Front. Agron. Frontiers in Agronomy Front. Agron. 2673-3218 Frontiers Media S.A. 10.3389/fagro.2026.1771067 Original Research Zero tillage enhances cold stress tolerance and yield stability in dryland wheat Zehtab SalmasiSaeid 1 * Supervision Writing – review & editing Writing – original draft Project administration KhorsandiHadi 2 Methodology Writing – original draft Formal analysis Investigation Software Data curation LotfiRamin 2 Writing – review & editing Methodology Writing – original draft Sustainable Agriculture Science Center, Department of Plant and Environmental Sciences, New Mexico State University, Alcalde, NM, United States Dryland Agricultural Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Maragheh, Iran Correspondence: Saeid Zehtab Salmasi, saeidzs@nmsu.edu 04 03 2026 2026 8 1771067 18 12 2025 09 02 2026 03 02 2026 Copyright © 2026 Zehtab Salmasi, Khorsandi and Lotfi. 2026 Zehtab Salmasi, Khorsandi and Lotfi https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

Cold stress limits rainfed wheat productivity. We combined a cold−room assay (+4 → −15 °C) with a two−year split–split plot field trial to test whether zero tillage (ZT) and sowing date improve cold tolerance across bread and durum cultivars. ZT, especially with September sowing, enhanced PSII performance (higher ETo/RC, Fv/Fm, Fv/Fo; lower ABS/RC and Fo/Fm), increased antioxidant activity (SOD, APX, CAT), and reduced H2O2 and MDA, leading to higher and more stable grain yield. Winter cultivars sustained pigments and antioxidant defense better than spring types. These results position ZT + early sowing as a practical, climate−smart strategy to buffer cold stress and stabilize yields in drylands.

 Graphical Abstract

Infographic summarizing that zero tillage and early sowing in dryland wheat improve cold stress tolerance and yield stability by increasing Fv/Fm ratio and reducing reactive oxygen species, leading to better yield stability compared to conventional tillage.

antioxidant enzymes chlorophyll fluorescence cold stress dryland wheat yield stability zero tillage The author(s) declared that financial support was not received for this work and/or its publication. section-at-acceptance Climate-Smart Agronomy Introduction

Wheat (Triticum spp.) is a cornerstone crop for global food security, yet its production in dryland systems faces mounting challenges from climate variability. Increasingly erratic temperature patterns, such as warmer autumns, mid-winter thaws, and late spring freezes, compress sowing windows and elevate the risk of cold stress during early developmental stages (Neupane et al., 2022; Wang et al., 2017; Hassan et al., 2021; Noort et al., 2022; Ejaz et al., 2023). These stress events impair stand establishment, disrupt phenology, and reduce yield stability, particularly when combined with water deficits typical of rainfed environments (Guo et al., 2019; Koua et al., 2021; Koua et al., 2023; Denora et al. 2023; Dong et al., 2024). Physiologically, cold stress inhibits photosynthesis, triggers reactive oxygen species (ROS) accumulation, and accelerates membrane lipid peroxidation, ultimately compromising plant growth and productivity (Ruelland et al., 2009; Han et al., 2013).

Conservation agriculture (CA) has emerged as a climate-smart approach to sustain crop productivity under such constraints. Among CA practices, zero tillage (ZT), characterized by minimal soil disturbance and residue retention, offers multiple benefits: improved soil water conservation, moderated temperature fluctuations, and enhanced nutrient cycling (Kay and VandenBygaart, 2002; Van Wie et al., 2013; Hobson et al., 2022; Behr et al., 2024; Chaudhary et al., 2024; Fiorentini et al., 2024). In dryland wheat systems, ZT often improves yield and year-to-year stability by buffering the soil microclimate and strengthening early establishment (Hemmat and Eskandari, 2006; Nurbekov et al., 2024). However, while ZT’s role in mitigating drought stress is well documented, its physiological and biochemical contributions to cold stress tolerance remain insufficiently understood.

