The impact of non-structural carbohydrates (nsc) concentration on yield in prunus dulcis, pistacia vera, and juglans regia

ABSTRACT Successful yield in orchards is the culmination of a series of events that start with plants entering dormancy with adequate energy reserves (non-structural carbohydrates; NSC).

These NSC are responsible for the maintenance of activities during dormancy and extending onto the period of activeness. Using multi-year yield information and monthly NSC content in twigs,

we show that high levels of carbohydrate in _Prunus dulcis_, _Pistachio vera_, and _Juglans regia_ during the winter months are indeed associated with high yield, while high levels of the

NSC in late summer often correlate with low yield. An evaluation of monthly NSC level importance on yield revealed that for _P. dulcis_ high levels in February were a good predictor of yield

and that low levels throughout summer were associated with high yield. In _P. vera_, high levels of NSC in December were best predictors of yield. _J. regia_ exhibited peculiar patterns;

while high pre-budbreak reserves were associated with high yields they only played a minor role in explaining crop, the most important months for predicting yields were June and July.

Results suggest that NSC levels can serve as good predictors of orchard yield potential and should be monitored to inform orchard management. SIMILAR CONTENT BEING VIEWED BY OTHERS WATER USE

EFFICIENCY (WUE) AND NUTRIENT CONCENTRATION OF SELECTED FODDER RADISH (_RAPHANUS SATIVUS_ L.) GENOTYPES FOR SUSTAINABLE DIETS Article Open access 28 December 2024 GRASS PEA DUAL PURPOSE DRY

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VARIABILITY IN WEATHER CONDITIONS IN THE LAST TWO DECADES IN LEBANON Article Open access 24 March 2024 INTRODUCTION _“path to literary perfection—small alliteration”_ JO Perennials are

characterized by their persistence across seasonal cycles, including recurring periods of dormancy and activity, that may be intermittently punctuated by biotic and abiotic disturbances. As

such, they must accommodate both short and long-term fluctuations in energy supply and demand1,2,3,4. The nonstructural carbohydrates (NSC) reserve pool in trees, mostly consisting of

soluble sugars and starch, constitutes the primary resource-supply for energetic disparities3,4. Short-term variability typically results from the day/night cycle wherein metabolic processes

continuously draw energy from NSC reserves which are all the while replenished by the daily photosynthetic activity5. Long-term variability can result from either periods of drought,

forcing plants to keep stomata closed (days–weeks), or from seasonal shifts like dormancy when photosynthetic activity is relatively absent (summer–winter). Thus, the survival of perennial

species depends on their ability to accumulate adequate NSC reserves to meet resource demands during any period in which photosynthetic output is absent or lacking. Furthermore, not only are

sufficient NSC reserves critical for supplementing energy deficiencies but a growing body of evidence suggests that whole-tree NSC reserve levels/status play an important role in sustaining

and synchronizing certain phenological progressions. NSC reserves, specifically those present when approaching the end of the season/dormancy, can affect all aspects of tree physiology

including effective bloom, spring growth, and ultimately yield. The level of NSC in twigs, in particular, seems to be the most variable yet the most indicative of whole tree storage status3

and is of major importance in terms of energy supply for flower development and during the initial phases of vegetative bud growth in species like _Prunus dulcis_, _Pistacia vera_, and

_Juglans regia_1,6. Additionally, there is increasing evidence suggesting that conversions between NSC forms, soluble sugars and starches, may potentially serve as a ‘dormancy clock’6.

Hence, the timing and synchrony of bloom is strongly impacted by disturbances especially to the NSC accumulation and dispersion that flank dormancy7,8. Surprisingly, despite the importance

of NSC activity in providing protection against adverse weather conditions through dormancy and in influencing the timing and synchrony of bloom, little attention has been given to how trees

physiologically prepare for this quintessential period of quiescence6,7,9. The amount of reserves needed to maintain dormancy and a healthy growth resumption (bloom/leafing) can be variable

and not easily predicted. The build-up of pre-dormancy reserves may be subject to changing abiotic and biotic conditions, growth, and reproductive activity during the active season3

especially in alternate bearing species like _P. vera_. Additionally, not only is the NSC reservoir contingent upon the active season but the length and conditions of the dormant period

itself can also vary from year-to-year, further affecting the amount of reserves readily available to sustain phenological transitions. The unpredictable nature of the local climate combined

with the selection for yield maximization most likely enforce the need to store more NSC reserves in domesticated plants than what is required for the average dormancy period in most

