California has been among the top global producers of dried grapes (raisins) for more than a century. For most of this time, California raisin grapes were harvested by hand and dried in the vineyard on trays ( Fidelibus, 2014). However, the traditional tray-drying method was the most labour-intensive seasonal farm activity in North America ( Calvin & Martin, 2010). The declining availability and increasing cost of labour made tray drying unsustainable for most growers, and intense competition from foreign producers and better financial returns for other crops have all contributed to a substantial decline in the California raisin industry ( Fidelibus, 2014; Calvin et al., 2022). As domestic production decreased, raisin prices in the USA have become increasingly dependent on Turkish production and exports (Calvin et al., 2022). To remain competitive in a global marketplace, raisin growers, like other fruit and vegetable producers in the USA, must produce crops more efficiently with fewer labour inputs (Charlton et al., 2025).

To address this problem, most growers have implemented one of two partially mechanised production systems: “continuous tray” (CT) or “dry-on-vine” (DOV) ( Fidelibus, 2014). In CT systems, a harvest machine shakes the berries from the vines and deposits them onto tray paper via a tray-laying device ( Berg & Striegler, 2002). After drying, a pickup machine retrieves the raisin trays. Many growers have transitioned to a CT system because it is compatible with existing conventional ‘Thompson Seedless’ raisin vineyards. However, CT is not an ideal solution, as the cane-pruned Thompson Seedless variety is not amenable to mechanised pruning, and tray-drying requires sunlit drying space between rows, which constrains trellis height and row spacing, thereby limiting yield potential. The DOV system was a further advancement in raisin mechanisation ( Berg & Striegler, 2002). The DOV system consists of severing grapevine canes bearing clusters of mature fruit, thus separating the clusters from the permanent vine structures, and causing the fruit to DOV ( May & Kerridge, 1967). When dry, a mechanical harvester collects the raisins ( Fidelibus, 2014). The DOV process takes longer than tray-drying due to the lower temperatures in the trellis as compared to on the ground. Thus, DOV is best suited for vineyards with early-ripening grapevine varieties on expansive trellis systems to ensure timely drying and capitalise on the fact that sunlit row middles are not needed for drying ( Fidelibus, 2014).

Studer (2000) observed that the berries of some early ripening table grape varieties, under favourable drying conditions, will naturally DOV (NDOV), without the need for cane-cutting. An NDOV raisin variety with fruitful basal buds would permit mechanisation of harvesting and winter pruning, which would amount to an unprecedented level of mechanisation for raisin grapes ( Studer, 2000). Toward that end, Sunpreme, the first NDOV raisin variety, was released in 2015 ( Ramming, 2015). Sunpreme’s NDOV trait has the potential to transform raisin production, but it also has a notable preharvest fruit drop (shatter) problem, although the impact of preharvest shatter on yield potential has not been determined. Further, factors affecting preharvest shatter or drying of NDOV varieties have received little attention, although Ledbetter and Marini (2016) noted that the berries of NDOV varieties may not dry well in years with particularly heavy crops or poor drying weather.

Production data for Sunpreme are limited. A preliminary study reported that yield averaged approximately 10.8 tons/ha for vines trained to a double-T trellis with 0.91 m and 0.61 m cross-arms and found cane-pruned vines to be as productive as spur-pruned vines ( Ramming, 2015; as cited in Ledbetter & Marini, 2016). Subsequent testing with a single cross-arm trellis confirmed that pruning style had little effect on raisin quality, so Ledbetter and Marini (2016) concluded that the variety should be spur-pruned, if not mechanically pruned. Ledbetter and Marini (2016) also showed that deficit irrigation improved raisin drying, but reduced raisin quality. Aside from the preliminary research on pruning and irrigation cited above, there are no other published studies on NDOV cultural practices, so there is a lack of practical insight on trellises, rootstocks, and nutritional needs for NDOV raisin grapes. Quadrilateral trellis systems, which were used for the initial testing of Sunpreme, can be managed with machines, but currently available vineyard mechanisation equipment works best with single curtain trellis systems ( Kurtural & Fidelibus, 2021), on which NDOV varieties have not previously been tested.

Likewise, initial testing was conducted on own-rooted vines, but rootstocks are needed in the San Joaquin Valley (SJV) to protect against damaging soil pests. Freedom is the most widely used rootstock for raisin grapes in the SJV, but sudden-vine decline has recently become a serious problem for grapevines on that stock (Eskalen et al., 2022), so growers are increasingly selecting other stocks such as 1103P. Rootstock choice can substantially affect vine mineral nutrition, vegetative growth, berry size, and yield in the SJV (Migicovsky et al., 2021), and is therefore an important consideration for NDOV vineyards.