Mechanistically, ZT alters soil thermal conductivity and porosity, reducing diurnal temperature swings and freeze–thaw cycles (Abu-Hamdeh, 2000; Sarkar and Singh, 2007). Residue cover conserves profile water and reduces evaporative losses, supporting winter survival and spring re-acclimation. These soil-mediated effects may translate into improved photosynthetic resilience under cold stress, yet direct evidence linking ZT to photosystem II (PSII) electron transport and oxidative stress mitigation is scarce. Chlorophyll fluorescence (Chl F) analysis, particularly the OJIP transient and derived performance indices, provides sensitive diagnostics of PSII function under stress (Strasser, 1997; Tsimilli−Michael and Strasser, 2013; Kumar et al., 2020; Spanic et al., 2021; Papageorgiou and Govindjee 2004; Koua et al., 2022). Cold-induced ROS bursts are countered by enzymatic antioxidants, superoxide dismutase (SOD), ascorbate peroxidase (APX), and catalase (CAT), and non-enzymatic pools, which collectively maintain cellular redox balance (Aebi, 1984; Nakano and Asada, 1981; Dhindsa et al., 1981; Lotfi et al., 2015). Integrating these physiological and biochemical markers under field conditions is critical to understanding ZT’s role in cold stress adaptation.

Genotypic variation further complicates this picture. Winter wheat cultivars typically exhibit stronger acclimation and re-acclimation capacity than spring types, sustaining chlorophyll content and antioxidant activity under prolonged cold (Han et al., 2013; Sairam et al., 2001). Sowing date also modulates stress exposure: early sowing (September) enables root and canopy development before severe freezes, whereas late sowing (November) shortens acclimation windows and heightens oxidative damage (Wang et al., 2017). Despite these interactions, few studies have examined how ZT interacts with sowing date and cultivar type to influence PSII performance, antioxidant defense, and yield stability under real-world cold stress scenarios.

Although ZT is recognized for conserving soil moisture and moderating temperature, its direct, field-scale impacts on photosynthetic electron transport and oxidative stress mitigation during cold events remain poorly quantified. Understanding these linkages is essential for designing climate-resilient management strategies in dryland wheat systems.

This study aimed to (i) determine whether ZT improves PSII performance and antioxidant activity under cold stress, (ii) assess cultivar differences in physiological and biochemical acclimation, and (iii) evaluate how sowing date modulates these responses and yield stability.

We hypothesize that zero tillage, combined with early sowing, enhances cold stress tolerance and yield stability in dryland wheat by improving PSII electron transport efficiency and strengthening antioxidant defense mechanisms compared to conventional tillage.

 Materials and methods Site, design, and treatments

Two complementary experiments were conducted at the Dryland Agricultural Research Institute (DARI), Maragheh, Iran: a controlled cold−room pot study and a split−split plot field trial across two seasons (2018–19, 2019–20). Six cultivars were evaluated, winter bread wheats (Sardari, Baran), facultative bread wheat (Rizhav), and spring durums (Saji, Rascon, Gerdish) (Table 1). Field factors: main plot; sowing date (mid−September, mid−October, mid−November); subplot; tillage (ZT vs. CT); sub−subplot; cultivar; randomized complete block design (RCBD), n = 3.

Names and characteristics of wheat cultivars.

Numbers Released nameor variety Classified by
Kernel texture and genome Growing season
1 Sardari Bread wheat, hexaploid genome Winter
2 Baran Bread wheat, hexaploid genome Winter
3 Rizhav Bread wheat, hexaploid genome Facultative
4 Saji Durum wheat, tetraploid genome Spring
5 Rascon Durum wheat, tetraploid genome Spring
6 Gerdish Durum wheat, tetraploid genome Spring

Rationale for cultivar panel: the set reflects dominant regional classes and phenology windows under dryland conditions; one facultative type (Rizhav) was included to represent winter–spring intermediates, constrained by seed availability and farmer adoption in the study area.

Seeds (380 m-²) were drilled (Aske model 2200) at 4–5 cm depth; rows 17.5 cm; plot size 13 rows × 10 m. Fertilizer: 87 kg N ha-¹ (urea) + 32 kg P ha-¹ (TSP) at sowing; one 50 mm irrigation ensured emergence. Soils (0–30 cm) were sampled at 10 points for physical/chemical characterization (Table 2). Monthly minimum/maximum temperatures, days ≤ 0 °C, and precipitation for both seasons are summarized in Table 3 (Weather).

Physical and chemical characteristics of the soil at the experimental location.

Depth Ece×103dS.m-¹ pH P K Total N CaCO3 OM Sand Silt Clay
Mg.kg-1 %
0–30 cm 0.69 7.36 17 363.4 3.50 6.25 0.66 38 36 26

Where P, K, N, CaCO3, OM are phosphorus, potassium, nitrogen, calcium carbonate, organic matter, respectively.

Monthly weather conditions (2018–2019; 2019–2020) at the experimental site.