undomesticated perennials10,11. While the accumulation of reserves is often seen as a byproduct of an excess of carbohydrates, mounting evidence suggests that it may actually be a sink that

actively competes with growth and reproduction rather than merely a passive process12,13. To their undomesticated counterparts, this ‘excess’ might provide a competitive advantage in which

long-term survival is promoted over current vegetative growth and reproductive capacity (yield). However, in domesticated fruit and nut species this may instead shift to promoting short-term

gains in reproductive capacity in lieu of long-term NSC reserve formation. This, in turn, potentially makes selected varieties potentially more susceptible to the negative impacts of

unexpected changes in dormancy conditions and reduces their resilience to additional stresses. Finally, as a healthy and synchronous bloom is a prerequisite for pollination and fruit set,

any changes to NSC content and its forms as affected by weather, biological stress or management can result in significant yield variation. Furthermore, since NSC levels and their form can

affect a range of physiological activities, it is important to ask if and when NSC content has the greatest impact on tree productivity and if it is always better to assure high NSC content

to generate high yields. Therefore, to answer these questions, we used multi-year observations of NSC content in twigs of _P. dulcis_, _P. vera_, and _J. regia_ and combined them with

reported yields for over 300 orchards located across the Central Valley, CA, USA. MATERIALS AND METHODS Using a Citizen Science approach, growers across the entire Central Valley of

California sent samples of current-season twigs of _Prunus dulcis_ (Mill. D.A Webb), _Pistacia vera_ L. and _Juglans regia_ L. (Fig. 1). The study complies with local and national

guidelines. The carbohydrate data set used in this study spans from September 2016 to August 2019 with yield data for the 2017–2019 period. Out of over 590 orchards participating in the NSC

study, we selected the orchards from which growers shared yield information for at least one year during the 2017–2019 period. This resulted in 132 _P. dulcis_, 122 _P. vera_, and 84 _J.

regia_ orchards used in the presented analysis. We encouraged growers to collect samples once a month, however frequency and participation level varied over time and therefore the data sets

varied from month to month. Specific details of sample collection and handling were described previously1. Briefly, a unified protocol for sample collection required that one current season

twig from three trees per orchard be cut at the base where the current season’s wood met last year’s wood. The bark from the lower 10 cm of the twig was removed using a razor blade. Both the

bark and the wood of the three twigs were put in a paper envelope and mailed to the laboratory for NSC analysis. Buds were excluded from the samples. The integrity of the NSC content over

shipping time was tested to assure the quality of the results1. Upon arrival, samples were put in the dryer for 48 h at 75 °C. The bark and wood were chopped into small < 1 mm pieces

separately and ~ 100 mg of each was ground into a fine powder (~ 1 µm) using a ball grinder (MiniBeadbeater-96, Glen Mills Inc., NJ). To analyze for soluble sugar and starch content, we used

the previously described protocol14 with modifications to use smaller sample sizes15. Specifically, 25 mg of powder per sample was placed in 1.5 mL tubes. Tubes were then treated with 1 mL

of sodium acetate buffer (0.2 M, pH 5.5), vortexed, and incubated in a 70 °C water bath for 15 min and centrifuged (10 min at 21,000_g_). 50 µL of supernatant was extracted and diluted in

ultra-pure (UP) water (1:20, v:v) and vortexed. Soluble sugar content was quantified from diluted supernatant tubes using an anthrone/sulfuric acid colorizing reagent (0.1% (m:v) in 98%

sulfuric acid) and reading absorbance at 620 nm in a spectrophotometer. The remaining centrifuged tubes containing the pellet and buffer were used for starch quantification. To extract the

starch, the tubes were boiled at 100 °C for 10 min to allow starch gelatinization, and let sit for 20 min at room temperature (22 °C). Once cooled, 100 µL of amyglucosidase (7 units per mL,

Sigma-Aldrich) and 100 µL amylase (0.7 units per mL, Sigma-Aldrich) were added to the tubes and incubated for 4 h at 37 °C in a rotating incubator. Samples were then centrifuged (10 min at

21,000_g_). Tubes were then centrifuged and 50 µL of supernatant was extracted and diluted in 1 mL of ultra-pure (UP) water (1:20, v:v) and vortexed. Total soluble sugar content was analyzed

using the same method described above. Starch content was determined by subtracting the original from the post-digestion soluble sugar content. All samples were plated onto 96-well plates.

