# Effect of Selected _Trichoderma_ Strains and Metabolites on Olive Drupes
## 4 Discussion  
Today, it is considered a priority to limit pesticides against phytopathogenic agents or replace them with products of biological origin. The use of mycopparasitic fungi, particularly those belonging to the genus _Trichoderma_, has met considerable success [11]. The world market of biopharmaceuticals proposes over 50 bioformulates containing _Trichoderma_ strains as active ingredients [51]. The considerable achievement of _Trichoderma_ fungi in agriculture is due to their suppression of pathogenic species, both terricolous and foliar, among the most harmful, such as those belonging to the genera _Fusarium_, _Sclerotinia_, _Botrytis_, and _Pythium_[52]. Microbial inocula to promote plant development and/or control phytopathogenic agents is still not very widespread in tree crops. Few studies evaluated the effect of beneficial microorganisms on the fitness of the olive tree and provided helpful information for the use of bioformulates in the open field. The present work aims to evaluate the effects of the field applications of _Trichoderma_ spp. strains and some of their metabolites on young olive trees' drupes weight and nutraceutical content contained therein. The olive is the most representative tree in Italy, with both historical and productive significance. There are three types of olives on the market: olive for oil production, olive for  
Figure 4: Luteolin content in drupes. Samples are indicated by treatments with _Trichoderma_ strains (THI, GV41, T22, M10, and KV906) or secondary metabolites (HA and 6 PP). Values are the means of three replicates \(\pm\) SE. Different letters indicate significant differences (\(p<0.05\)). Figure 3: Oleuropein content in drupes. Samples are indicated by treatments with _Trichoderma_ strains (THI, GV41, T22, M10, and KV906) or secondary metabolites (HA and 6 PP). Values are the means of three replicates \(\pm\) SE. Different letters indicate significant differences (\(p<0.05\)). the table, and dual-use. Fruit size, oil content flesh, and weight/pit weight ratio determine the inclusion in the product classes. Olives for oil production have an average weight below 3, table-use have an average weight higher than 5, dual-use between 3 and 5 [53]. Extensive research has been conducted on multiple species to understand the mechanisms that control fruit size [54]. Environmental and genetic factors affect the fruits' growth potential [55]. In particular, the water volume and the type of irrigation used for cultivation are noteworthy [56]. Water deficit results in high reactive oxygen species (ROS) (e.g., hydrogen peroxide, hydroxyl radical superoxide anion, and singlet oxygen) [57]. ROS can damage DNA, lipids, and protein, thereby affecting plants' metabolism [58]. Plants react to ROS, making enzymes with different biological activities (e.g., catalase, ascorbate peroxidase, superoxide dismutase, monodehydroase reductase, dehydroroscorbate reductase, guaiocal peroxidase, and glutathione reductase) [59] and primary or secondary metabolites (e.g., polyols, soluble sugars, alkaloids, free amino acids, and phenols) [60]. In this work, all treatments (excluding M10 and KV906) enhanced drupe weight, probably due to _Trichoderma_ strains' ability to induce root growth, preserve nutritional uptake, and interfere with phenolics' productions [61]. The diverse response to bio-treatments was probably linked to the different abilities of each strain and metabolite to interact with the plant's secondary defense mechanisms [15]. The variation in phenolics (variety and levels) was tested using targeted and untargeted metabolomics to evaluate the interaction of _Trichoderma_ spp. and metabolites with the plant defense mechanism. Targeted metabolomics uses analytical techniques and suitable multivariate statistical analysis (MSA) tools to evaluate some metabolites simultaneously [62]. The untargeted approach determines unknown and known metabolic changes based on data-independent acquisition (DIA). DIA methods make complex fragmentation spectra.