Year 2018-2019 Year 2019-2020
Month Absolute minimum temperature °C Absolute maximum temperature °C Days under zero °C Precipitation mm Absolute minimum temperature °C Absolute maximum temperature °C Days under zero °C Precipitation mm
October 3 28 0 9.7 2.5 29 0 21.6
November -2.5 19.2 7 47 -10 16.4 17 4
December -6 12 16 91.4 -7 11.6 21 27.8
January -14.5 8.4 28 40.8 -17 13 28 67.6
February -14.5 10 25 86.4 -25 6.2 30 24.9
March -8 13.8 23 55.6 -9 16.4 18 58.6
April -4 19 5 116.1 -2.5 19 9 80.1
May -4 25.8 7 43.4 1 25 0 42
June 5 31.8 0 4.2 3.5 32.6 0 0.2
July 10 37.4 0 0 8 37.6 0 13
Controlled cold−stress pot experiment

Justification of temperature protocol: The step−wise 24 h exposure at +4, −5, −10, and −15 °C follows wheat cold−stress testing practice to capture acclimation and oxidative dynamics without acute lethality. This stepwise regime aligns with established controlled−freezing test practices for winter wheat, where plants are acclimated near 3–4 °C and then subjected to incremental subzero exposures (~24 h per step) to resolve acclimation and injury dynamics (Skinner and Bellinger, 2016).

A completely randomized design (CRD; n = 3) was used. Twelve seeds per pot (15 × 20 cm; 1.5 kg field soil) were sown, watered to field capacity (tap water EC 0.87 dS m-¹), and grown at 15 °C under 2000–4000 lux. At the four−leaf stage (Zadoks 14), seedlings were exposed to +4 °C for 24 h, then −5 °C, −10 °C, and −15 °C (each for 24 h). Three seedlings per cultivar per temperature were harvested for pigments and enzyme assays.

 Sampling and measurements Chlorophyll a fluorescence measurements

At anthesis (Zadoks 65), flag leaves were dark−adapted (≥ 30 min) and probed (Handy−PEA; Hansatech, UK) to obtain Fo and Fm and compute ABS/RC, ETo/RC, Fo/Fm, Fv/Fm, and Fv/Fo (Strasser, 1997; Tsimilli−Michael and Strasser, 2013). OJIP transients were double normalized (WOK, WKJ, WJI, WIP), and ΔWOX = WOX(ZT) − WOX(CT) was calculated (Zivcak et al., 2014; Hassannejad et al., 2020).

 Relative water content

Relative water content was determined by flag leaf sampling at the anthesis stage as follows:

Relative water content (%)=(Fresh weight−Dry weight)(Saturated weight−Dry weight)×100 Photosynthetic pigments

Chl a and Chl b were quantified after 80% ethanol extraction (Wellburn, 1994).

Chl a (µg cm-²) = [(12.7 × A663) − (2.6 × A645)] × (ml ethanol/leaf area).

Chl b (µg cm-²) = [(22.9 × A645) − (4.68 × A663)] × (ml ethanol/leaf area).

 Enzyme assays

Leaf samples (0.5 g) were homogenized in 0.1 mol L-¹ phosphate buffer (pH 7.5) + 0.5 mmol L-¹ EDTA; centrifuged (15,000 g, 4 °C, 15 min).

Catalase (CAT) (Aebi, 1984): ΔA240 in reaction with H2O2.

Ascorbate peroxidase (APX) (Nakano and Asada, 1981): ΔA290 (ϵ = 2.8 mmol-¹ cm-¹).

Superoxide dismutase (SOD) (Dhindsa et al., 1981; Cakmak and Horst, 1991): unit = 50% inhibition of NBT photoreduction; expressed as U mg-¹ protein.

 Lipid peroxidation

TBARS assay (modified from Cakmak and Horst, 1991): A532 corrected by A600; reported as MDA equivalents.

 Hydrogen peroxide

KI method (Sergiev et al., 1997): A390 against standard curve.

 Grain yield

At ~12% grain moisture, five inner rows (8 m) per plot were harvested to determine grain yield.

 Statistical analysis

Assumptions of ANOVA, including normality and homoscedasticity, were verified prior to analysis using Shapiro–Wilk and Levene’s tests, and data met these criteria. Data were analyzed in SAS v9.1. Controlled study: factors T (temperature), V (cultivar), and T × V. Field study: Y (year), D (date), T (tillage), G (cultivar), and interactions. Means were separated by LSD at P ≤ 0.05.