To account for any procedural variability (chemicals, timing, pipetting, temperature, etc.), each plate contained a glucose standard curve (4 wells per plate) and wood/bark standard tissue

samples with known soluble sugar and starch contents (4 wells of each per plate) that were concurrently undergoing all steps in the same chemical analysis. The wood/bark standard tissue is a

sample from a homogenous mix of several thousand ground samples leftover from a 2016 preliminary part of the study1. To calculate the coefficient of correlation (r) between yield and

carbohydrate content for each of the 12 months preceding harvest (September till August) we used the ‘cor’ function using the Pearson method (R-core). A linear model Yield = ß0 + ß1 × 

ConcentrationNSC type (lm, R-core) was used to estimate the slope parameter (ß1; yield change in kg ha−1 in response to an increase of NSC concentration by 1 mg g−1 of tissue). To determine

the most important months, for each carbohydrate type, in predicting the observed yields we used the Random Forest Regressor in PyCaret (Python; PyCaret.org. PyCaret, April 2020, URL

https://pycaret.org/about. PyCaret version 2.3). The native function ‘feature importances’, in which ‘months’ were assigned as features, was used to indicate which months were the most

important predictor of yield. RESULTS From post-harvest (September) till harvest (August), NSC concentrations in twigs not only show seasonal variation1 but are also characterized by high

variation within each month of the year in all three species (_P. dulcis_, _P. vera_, and _J. regia_; to access raw NSC data visit http://zlab-carb-observatory.herokuapp.com/). Due to the

seasonal variation in NSC content, calculation of the coefficient of correlation between NSC content and yield was performed separately for each month. In general, the analysis revealed that

the coefficients of correlation between NSC concentrations and yield were positive and significant (at p-value < 0.1) during mid-winter (January and February) in all three species (Table

1; Figs. 2, 3, 4). Moreover, _P. dulcis_ (almond) was characterized by the presence of multiple periods of significant negative correlations between NSC content and yield; during the active

period (April to July), highly significant negative correlations before harvest (August), and following harvest in September. Soluble sugar concentration in the bark was only weakly

correlated with yield, while total NSC concentration and NSC concentration in wood was significantly correlated in 5 or 6 months during the year preceding harvest (Fig. 2). _P. vera_

(pistachio) was characterized by significant positive correlations between concentrations of NSC and yield over the period from post-harvest till the end of dormancy (September till March).

Specifically, starch content, in wood and bark, was the main driver behind these positive correlations. During the active period spanning from April till July, NSC contents were not

significantly correlated with the current-year yield. A shift to negative correlations occurred in August (before harvest) when total NSC, NSC in bark, and starch in bark showed negative

correlations with yield. Interestingly, starch content in wood and bark as well as the total content of NSC was most correlated with yield across all months, while soluble sugar

concentration in wood remained uniformly non-correlated to yield through the entire season (Fig. 3). Out of the three analyzed species, NSC concentrations in _J. regia_ (walnut) were the

least correlated with yield. Only during the late dormancy period (February–March), the content of NSC and their forms were positively correlated with yield. Unlike in both other species, no

significant negative correlations between NSC and yield were observed in _J. regia_ (Fig. 4). Each type of carbohydrate (NSC total, NSC in wood, NSC in bark, starch in wood, starch in bark,

soluble sugars in wood, and soluble sugars in bark) was independently analyzed and the relative importance of each month’s content as the predictor of yield was determined using the Random

Forest Regressor algorithm (PyCaret’s Regression Module with the split between training and test group of 0.7 and 0.3 respectively; Figs. 5, 6, 7). The positive or the negative impact of NSC

concentrations on yield was assigned using the sign of coefficient of correlation for that month (Table 1). In _P. dulcis_, NSC content in February was the most important positive feature

contributing to yield, while NSC concentration in August was the most important negative feature in predicting yield (Fig. 5). In _P. vera_, NSC concentrations in December was the most

important positive feature in predicting yield, while NSC concentrations in August was the most important negative indicators predicting high yield (Fig. 6). In _J. regia_, NSC concentration

in July was the most important positive indicator for yield followed by May concentrations, while the concentration in June was the most important negative feature in predicting yield (Fig.

 7). DISCUSSION The two main goals of the presented work were (1) to test for the presence of correlations between NSC concentration in twigs of nut trees and orchards’ yields and (2) to

determine the months at which carbohydrate concentration were the best predictors of realized yield. In general, several correlations were significant (Table 1), the coefficient of

correlation (r) ranged from maximum positive correlations of 0.42, 0.63, and 0.52 and negative correlations of − 0.44, − 0.36, and − 0.36 for _P. dulcis_, _P. vera_, and _J. regia_,

respectively. Typically, winter (dormancy) NSC concentration was positively correlated with yield, while the summer (active period) NSC concentration was negatively correlated with yield.