Nitrogen (N) fertiliser is commonly applied to raisin vineyards across the SJV ( Christensen & Peacock, 2000). Vines grafted onto certain rootstocks, including Freedom, have lower N requirements than own-rooted vines, possibly due to the rootstock’s more vigorous and explorative root system ( Christensen & Peacock, 2000). Sunpreme vineyards should have higher N needs than traditional Thompson Seedless vineyards due to their higher yield potential, but excess N could promote vegetative growth and delay fruit ripening ( Christensen & Peacock, 2000; Verdenal et al., 2021), both of which would be undesirable in an NDOV vineyard. Grapevines carrying heavy crop loads are also prone to potassium (K) deficiency, which can delay ripening. Rootstocks differ in their nutrient uptake characteristics; for instance, Freedom is exceptional in accumulating K compared with rootstocks such as 1103P. However, rootstocks with Vitis champinii parentage, including Freedom, are also prone to Zn deficiency ( Christensen & Peacock, 2000). Consequently, the best rootstock for NDOV varieties in the SJV might depend on trellis design and overall nutritional status.

Petioles have traditionally served as the standard tissue for monitoring grapevine nutrition in California, especially for raisin grapes ( Schreiner & Scagel, 2017). However, several mineral nutrients exhibit greater variability in petioles than in blades, suggesting that blades may be a better tissue for nutrient testing ( Schreiner & Scagel, 2017; Romero et al., 2013). Moreover, there is growing interest in developing remote-sensing technologies for vineyard nutrition monitoring. Such technologies leverage the principle that leaf biochemical composition influences radiative properties such that remotely sensed spectral data can be used to estimate leaf mineral nutrient content (Farajpoor et al., 2025). For these reasons, tissue test results from both petioles and leaf blades may be useful reference values for growers managing this relatively new variety.

Accordingly, the objectives of this study were to determine the effects of trellis, rootstock, and N fertiliser application rate on tissue nutrient test results and on NDOV raisin grape performance, including preharvest fruit drop, yield, and quality.

The experiment was conducted in a vineyard at the University of California Kearney Agricultural Research and Extension Centre, in Parlier, California, USA. The vineyard was planted in late August 2019, with a split-split plot design, where the main-plot factor was trellis (bilateral or quadrilateral), the sub-plot factor was rootstock (own-rooted, Freedom, or 1103P), and the sub-sub plot factor was annual nitrogen application rate (45 or 90 kg/ha). The vineyard was divided into four blocks, each consisting of six consecutive vine rows which were oriented east-west, with 43 vines/row, a 2 m within-row spacing, and a 3.5 m between-row spacing. Each block was divided into two three-row main plots which were randomly assigned to receive a bilateral or quadrilateral trellis system. The bilateral trellis consisted of steel posts at every vine space, each of which extended vertically 1.65 m above the vineyard floor, and to which a single cordon wire was affixed, approximately 5 cm from the tip of the stake. The quadrilateral trellis system consisted of steel posts at every other vine space (alternating with aluminium stakes), with one 0.56 m wide cross arm secured to the steel stakes at 1.40 m above the vineyard floor.

Within each main-plot, entire vine-rows were randomly assigned to each sub-plot factor and were thus planted with either own-rooted vines, or vines grafted to Freedom, or 1103P rootstock. Vines were irrigated through October 2019 and trained and suckered as needed. In December 2019, vines were pruned to a trunk terminating just above the cordon wires. In 2020, all vines were supplied with the equivalent of 22.4 kg N/ha as Ca(NO ₃) ₂, applied through the drip irrigation system in spring and summer. Vine training was completed during this period, and the canes to be retained as cordons were established throughout the vineyard.

Vines were pruned in late January 2021, with two canes retained per vine on the bilateral trellis, and four canes retained per vine on the quadrilateral trellis. In early spring 2021, the two N fertiliser application rate sub-sub plots within each vine row were established (45 or 90 kg N/ha) and maintained for the duration of the study. Each sub-sub plot consisted of 18 adjacent vines, with two to three guard vines between each sub-sub plot and/or at the end of the row. Nitrogen was applied as a mixture of Ca(NO ₃) ₂ and (NH ₄) ₂SO ₄, with each annual application consisting of two equal amounts of N (1/2 of the annual allotment), with the first made approximately 1 month after budbreak, and the second at fruit set.