 Results Controlled conditions (cold room)

ANOVA indicated that temperature, cultivar, and T × V significantly affected Chl a, Chl b, SOD, APX, CAT, H2O2, and MDA (Table 4—ANOVA; Table 5—means). With decreasing temperature (+4 to −15 °C), Chl declined and antioxidant enzymes/oxidative markers increased. Sardari and Baran maintained higher Chl and antioxidant activities, with lower H2O2 and MDA than Rizhav and spring durums (Saji, Rascon, Gerdish). CAT and H2O2 rose sharply in Rizhav/Saji at lower temperatures, suggesting stronger stress response (Table 5).

Analysis of variance for biochemical characteristics in the cold−room experiment (T = temperature; V = cultivar).

SOV df Chl a Chl b SOD APX CAT H2O2 MDA
Rep 2 66.86 42.20 0.564 0.0037 0.0078 0.019 0.976
T 5 690.32** 349.92** 1.726 0.1785** 0.3486** 4.665** 48.15**
V 3 14037** 4150** 871** 0.3915** 0.8636** 21.92** 752**
T × V 15 90.88** 63.12** 11.19** 0.0206** 0.0364** 0.973** 8.82*
Residual 46 33.82 10.59 3.15 0.0026 0.0036 0.078 3.75

1 * and **: significant at 5% and 1% probability levels. Chl a, chlorophyll a; Chl b, chlorophyll b; SOD, Superoxide dismutase; APX, Ascorbate peroxidase; CAT, Catalase; H2O2, Hydrogen peroxide; MDA, Malondialdehyde.

Means of the biochemical properties of the wheat cultivars at different temperatures under controlled conditions.

Treatments Chl aµg·cm−2 Chl bµg·cm−2 SODg.g-1 APXg.g-1 CATg.g-1 H2O2g.g-1 MDAg.g-1
+4 °C Sardari 95.07 57.64 0.26 0.67 0.99 13.87 03.92
Baran 100.95 61.07 0.24 0.56 1.07 12.83 03.35
Rizhav 85.38 56.64 0.09 0.32 0.91 12.11 03.60
Saji 92.39 54.00 0.12 0.29 0.88 13.19 03.19
Gerdish 87.25 65.01 0.13 0.39 0.94 12.7 03.17
Rascon 92.57 64.37 0.13 0.37 0.95 11.94 03.49
-5 °C Sardari 79.11 48.82 0.31 0.72 1.20 16.52 10.22
Baran 77.98 45.71 0.31 0.62 1.06 15.54 10.81
Rizhav 55.96 38.30 0.19 0.48 2.27 19.72 16.46
Saji 54.12 36.06 0.22 0.53 2.21 21.68 14.36
Gerdish 71.10 39.41 0.21 0.55 2.03 19.17 14.03
Rascon 71.79 40.06 0.19 0.53 2.01 17.99 14.70
-10 °C Sardari 65.06 38.32 0.53 0.94 1.24 19.74 13.31
Baran 64.19 35.41 0.66 0.91 1.29 18.98 14.67
Rizhav 42.12 25.56 0.29 0.59 3.84 27.41 17.93
Saji 38.48 23.41 0.29 0.61 4.02 26.81 17.83
Gerdish 40.18 22.70 0.39 0.79 3.59 24.59 17.95
Rascon 46.01 27.94 0.31 0.81 3.28 22.53 18.10
-15 °C Sardari 32.74 38.15 0.75 1.31 2.24 24.31 15.44
Baran 30.57 39.40 0.74 1.32 2.68 24.99 16.42
Rizhav 25.11 18.95 0.29 0.61 4.10 30.11 19.57
Saji 23.05 17.87 0.24 0.62 3.97 30.47 20.17
Gerdish 28.95 20.45 0.48 0.91 3.51 28.97 18.82
Rascon 28.93 25.26 0.38 0.82 4.08 28.04 18.98
LSD 5% 9.558 5.349 0.920 0.084 0.099 0.459 3.185

*Chl a, chlorophyll a; Chl b, chlorophyll b; SOD, Superoxide dismutase; APX, Ascorbate peroxidase; CAT, Catalase; H2O2, Hydrogen peroxide; MDA, Malondialdehyde.