Thus, more is not always better. In fact, the apparent exhaustion of NSC just prior to harvest can be linked to high yield, in which case, less is better. The presence of such correlations

underlines the importance of monitoring NSC reserves for enhancing yield success. The inverse relationship between yield and summer NSC suggests that yield comes at the expense of NSC

reserve formation. Nevertheless, the positive correlation in the fall and winter requires that NSC reserves be replenished during the short postharvest period, prior to senescence, to assure

adequate reserves for bloom. If NSC reserves are not replenished, a lower yield may be expected and may help explain the presence of alternate bearing at either the whole-tree or orchard

level in the case of _P. vera_16 or at the twig level seen in _P. dulcis_17. Interestingly, despite the general trends mentioned above, there were large differences in the magnitude and

temporal patterns of the positive and negative impacts of high NSC levels on yield among the studied species. In _P. vera,_ NSC levels were almost always positively correlated with yield

from September through June (i.e. through the post-harvest, dormancy period, bloom, and vegetative part of the season). Out of all the months however, December NSC concentration was the most

important positive predictor of yield, this was true in all of its studied forms and locations (NSC total, NSC in wood, NSC in bark, starch in wood, starch in bark, soluble sugars in wood

and soluble sugars in bark). NSC concentration was only negatively correlated with yield in the short period preceding fruit maturation (August). The low levels of August NSC associated with

high yields, suggest that reserve exhaustion during this period was correlated with a high accumulation of nut biomass. This pattern may reflect sink dominance of fruit over reserve

formation. However, if high yield results in the depletion of NSC concentrations to the extent that they cannot be replenished prior to senescence (high levels of NSC are required in

December to assure high yield), then this may lead to a reduction in the following year’s yield and ultimately explain the alternate bearing habit seen in _P. vera_16. If true, breeding

objectives aiming to reduce alternate bearing in _P. vera_18 may benefit from selecting varieties that show a strong NSC recovery pattern in the fall. _Prunus dulcis_ presents a slightly

more complicated picture of carbohydrates’ impact on yield. NSC total, starch, and sugar concentrations in wood were positively correlated with yield in late fall and during dormancy

(November through February) with February reserves being the most important positive feature associated with high yield. This would suggest that high NSC levels just prior to and during

bloom are the most important prerequisite for achieving higher yields. Hence, a high NSC content during dormancy, achieved either by preservation and/or by the influx of sugars from more

distal sources during bloom, to provide sufficient energy and structural material for flowers is the key element to yield success. This finding may also provide an interesting opportunity

for _P. dulcis_ breeding efforts, wherein selection could be informed by high NSC levels in February19. The sudden change in direction, from a positive relationship in February to a negative

in March, most likely reflects the strong dependence on local twig reserves for sustaining a healthy bloom and promoting vegetative bud pushing. The ensuing negative correlation,

characterized by a steep decline in NSC concentration beginning in March, continuing through the summer1,3 suggests that during the most active period, the reproductive NSC sink takes

precedence over reserve formation. While reproductive prioritization outweighs reserve formation in both _P. dulcis_ and _P. vera,_ the persistent decline observed in _P. dulcis_ comes in

stark contrast to _P. vera,_ where only a narrow time frame, the nut filling period, was negatively correlated with yield. This prolonged period of low NSC content and its associated

negative correlation with yield in _P. dulcis_ may be offset by the fact that while _P. dulcis_ has the earliest harvest amongst the three species, its senescence occurs at the same time as

in _P. vera_ and _J. regia._ Thus, in effect allowing more time for the recovery of NSC and potentially avoiding a pronounced alternate bearing habit17. _Juglans regia_ presents the most

ambiguous pattern of carbohydrate impact on yield. Much like _P. dulcis_ and _P. vera_, we also found the strongest positive correlations between NSC content and yield in the months just

prior to budbreak. However, in contrast to the two-former species, _J. regia_ is a wind-pollinated species with female flowers developing on new vegetative extension growth and thus relies

on the concurrent development of both the vegetative and flowering structures. As a result, this magnifies the burden of bearing enough NSC reserves to initiate both their growths following

dormancy. In walnut, this burden exceeds the storage-supply capacity within the twigs and it must therefore import NSC from distant sources to attain sufficient energy. Therefore, in

preparation for bloom, _J. regia_ may strongly depend on the redistribution of NSC, via the xylem, from the stem to twigs thus reducing its reliance on autumnal carbohydrate reserves.

