Domenico Ronga*1
, Federica Caradonia1, Fulvia Rizza2, Franz-W. Badeck2, Enrico Francia1, Marianna Pasquariello1,
Giuseppe Montevecchi1, Luca Laviano1, Justyna Milc1, Nicola Pecchioni1
1Department of Life Sciences, University of Modena and Reggio Emilia, Via Amendola, n. 2, 42122 Reggio Emilia (RE), Italy.
2Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria - Centro di ricerca per la Genomica e la Bioinformatica (CREA-GB), Via San
Protaso, 302, 29017, Fiorenzuola d'Arda, Italy.
*domenico.ronga@unimore.it
Abstract
Changes in agronomic traits of processing tomato cultivated in the past decades might give useful information to develop breeding programs in order to face future food security challenges. The present study investigated six different processing tomato genotypes selected among the most widely cultivated over the past 60 years in Southern Europe. The aim was to assess morphological and physiological traits associated to yield improvement, studying the changes that have occurred until nowadays to highlight some of these that could contribute to improve the sustainability of the crop. Several agronomic trait data were collected in open field using currently management. The most modern genotype H3402 resulted as expected more suitable to the mechanized management, and showed distinct assemblies of traits such as higher harvest index and number of fruits vs. the old variety Pearson. However, no significant differences were observed between the two in marketable yield per square meter and solid soluble content.
Keywords: processing tomato, physiology, morphology, biomass, quality, breeding
Parole chiave: pomodoro da industria, fisiologia, morfologia, biomassa, qualità, miglioramento gentico Introduction
Ranking second after potato among horticultural crops, tomato (Solanum lycopersicum L.) yield in Europe has increased by 200% from 1961 until nowadays (FAOSTAT, 2017). This increase might be attributed both to advancements in agricultural practices and to plant breeding (Barrios-Masias and Jackson, 2014; Foolad, 2007; Grandillo et al., 1999; van der Ploeg et al., 2007). The main characters improved by breeders in processing tomato were: tolerance to biotic and abiotic stresses, plant growth habit, fruit firmness and jointless fruits (Foolad, 2007). For fresh market tomato, van der Ploeg et al. (2007) and Higashide and Heuvelink (2009) reported that, under current management, modern genotypes show an important increase of yield in comparison to old cultivars released starting from 1950s, and this increase was due to higher light use efficiency. Barrios-Masias and Jackson (2014) compared eight processing tomato genotypes released in California in the past 80 years reporting that the modern cultivars have accumulated phenological traits (i.e. early flowering and concentrated fruit set) together with morphological ones (e.g. smaller canopy and low vegetative biomass), correlated with gains in nitrogen concentration in biomass and photosynthetic rates. On the other hand, to the author’s knowledge, no such studies are available for Southern Europe, another important area of tomato cultivation. Hence, this study investigated six different processing tomato genotypes, released and cultivated over the past 60 years, with the final aim to investigate agronomic, morphological and physiological changes that occurred in tomato genotypes.
Materials and Methods
Six processing tomato genotypes – Pearson released in the 1950s, C33 released in the 1970s, H2274 released in 1975, E6203 released in 1984, Brigade released in 1989 and H3402 released in 2002 – were evaluated in an open field trial at ISI Sementi S.p.A. (Fidenza, Italy), during the spring-summer 2013 using current management techniques. Six-weeks old tomato seedlings were transplanted at the end of April in single row (1.40 m spacing between rows), with a final density of 3.6 plants m-2 for all genotypes tested in each year. The experimental design was a randomized complete block design with
three replicates. A total of 166 Kg ha-1 of N, 84 Kg ha-1 of P, 214 Kg ha-1 of K were applied; phosphorus and potassium
were supplied before transplanting while nitrogen was applied 33% at transplanting and 67% from full flowering to fruit set and seed ripening. Irrigation water, distributed with a drip system, was determined on the base of the total water lost by evapotranspiration calculated according the formula: ETc = ETo × Kc, where ETo is the reference evapotranspiration and Kc was the crop coefficient of tomato (Allen et al., 1998). The 100% ETc was restored when 40% of total available water in the soil was depleted in agreement with the evapotranspiration method of Doorenbos and Pruitt (1977). During the trial
about 4500 m3 ha-1 of irrigation water was applied. Weeds and pests were controlled according to the conventional
management rules of Emilia Romagna Region, Italy.