 Field fluorescence transients, sowing date, and tillage Chlorophyll fluorescence (OJIP) transient

All wheat cultivars have shown a typical polyphasic rise in chlorophyll a fluorescence (Chl F) transient curves. A recognizable increase in the J-I-P phase of Chl F transient curves was observed in the Baran and Sardari cultivars, but the values were low in the Rizhav and Saji cultivars (Figure 1A). Plants from the first date of sowing (Sept.) had higher Chl F values at the J-I-P phases, and with delays in the time of sowing, Chl F values at these stages declined (Figure 1B). Additionally, the results indicated that plants grown under zero tillage treatment had slightly higher Chl F values at the J-I-P phase (Figure 1C).

Changes in chlorophyll a fluorescence intensity of wheat cultivars (A) on different dates of sowing (B) and tillage practices (C).

Grouped bar chart with three panels compares chlorophyll a fluorescence intensity. Panel A shows Baran and Sardari cultivars have the highest values. Panel B shows September and October sowing dates yield higher intensities than November. Panel C shows ZT tillage method results in higher intensity than CT.

For a detailed analysis of the impact of zero tillage (conservation agriculture) on electron transport efficiency of wheat cultivars, the changes in OJIP fluorescence rise kinetics and the differential curves during O to P transients were presented (L, K, J, I, and G bands). The bands were generated by taking the difference of normalized fluorescence values between the O-K, K-J, J-I, and I-P phases. Both curves were calculated and plotted with the mean of three individual data points. Chl F transients were double normalized between Fo (0.05 ms) and FK (0.3 ms) according to WOK = (Ft − Fo)/(FK − Fo). The control transient was then subtracted from those of the treated plants (ΔWOK). Moreover, Chl F transients were double normalized between FK (0.3 ms) and FJ (3 ms), defined as WKJ = (Ft − FK)/(FJ − FK), with differential calculation of zero tillage vs conventional tillage (ΔWKJ). Double normalized Chl F data during 3 ms to 30 ms and from 30 ms to the time to reach Fm (300 ms) were drawn to provide ΔWJI and ΔWIP, respectively (Figure 2). Positive values indicate lower electron transportation rates, i.e., decreased efficiency of electron transport with negative values. Zero tillage had no significant effect on Chl F at WOK (Figure 2). However, according to the results, wheat plants under zero tillage treatment had greater electron efficiency at WKJ, WJI, and WIP (Figure 2) phases.

Effect of zero tillage application on the normalized fluorescence transient curve of wheat: Change in the shape of the chlorophyll a fluorescence transient curves normalized between Fo and FK expressed as WOK (WOK = (Ft –Fo)/(Fk –Fo)), Fk and FJ expressed as WKJ (WkJ = (Ft − Fk)/(FJ − Fk)), FJ and FI expressed as WJI (WJI = (Ft − FJ)/(FI − FJ)) and FI and FP expressed as WIP (WIP = (Ft − FI)/(FP − FI)). ΔWOX = WOX (treatment) − WOX (control).

Four line graphs display normalized delta W values over time for four different data sets. Top left shows DWOK (Fo-FK normalized), top right shows DWKJ (FK-FJ normalized), bottom left shows DWJ (FJ-FI normalized), and bottom right showsDWIP (FI-FP normalized). Each graph presents fluctuating or trending patterns for their respective data series, illustrating change over varying time intervals in milliseconds. Chlorophyll fluorescence parameters

Absorption flux per one active reaction center (ABS/RC), the maximum electron transport flux per reaction center (ETo/RC), the maximum quantum yield of basal non-photochemical energy losses (Fo/Fm), the maximum quantum yield of PSII (Fv/Fm), and the activity of the water-splitting complex on the donor side of PSII (Fv/Fo) were significantly affected by the date of sowing (Table 6). Maximum values of ABS/RC and minimum values of Fo/Fm were recorded from the third (Nov.) and the first (Sept.) dates of sowing. Differences between the Sept. and Oct. dates for ABS/RC were not significant. The highest values of ETo/RC, Fv/Fm, and Fv/Fo were obtained from the Sept. (first date of the sowing) (Table 6).

Means of SOD, H2O2, and MDA of dryland wheat cultivars at different times of sowing in conservation and conventional tillage practices over two years.