Indeed, in February and March, we observed that increases in twig NSC were most consistently in the woody conductive tissues15,20. Furthermore, given that flowering and vegetative growth

occur simultaneously, photosynthetic independence promptly follows thereby quickly becoming the main energy source for supporting both their growths. Hence, the dependence on a distal

energetic supply for growth initiation and then on current photosynthate for growth sustenance may explain the lack of significant correlations between twig NSC storage and yield. As a

consequence, the antagonistic relationship between storage and reproductive sinks that is more apparent in _P. vera_ and _P. dulcis_ is diminished, making _J. regia_ potentially less

sensitive to twig reserve carbohydrate content. Interestingly, when analyzing monthly importance there were consecutive shifts; from a high NSC content in June, as the most important

predictor of low crop, to a high NSC content in July, as the most important predictor of high yield. These months, in particular, coincide with the transitional phases that occur between

growth and storage accumulation. In _J. regia_ specifically, June marks the fastest growth rates and the lowest carbohydrates content while July is the moment at which growth slows but also

the point of maximum reserve accumulation rates1. Therefore, in the context of phenology and yield, it is thought-provoking that the crux between the interplay of these months is captured as

most important for predicting final yields. Such increasing importance on mid-summer carbohydrate concentrations further supports the notion that in _J. regia_, high crop is not dependent

on the competition between storage and yield but rather on an overall high photosynthetic productivity especially at the end of summer. The low dependence of yield on autumnal NSC reserves

can be expected from the fact that multi-year observations of NSC content on walnut tree twigs were relatively unaffected by seasonality compared to the two other studied species1. In

addition, it is important to note that an impact of NSC reserves on yield is not always detected, for example in _Olea europea_ L. (olive tree) no such impact has been reported21. However,

such a relationship may be very difficult to detect in small, short term experimental studies due to high temporal and year-to-year variation in NSC content1,3,9. In all cases, only 1 or 2 

months shared a high importance for crop prediction and such distribution of importance may suggest the practical implications in using carbohydrate analyses for orchard management and

decision making. A simple NSC concentration analysis in twigs at specific months for example, December for _P. vera_ or February for _P. dulcis_, can help project yield and provide

information for assessing irrigation and fertilization needs. As non-structural carbohydrate content represents a buffer between photosynthetic capacity and needs (base respiration, growth,

yield, defense, and dormancy reserve formation), knowledge on their dynamics may provide physiological insights to better understand the physiological status of trees. Sudden and unexpected

changes to NSC concentrations may reflect orchard health issues. The introduction of NSC analysis to breeding may open new avenues in the search for high-yielding varieties. We can also

expect that adding NSC content analysis to yield prediction models which consider environmental elements (temperature, rainfall) as physiological attributes and encompass a range of abiotic

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like to thank all growers who contributed samples and yield and the undergraduate researchers that work in our lab without whom, this research would not be possible. FUNDING This work was

made possible by the California Department of Food and Agriculture (18-0001-020-SC), The Almond Board of California, the California Walnut Board, and the California Pistachio Research Board.

AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Department of Plant Sciences, University of California Davis, Davis, CA, 95616, USA Maciej A. Zwieniecki, Jessica Orozco, Katelyn B. Cooper 

& Paula Guzman-Delgado * Department of Natural Resources and the Environment, Cornell University, Ithaca, NY, 14853, USA Anna M. Davidson Authors * Maciej A. Zwieniecki View author

publications You can also search for this author inPubMed Google Scholar * Anna M. Davidson View author publications You can also search for this author inPubMed Google Scholar * Jessica

Orozco View author publications You can also search for this author inPubMed Google Scholar * Katelyn B. Cooper View author publications You can also search for this author inPubMed Google

Scholar * Paula Guzman-Delgado View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS M.Z. conceptualized the project, analyzed data, and wrote

first version of the manuscript. J.O. and P.G.-D. provided thorough interpretation of data help with analysis and manuscript preparation. A.D. and K.C. collected data and managed the

processing of laboratory samples data interpretation and provided edits to the manuscript. CORRESPONDING AUTHOR Correspondence to Maciej A. Zwieniecki. ETHICS DECLARATIONS COMPETING

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permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Zwieniecki, M.A., Davidson, A.M., Orozco, J. _et al._ The impact of non-structural carbohydrates (NSC) concentration on yield in _Prunus

dulcis, Pistacia vera_, and _Juglans regia_. _Sci Rep_ 12, 4360 (2022). https://doi.org/10.1038/s41598-022-08289-8 Download citation * Received: 29 October 2021 * Accepted: 02 March 2022 *

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