Growth and physiological parameters were assessed every 2 weeks starting from one month after transplant by sampling 2 plants per plot and then converting values per square meter. A total of 21 traits were recorded at four timings: 0 (transplanting), 1 (full flowering), 2 (fruit ripening), 3 (fruit harvest). Number and angle of leaves, number of stems, number of flowers and fruits and heights of plants were recorded for the morphological characterization. Physiological traits were evaluated in term of estimation of chlorophyll content (Chl), flavonoid (Flv) and nitrogen status (NBI). Chlorophyll (a/b) (ChlMASS) was measured also by specific spectrophotometric assay (V-550 UV-VIS, Jasco Inc, Easton, USA). The
physiological parameters were measured on the youngest fully expanded leaf using Dualex 4 Scientific (Dx4) (FORCE-A, Orsay, France). At harvest time, leaf area index, marketable yield, total fresh biomass, dry weight of leaves, stems, fruits and harvest index, were recorded along with a series of quality-related parameters: pH, °Brix, total carotenoid and polyphenol content. Leaf area was measured using subsamples of fresh leaves that were run through the leaf area meter LI- 3000A (LI-COR Inc., Nebraska, USA).
Analysis of variance (ANOVA) was performed with GenStat 17.0th edition on data recorded at harvest time. Means were compared using Duncan’s test at the 5% level. In addition, a Principal Component Analysis (PCA) model (Jackson, 1991; Wold et al., 1987) was used for biplot generation on all data recorded during the cropping season.
Results and Discussion
Fruits were harvested at mature stage at the end of August 2013. As reported in Table 1, H2204 was the cultivar with the highest leaves dry weight and stem dry weight. C33 and E6203 reported the highest marketable yield and harvest index, the latter trait was showed also by the most modern cultivar (H3402). As regard fruit quality, Brigade showed the highest value of solid soluble content (°Brix). These results are partially in agreement with the previous work of Higashide and Heuvelink (2009) on fresh market tomato, which showed an increase of yield per year of release, an increase of fruit and total dry weight, and harvest index in modern genotypes. These differences were probably due to the different genotypes investigated. In fact, Higashide and Heuvelink (2009) studied genotypes suitable for greenhouse cultivation, with indeterminate growth habit, while in the present study were assessed genotypes suitable for the cultivation in open field characterized by traits for mechanized harvest.
Tab. 1: Traits recorded at harvest time. LDW = leaves dry weight; SDW = stem dry weight; FDW = fruit dry weight; TDW
= total dry weight; LAI = leaf area index; MY = marketable yield; HI = harvest index; ns = not significant. Values within
columns followed by different letters are significantly different at P<0.05.
Tab.1: Parametri rilevati alla raccolta. LDW = peso secco delle foglie; SDW = peso secco dei fusti; FDW = peso secco dei frutti; TDW = peso secco totale; LAI = indice di area fogliare; MY = produzione commerciale; HI = indice di raccolta; ns = non significativo. Valori all’interno delle colonne seguiti da lettere differenti sono statisticamente significativi a P<0.05.
Cultivar Pearson 418.6 b 425.4 ab 462.7 ns 1776.3 ns 3.0 ns 9435.2 ab 36.1 abc 6.0 ab C33 528.2 ab 302.5 ab 605.2 ns 1435.8 ns 4.2 ns 13398.6 a 42.6 a 5.2 b H2274 887.6 a 712.3 a 423.2 ns 2023.1 ns 3.7 ns 9681.7 ab 22.8 b 5.1 b E6203 621.6 ab 338.6 ab 653.5 ns 1613.7 ns 3.7 ns 13043.7 a 42.2 a 5.4 b Brigade 389.9 b 75.3 b 438.2 ns 903.4 ns 3.1 ns 7877.5 b 36.3 abc 6.9 a H3402 414.1 b 208.3 ab 638.8 ns 1261.1 ns 3.0 ns 11525.4 ab 50.3 a 5.8 ab Average 543.3 343.7 536.9 1502.2 3.5 10827.0 38.4 5.8 °Brix LAI (m m-2) HI LDW (g m-2) SDW (g m-2) FDW (g m-2) TDW (g m-2) MY (g m-2)
All measured traits were also analyzed using Principal Component Analysis (PCA) to determine putative associations between the investigated traits and the six genotypes cultivated over the past decades (Figure 1). The relative contribution of the various physiological traits might give some useful information that might be used in future breeding programs to design new élite genotypes. The contributions of the first two PCs were 42.12% and 23.84% and their sum explained 65.96% of the variation. The negative side of PC1, included E6203 (rel. 1984) and H3402 (rel. 2002), two genotypes with higher values of ChlMASS and leaf, stem and total dry weight at transplant, high number of leaves at full flowering time, high number of fruits
recorded at each timing and high value of fruit dry weight at harvest time.
The positive side of PC1 included Pearson (rel. 1950s) and H2274 (rel. 1975) with high value of ChlDX and heightat each
timing; high values of flower number, FlvDX and number of leaves at fruit ripening; while at harvest time reported the high
Brigade showed intermediate values ranging among the other investigated genotypes. Our result regarding phenological and morphological traits highlighted higher harvest index and number of fruit, smaller canopies and lower total dry weight, in the most modern genotype (H3402) respect to the oldest one (Pearson) confirming results reported by Barrios-Masias and Jackson (2014) who studied processing tomato genotypes released over the past 80 years and suitable for Californian environments.