SOD, LSD winter=1.18, LSD spring=1.03
Sardari Baran Rizhav Saji Rascon Gerdish
Year Sowing time Tillage Winter Spring Winter Spring Winter Spring Winter Spring Winter Spring Winter Spring
Y1 Sept. CT 10.12 13.97 10.37 14.03 10.05 13.10 7.40 10.54 6.84 9.65 4.16 7.33
ZT 11.11 13.82 12.98 15.99 10.80 13.84 7.40 11.61 7.13 9.84 5.24 7.88
Oct. CT 11.10 14.02 12.85 15.23 9.83 11.83 5.23 7.57 5.68 8.92 5.90 7.68
ZT 12.65 14.16 13.16 16.03 10.08 13.41 6.03 7.86 6.86 8.90 6.78 8.26
Nov. CT 8.66 10.03 9.08 10.33 10.96 11.90 7.36 8.47 7.18 8.82 4.80 8.16
ZT 9.99 12.70 9.77 10.76 10.84 12.69 7.13 9.01 7.70 9.74 5.11 8.32
Y2 Sept. CT 7.94 11.75 14.60 16.41 6.26 7.01 5.06 5.85 8.20 10.07 8.43 10.30
ZT 8.28 12.57 15.09 18.28 6.24 6.97 5.00 5.72 8.14 10.00 8.52 10.39
Oct. CT 8.05 12.03 14.67 17.60 5.34 6.53 4.18 5.49 7.32 9.19 7.81 9.36
ZT 8.75 12.76 14.10 17.65 5.51 6.29 4.27 4.90 7.41 9.28 8.21 10.08
Nov. CT 5.78 8.11 9.30 12.89 4.48 5.34 3.24 4.31 6.38 8.25 6.25 11.11
ZT 5.64 8.91 10.24 13.30 5.04 6.20 3.96 4.89 7.10 8.97 6.54 11.41
H2O2, LSD winter=0.61, LSD spring=0.41
Winter Spring Winter Spring Winter Spring Winter Spring Winter Spring Winter Spring
Y1 Sept. CT 1.74 2.34 1.37 2.01 2.10 2.47 2.36 2.95 2.96 3.57 3.10 3.45
ZT 1.37 1.77 1.77 1.96 1.80 2.17 1.80 2.32 2.30 2.90 1.78 2.39
Oct. CT 2.82 2.88 2.02 2.56 2.63 2.96 1.73 2.34 3.48 3.70 3.34 3.70
ZT 2.06 2.52 1.89 1.84 1.93 2.19 1.84 2.39 2.88 3.49 1.96 2.57
Nov. CT 3.45 3.70 2.82 2.87 3.18 3.74 3.45 3.70 3.59 4.48 3.64 4.47
ZT 2.37 2.43 2.49 3.48 1.83 2.49 3.18 3.64 3.42 3.69 3.55 3.79
Y2 Sept. CT 2.14 1.51 2.23 1.46 4.56 4.39 5.70 5.61 3.47 3.17 3.15 2.90
ZT 1.96 1.87 2.05 1.83 4.26 4.22 5.40 5.44 3.29 3.26 2.97 2.94
Oct. CT 2.75 1.61 2.84 1.56 5.35 4.45 6.49 5.67 4.08 3.81 3.78 3.49
ZT 2.26 2.13 2.35 2.08 4.40 4.31 5.54 5.53 3.59 3.38 3.27 3.06
Nov. CT 3.03 1.72 3.12 1.67 4.89 4.54 6.03 5.76 4.36 4.03 4.07 3.73
ZT 2.41 2.27 2.50 2.22 4.50 4.37 5.64 5.60 3.74 3.57 3.42 3.25
MDA, LSD winter=1.65, LSD spring=2.26
Winter Spring Winter Spring Winter Spring Winter Spring Winter Spring Winter Spring
Y1 Sept. CT 20.90 28.68 18.20 27.07 22.20 30.54 24.20 30.66 29.30 37.38 25.40 34.28
ZT 15.30 21.58 12.70 20.66 17.50 24.70 17.50 25.14 27.60 30.89 20.30 26.72
Oct. CT 27.20 33.88 18.00 23.87 28.30 34.33 15.90 24.37 26.90 34.62 28.40 33.63
ZT 16.70 23.08 26.50 31.65 19.40 26.44 19.50 23.22 26.40 33.79 23.30 29.70
Nov. CT 29.70 35.70 27.90 34.24 28.60 35.58 29.60 37.07 38.90 44.65 38.40 45.15
ZT 20.10 24.79 26.50 32.49 24.80 30.11 24.60 30.90 34.50 39.44 30.60 38.88
Y2 Sept. CT 20.10 19.51 19.10 18.29 32.60 32.48 35.30 35.91 25.50 24.30 23.20 22.05
ZT 20.00 19.48 18.90 18.52 30.30 29.94 33.50 31.12 24.30 23.46 22.00 21.21
Oct. CT 22.80 21.61 22.80 21.84 34.40 33.51 37.60 36.84 29.10 27.87 26.70 25.25
ZT 22.60 21.82 21.00 20.89 35.40 34.30 38.60 36.00 25.60 24.77 23.40 22.28
Nov. CT 26.30 25.72 25.90 23.80 39.90 39.30 42.90 42.54 30.40 29.03 28.00 26.45
ZT 24.70 24.27 22.80 21.92 37.60 37.05 40.90 39.22 27.70 26.36 25.30 24.11