In the dormant seasons preceding the 2022 and 2023 seasons, the vines were spur-pruned by hand, leaving one two-bud spur at each position on vines with quadrilateral cordons, and two two-bud spurs (where possible) at each spur position on vines with bilateral cordons, in an attempt to match the number of nodes per vine. During the growing seasons, the CropManage web tool ( https://cropmanage.ucanr.edu/) was used to help schedule irrigations, with a 70 % deficit through veraison, as recommended by Peacock et al. (2000). After veraison, an additional deficit was sometimes needed to help control shoot growth, and a pressure chamber was used to monitor mid-day leaf water potential periodically. Approximately 655 mm of water was applied each season, as is typical of raisin grape vineyards with a similar canopy size in the San Joaquin Valley (Peacock et al., 2000). Besides N, all vines were fertigated every year with potassium (K) thiosulfate between bloom and veraison, applying approximately 11.2 to 16.81 kg of K/ha each season. Additionally, in late November 2022, 113 kg of sulfate of potash (48.2 kg actual K) per ha was top-dressed to a 1 m-wide band beneath the vines in each row. No other fertilisers were applied during the study. During each growing season, various herbicides, fungicides, and insecticides were applied to control common grape pests in this region (Bettiga, 2013).

Paired samples of petioles and leaf blades were collected from vines throughout each plot at bloom and veraison, at sampling dates listed in Table 1. Samples at bloom were collected opposite clusters, whereas samples at veraison were collected from positions having mature, recently expanded leaf blades. After separating the blades from the petioles, the tissues were rinsed in deionised water, surface-dried using a centrifugal spinner, placed in paper bags, and dried to a constant weight in a forced-air oven at 55 ℃. Dried samples were ground in a mill and submitted to a commercial laboratory (Valley Tech Ag Laboratory Services, Tulare, CA) to determine macro- and micronutrient content using standard methods (Gavlak et al., 2003).

In late July of each year, replicated berry samples were collected from vines in each plot following standard methods described previously (Fidelibus et al., 2008). Briefly, samples consisting of 100 berries were taken from clusters selected at random from vines within each treatment replicate. The samples were weighed, and average berry weight was calculated. The berries were then crushed to express juice, which was centrifuged to remove insoluble solids. Soluble solids were measured with a hand-held, temperature-compensating digital refractometer (Palette 101; Atago, Farmingdale, NY, USA). Titratable acidity of the juice was determined by titration with 0.133 N NaOH to an 8.20 endpoint using an automatic titrator (855 robotic titrator; Metrohm USA Inc., Riverview, FL).

Each year in July, sections of weed mats measuring approximately 0.91 m × 1.14 m were installed beneath randomly selected vines in each plot to catch any abscising berries. The corner of each mat was stapled to wooden stakes which were driven into the ground beneath the vines such that mats were raised approximately 14 cm above the soil surface. After installation, each mat covered a sufficient area of soil beneath vines on either trellis to collect any berries that abscised from a 1 m length of row. The mats were observed one or a few times a week until harvest, and any grapes on the mats were collected, placed into paper bags, and dried. Raisins were harvested when moisture levels were judged to be ≤ 16 %, or the onset of poor drying weather was anticipated, whichever came first. Within a few days of harvest, any remaining berries/raisins on the mats were collected and dried, and then all the raisins in the vine canopy directly above each weed mat were harvested, collected into paper bags, weighed, and then placed in a forced-air oven and dried to a constant weight. The fresh weight of raisins picked from the vine canopies above the weed mats was included in the harvest yield determinations for the plots they came from, and the dry weight of the same raisins was used to determine percent preharvest fruit drop, which was calculated as the ratio of the dry weight of grapes/raisins which fell onto the mats divided by the dry weight of those raisins plus the dry weight of the raisins picked from the vines directly above the mats. The dried raisins picked from above the weed mats were frozen in liquid N to embrittle them, and then they were ground into a fine powder with a mortar and pestle while frozen. Subsamples of dried and finely ground raisins were sealed in plastic vials and submitted to a commercial laboratory for determination of macro- and micronutrient content. The amount of mineral nutrients in a ton of fresh raisins was determined by multiplying the estimated dry matter (0 % moisture) of a ton of raisins by the nutrient concentration (percentage) of the raisins.

At harvest, all remaining clusters of raisins were hand-picked and weighed. Approximately 2 kg of raisins from each plot were collected, manually destemmed, and submitted to the USDA Processed Products Division (Fresno, CA) for moisture and quality determination following official methods (USDA, 2016). Raisins were graded using airstream sorters to determine Grade A and B ("B and better") and substandard. Yield comparisons were made after adjusting raisin weights to 14% moisture (Fidelibus et al., 2008). Yield per hectare was calculated by multiplying the average yield per vine in each plot by the number of vines per hectare.

For statistical analysis, the experimental design was considered a split-split-split plot, with year as the main-plot factor, trellis (high single-wire versus T-trellis) as the subplot factor (replicated four times), rootstock (own-rooted, Freedom, or 1103P) as the sub-sub plot factor, and annual N application rate (45 or 90 kg N/ha) as the sub-sub-sub plot factor. Statistical analyses were performed using SAS (SAS 9.4, SAS Institute, Cary, NC, USA).

Financial support was provided by USDA-NIFA Specialty Crop Research Initiative Award No. 2020-51181-32159.