Fig. 1: Biplots of PCA results. Physiological and morphological traits are in relation with the tested genotypes. 0, 1, 2 and 3 = measures recorded at transplanting, full flowering, fruit ripening and fruit maturity.
Red diamonds = cultivars studied; grey circles = traits investigated
NL = number of leaves; AL = angle of leaves; NS = number of stems; NFL = number of flowers; NFR = number of fruits; ChlDX = chlorophyll content; FlvDX = flavonoid content; NBIDX = nitrogen balance index; ChlMASS = chlorophyll a/b; LDW = leaves dry weight; SDW = stem dry weight; FDW = fruit dray weight; TDW = total dry weight; MY = marketable yield; LAI = leaf area index; HI = harvest index; Bx = °Brix; CAR = total carotenoids; POL = total polyphenols; BTH =
Brix t ha-1; H = plant height; SLA= specific leaf area.
Fig. 1: Biplot dei risultatti della PCA. I parametri fisiologici e morfologici sono in relazione con i genotipi testati.
0, 1, 2 e 3 = misure rilevate al trapianto, alla piena fioritura, adll’ingrossamento delle bacche e alla maturazione dei frutti. Rombi rossi= cultivar studiate; cerchi grigi = parametri investigati.
NL = numero delle foglie; AL = angolo delle foglie; NS = numero dei fusti; NFL = numero dei fiori; NFR = numero dei fiori; ChlDX = contenuto in clorofilla; FlvDX = contenuto in flavonoidi; NBIDX = indice di bilancio del’azoto; ChlMASS = clorofilla a/b; LDW = peso secco foglie; SDW = peso secco fusti; FDW = peso secco frutti; TDW = peso secco totale; MY = produzione commerciale; LAI =leaf area index; HI = harvest index; Bx = °Brix; CAR = carotenoidi totali; POL =
polifenoli totali; BTH= Brix t ha-1;H= altezza piante; SLA= specific leaf area.
Conclusions
In view of the global climate change, providing sufficient amounts of food and quality is impellent. Therefore, the knowledge of traits that might lead to an increase in tomato production and quality is useful to design the plant ideotype for future breeding programs. This work focused on changes that occurred in tomato putatively influencing the production in the last 60 years in Southern Europe. The change from indeterminate to determinate growth habit and other traits are highlighted in the most modern genotype such as smaller canopies, lower leaf biomass and higher harvest index. In the near future, more attention might be considered on angle of leaves, and °Brix, which are important traits to improve the production but also the quality of fruit. These results might provide information to examine new suites of traits that might drive future breeding and crop improvement reflecting the demands of future scenarios.
Acknowledgements
We wish to thanks Dr. P. Passeri, Dr. Massimiliano Beretta and ISI Sementi Spa (Fidenza, PR, Italy) for providing the seeds of cultivars and the experimental field used in this study.
References
Allen R.G., Pereira L.S., Raes D., Smith M., 1998. Crop evapotranspiration: Guidelines for computing crop water requirements. Irrigation and Drainage, 56. FAO, Rome, Italy.
Barrios-Masias F.H., Jackson L.E., 2014. California processing tomatoes: Morphological, physiological and phenological traits associated with crop improvement during the last 80 years. European Journal of Agronomy, 53: 45-55.
Doorenbos, J., Pruitt W.O., 1977. Guidelines for prediction of crop water requirements. Irrigation and Drainage, 24, FAO, Rome, Italy, 144.
FAOSTAT, 2017. http://www.fao.org/faostat/en/#home
Foolad M.R., 2007. Genome Mapping and Molecular Breeding of Tomato. International Journal of Plant Genomics. doi:10.1155/2007/64358.
Grandillo S., Zamir D., Tanksley S.D., 1999. Genetic improvement of processing tomatoes: A 20 years perspective. Euphytica, 110: 85-97.
Higashide T., Heuvelink E., 2009. Physiological and Morphological Changes Over the Past 50 Years in Yield Components in Tomato. The Journal of the American Society for Horticultural Science, 134(4): 460-465.
Jackson J. E., 1991. A Users Guide to Principal Components. Nr. 1. Wiley & Sons Ltd, New York, USA.
van der Ploeg A., van der Meer M., Heuvelink E., 2007. Breeding for more energy efficient greenhouse tomato: Past and future perspectives. Euphytica, 158:129-138.
Wold S., Esbensen K., Geladi P., 1987: Principal component analysis. Chemometrics and Intelligent Laboratory Systems, 2: 37–52.