Y1 (first year, 2018-19), Y2 (second year, 2019-20), SOD (Superoxide dismutase), H2O2 (Hydrogen peroxide) and MDA (Malondialdehyde).

Tillage methods had no significant effects on the Chl F parameters. According to Table 6, lower values of the ABS/RC and Fo/Fm, and higher values of the ETo/RC, Fv/Fm, and Fv/Fo were recorded for the zero tillage treatment. The effects of cultivar on Chl F parameters were significant (Table 6). The highest ABS/RC was obtained from the Rascon and Rizhav cultivars. The least value of ABS/RC was recorded for Baran (Table 6). Maximum and minimum values of ETo/RC and Fv/Fo were obtained from the Baran and Rizhav cultivars, respectively (Table 6). Saji had the highest value of Fo/Fm. The lowest Fo/Fm and the highest Fv/Fm were similarly obtained from the Sardari, Baran, Rascon, and Gerdish cultivars (Table 6).

 Physiological and biochemical properties

Some biochemical field data were collected in early winter and late spring from seedlings at different developmental stages (Figure 3) according to various sowing dates over two years. Analysis of variance indicated that the effect of year was significant on RWC, Chl a, Chl b, SOD, H2O2, MDA (spring), and grain yield. RWC, Chl a, and SOD (spring) were significantly affected by the date of sowing (Table 7; Figure 4). The interaction between year and date of sowing was significant for RWC, Chl a, SOD (winter), H2O2, MDA (spring), and grain yield. The main effect of tillage treatment was significant for Chl a, Chl b, SOD (winter), H2O2 (winter), and MDA. The interactions of year and tillage, date of sowing and tillage, and year, date of sowing, and tillage were significant for RWC, H2O2 (spring and winter), SOD, and MDA (spring). Chl a, Chl b, H2O2 (winter), and MDA (spring) were significantly affected by the main effect of cultivar. The interaction of year and cultivar was significant for all biochemical traits and grain yield. However, those traits were not significantly affected by the interaction of tillage and cultivar. Chl a, Chl b, and SOD were significantly affected by the interactions of date of sowing and cultivar, year and tillage and cultivar, and date of sowing and tillage and cultivar. RWC, Chl a, Chl b, and grain yield were significantly affected by the interactions of year, date of sowing, and cultivar. Interactions among year, date of sowing, tillage, and cultivar were significant for RWC, SOD, H2O2, and MDA (spring) (Table 7).

Different developmental stages of apex in dryland wheat cultivars: September sowing date [(A) Sardari, (B) Baran], October sowing date [(C) Sardari, (D) Baran], and November sowing date [(E) Sardari, (F) Baran].

Six-panel microscope photograph showing the progressive developmental stages of a plant shoot tip labeled A through F, with each panel displaying increasing elongation and differentiation of the shoot structure.

Analysis of variance and mean comparison of the chlorophyll a fluorescence parameters in different wheat cultivars under different dates of sowing and tillage treatments.

