy is a physiological phenomenon where an ovary grows into a fruit without fertilization (Varoquaux et al, 2000). It has been proposed as a possible solution to reduce yield flushing and to minimize BER in sweet pepper (Heuvelink and Körner, 2001). These authors reported that auxin application on unpollinated flowers of sweet pepper resulted in seedless fruits and a more regular production than in non-treated plants.…”

Section: Introductionmentioning

confidence: 99%

Selection of Sweet Pepper (Capsicum Annuum L.) Genotypes for Parthenocarpic Fruit Growth

Tiwari¹,

Dassen

Heuvelink³

2007

Acta Hortic.

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Yield irregularity and blossom-end-rot are major problems in sweet pepper production, which can be reduced by parthenocarpy. However no commercial parthenocarpic cultivars are available. The purpose of this study was to find parthenocarpic genotype(s) of sweet pepper with the ability to produce good quality fruits without seeds. Eleven genotypes of sweet pepper were studied at normal (20/20°C D/N) and at low night temperature (20/10°C D/N), in two greenhouse compartments from January till May. Fruit length, diameter, fresh and dry weight and number of seeds per fruit were measured. A higher percentage of parthenocarpic fruits was observed for all genotypes at low night temperature compared to normal temperature. Within the genotypes which showed at least 60% parthencarpic fruit growth at low night temperature, two groups were distinguished, which showed a different expression of parthenocarpy in response to the environment. In one set of genotypes (Line 1 and Line 3) high expressivity for parthenocarpy was found irrespective of night temperature. In another set of genotypes (Gen A, Gen B, Gen C, Lamuyo A, Lamuyo B and Bruinsma Wonder), a high level of parthenocarpy was expressed at low night temperature only, which may be due to non-viable pollen at low night temperature. Further evaluation of the latter six genotypes resulted in one genotype (Bruinsma Wonder) for which the absence of seeds only marginally influenced shape and size of fruits. These selected genotypes may eventually lead to an exploitation of parthenocarpy in sweet pepper breeding.

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“…1). No significant effect on sweet pepper yield can be caused by large cyclic fluctuations in fruit set during sweet pepper production, even under controlled and constant climate conditions [Heuvelink andKorner 2001, Del Amor andGómez-López 2009]. Jarosz and Horodko [2004] in greenhouse tomato cultivation in inert media: perlite, keramzite and rockwool also showed no significant effect on the marketable and total yield of tomato fruits.…”

Section: Resultsmentioning

confidence: 99%

The influence of additives to the peat substrate on the yielding and chemical composition of sweet pepper fruits (Capsicum annuum L.) grown in greenhouse

et al. 2017

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The influence of additives to the peat substrate on the yielding and chemical composition of sweet pepper fruits (Capsicum annuum L.) grown in greenhouseWpływ dodatków do substratu torfowego na plon i skład chemiczny owoców papryki (Capsicum annuum L.) uprawianej w szklarniSummary. The aim of this work was to determine the effect of using various additives to the substrate on the yield and quality of sweet pepper fruits grown in greenhouse. In the experiment four objects were used: 1) peat substrate (control object), 2) peat substrate with coconut fiber, 3) peat substrate with an addition of expanded keramzite, and 4) peat substrate with an addition of perlite. The experiment showed no significant effect of additives on the early, marketable and total yield of fruits and on the content of chlorophyll b. Beneficial effects of coconut fiber added to the substrate were found on the fruit quality: dry matter content, soluble sugar and L-ascorbic acid. The additive of perlite to the substrate had a significant effect on chlorophyll a and chlorophyll a : b ratio. Significant differences in the content of the analysed macroelements: Ca, K, Mg and P in fruits were found depending on the type of substrate used.

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Parthenocarpic Fruit Growth Reduces Yield Fluctuation and Blossom-end Rot in Sweet Pepper

Cited by 68 publications

References 25 publications

Neural network modelling to predict weekly yields of sweet peppers in a commercial greenhouse

Neural network modelling to predict weekly yields of sweet peppers in a commercial greenhouse

Selection of Sweet Pepper (Capsicum Annuum L.) Genotypes for Parthenocarpic Fruit Growth

The influence of additives to the peat substrate on the yielding and chemical composition of sweet pepper fruits (Capsicum annuum L.) grown in greenhouse

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