1.1. Introduction
Postharvest physiology and technology has been key to maintaining and extending the shelf-life of perishables and reducing food losses. However, postharvest losses are still significant and reduction of such losses would be the easiest, less costly, and most effective method instead of increasing food production (Pedreschi et al., 2013a).
Postharvest strategies or technological implementation, such as temperature reduction, modification of the atmosphere, or chemical treatments, are applied. These serve to reduce respiration rates, retard ripening, decrease ethylene production, and consequently retard senescence, prevent dehydration, and extend the shelf-life thus preserving produce quality. These strategies imply that produce are submitted to abiotic stresses and they need to activate different metabolic pathways to cope with these stresses and reach homeostasis to avoid undesirable quality traits that limit produce shelf-life (Pedreschi and Lurie, 2015).
Proteomics studies on fruits and vegetables have increased in recent years (Li et al., 2015; Buts et al., 2014). Proteins play key roles in fruit development, ripening, and senescence and are involved in key metabolic pathways and networks related to resistance to biotic and abiotic stresses. Numerous proteomics studies focused on understanding ripening, development, and senescence of different commodities such as tomato, grapes, citrus, strawberry, peach, papaya, mango, and banana are available and the reader is encouraged to review these papers to gain further insight (Rocco et al., 2006; Kok et al., 2008; Faurobert et al., 2007; Deytieux et al., 2007; Negri et al., 2008; Giribaldi et al., 2010; Katz et al., 2007, 2010; Bianco et al., 2009; Prinsi et al., 2011; Nogueira et al., 2012; Magalhaes Andrade et al., 2012; Torres-Toledo et al., 2012). Proteomic studies focused on microbial/fungal diseases and mechanisms during postharvest have been extensively reported. For example, Buron-Moles et al. (2015) studied the apple defense response to wounding, Penicillium expansum and Penicillium digitarum infection at the proteome and oxi-proteome (protein carbonyl) levels. The proteins Mal d 1.03A, Mal d 1.03E, and EF-Tu were specifically induced in response to P. digitarum infection. In addition, 27 oxidized proteins were identified as reactive oxygen species (ROS)-sensitive targets and were suggested to play a leading role in the response against biotic and abiotic stresses. Comparative proteomics and functional analysis have revealed that defense-related proteins, energy metabolism, and antioxidant-related proteins play key roles in fruits in response to storage conditions and elicitor treatments. For more studies on microbial/fungal diseases using proteomics approaches, the reader is referred to Gonzalez-Fernandez and Jorrin-Novo (2012), Shah et al. (2012), Chan (2013), and Taylor et al. (2008) and for a complete review of the mechanisms related to protein level changes in both the host and pathogen, the reader is referred to Chan (2013).
Numerous proteomics studies reported up to date have focused on understanding either desirable or undesirable postharvest quality traits (Urbany et al., 2011; Pedreschi et al., 2007; Nilo et al., 2010; Minas et al., 2016; Miyasaka et al., 2016) to find potential initial quality markers or early stage biomarkers of such quality traits. But these postharvest quality traits are strongly influenced by preharvest abiotic stresses (e.g., temperature, radiation, light exposure, dehydration) and enhanced or buffered by postharvest abiotic stresses. Thus, this book review focuses upon mainly commercially important fruits and vegetables with focus on how abiotic stresses (temperature, dehydration, atmosphere modification, light and chemical exposure, ozone treatments, etc.) influence certain produce quality traits or characteristics.
1.2. Factors Affecting Postharvest Quality
The type of stress and characteristics (severity, exposure, duration) and the characteristics of the different produce (genotype, maturity stage, organ type) will influence the response of the different produce to acclimate and withstand the different imposed abiotic stresses. It has been extensively reported that preharvest factors (e.g., growing conditions and crop management) and the stage of development influence the response of the different produce to abiotic stresses (Fig. 1.1) and thus on the postharvest phenotype obtained.
Some studies using other omics platforms have been reported on this topic but proteomics studies are still limited. Abdi et al. (2002) carried out a 2D-PAGE proteomics experiment for determining optimal harvest of stone fruits. Commercial harvest indices are skin color, firmness, soluble solids, and size. These parameters are affected not only by the cultivar but also by growing conditions and seasonal climatic factors. The authors proposed to use four allergenic proteins that were synthesized in the fruit a few days before the optimal harvest time in plums, peaches, and nectarines as a harvest index for stone fruits. Ye and Dilley (1992) and Dilley et al. (1995) by using a gel-based approach proposed 1-amino cyclopropane carboxylate-oxidase (ACO) as a biomarker for apple harvest. Other omics approaches employing transcriptomics and metabolomics have proposed potential initial quality markers for Hass avocado ripening heterogeneity and potatoes cold sweetening (Pedreschi et al., 2013b, 2014). Recently, Buts et al. (2016) studied at the proteome level using a gel-free approach, an apple browning disorder in the cultivar Braeburn related to preharvest application of calcium, potassium, and triazole as fertilizers. Calcium and potassium have been previously reported to reduce the incidence of this disorder while triazole displayed the opposite effect. Results from this study revealed that calcium and triazole application resulted in significant effects at the proteome level with 29 and 63 differentially expressed proteins after the treatment application. Key antioxidant enzymes were correlated with calcium fertilization and respiration and ethylene-related proteins were correlated with the triazole treatment. The authors, in addition, postulated that an early proteomics imprint (at harvest) could be used as an early decision tool of the postharvest performance of a batch to devel...