Date df ABS/RC ETo/RC Fo/Fm Fv/Fm Fv/Fo
Rep 2 0.004 ns 0.001 ns 0.12 ns 0.18 ns 0.014 ns
Treatment 2 0.141** 0.067** 17.0** 2.46** 2.515**
Residual 4 0.044 0.001 0.01 0.37 0.023
Sept. Means 1.077 b 0.732 a 0.225 c 3.39 a 3.399 a
Oct. 1.131 b 0.538 b 0.248 b 2.96 b 2.968 b
Nov. 1.477 a 0.437 c 0.365 a 1.64 c 1.642 c
Tillage
Rep 2 0.246 ns 0.062 ns 0.198 ns 0.182 ns 1.67 ns
Treatment 2 1.131 ns 0.175 ns 5.612 ns 14.80 ns 222.72 ns
Residual 4 0.897 0.254 0.311 1.861 36.04
CT Means 1.571 a 0.718 a 0.325 a 0.665 a 2.338
ZT 1.554 a 0.729 a 0.264 a 0.765 a 2.723
Cultivars
Rep 2 0.56 3.57 0.107 0.126 0.062
Treatment 2 180.17* 8.84** 8.089 ** 1.35** 1.728**
Residual 4 33.75 0.75 0.291 0.09 0.070
Sardari Means 1.288 bc 0.734 b 0.230 c 0.772 a 3.287 b
Baran 1.148 c 0.789 a 0.213 c 0.794 a 3.883 a
Rizhav 1.542 ab 0.625 c 0.282 b 0.663 b 2.264 c
Saji 1.776 bc 0.710 b 0.353 a 0.626 b 1.786 c
Rascon 1.251 a 0.710 b 0.231 c 0.761 a 3.198 b
Gerdish 1.182 c 0.684 b 0.241 c 0.750 a 3.080 b

* ns, * and **: not significant and significant at 5% and 1% probability levels. ABS/RC (Absorption flux per one active reaction center), ETo/RC (the maximum electron transport flux per reaction center), Fv/Fo (the activity of the water-splitting complex on the donor site of the PSII), Fv/Fm (the maximum quantum yield of PSII), Fo/Fm (the maximum quantum yield of basal non-photochemical energy losses).

Relative water content (mean ± SE) of wheat plants under ZT and CT across sowing dates (Sept., Oct., Nov.) over two years; winter and spring samples shown separately.

Grouped bar chart compares RWC percentage for two tillage types, CT and ZT, across three sowing dates for two years, showing higher spring RWC for September sowing and minor differences between tillage methods.

In the second year, all of the cultivars had more RWC than in the first year. The RWC of the Sardari, Baran, and Rizhav cultivars from the October date of sowing was higher than that of the others. However, the Saji, Rascon, and Gerdish cultivars from September had greater RWC in the first year. Additionally, plants from the first date of sowing had more RWC than those from the other dates during both years (Figure 4; Table 8). The maximum contents of Chl a and b for all cultivars were obtained in the first year. During both years, with a delay in the time of sowing, the contents of Chl a and b were reduced (Figure 5). The reduction of Chl content in the Sardari and Baran cultivars was less in comparison to that of the others (Table 8). With a delay in the time of sowing, grain yield decreased. In the first year, Sardari and Baran at the October date of sowing and Rizhav, Saji, Rascon, and Gerdish at the September date of sowing had higher grain yields. However, the highest grain yield of all cultivars in the second year was recorded from the September date of sowing (Table 8).

Analysis of variance of the biochemical properties of wheat cultivars in field conditions under different dates of sowing and tillage treatments during two years of the experiment.

AOV df RWCspring Chl aspring Chl bspring SOD H2O2 MDA Grainyield
winter Spring winter Spring winter Spring
Year (Y) 1 5378** 83268** 62360** 989** 9.89* 93** 12.70** 1ns 780** 3131**
Residual 4 1.73 57 517.6 0.51 0.45 0.21 0.031 923 2.56 90.45
Date (D) 2 682.26* 5694** 253ns 98.58ns 78.19** 10.80ns 8.918ns 401ns 786.07ns 752.62ns
Y×D 2 23.46** 2482* 66.37ns 5.27* 2.4ns 2.16** 2.931** 735ns 60.6** 467.80*
Residual 8 0.83 293.7 374.5 0.82 0.83 0.18 0.025 791 0.85 59.78
Tillage (T) 1 0.13ns 3420** 206.17* 117.05* 123.96ns 16.40** 4.67ns 279** 611.46** 73.77ns
Y×T 1 142.82** 351.5ns 6.19ns 86.32ns 68.74ns 0.34ns 5.14** 29ns 159.72ns 25.95ns
D×T 2 0.79ns 172.2ns 26.13ns 1.57ns 5.86ns 0.65** 0.06ns 34ns 26.23ns 154.8ns
Y×D×T 2 0.68ns 413ns 0.38ns 5.88** 12.08** 0.03ns 0.02ns 8ns 12.84** 220.24ns
Residual 12 1.03 165.2 30.95 0.32 0.93 0.07 0.035 29 1.08 77.47
Cultivar (G) 5 836.22ns 12870** 3838.7** 196.46ns 296.09ns 19.28** 25.95ns 716ns 475.17** 224.28ns
Y×G 5 200.97** 3787** 1028.1** 66.84** 88.04** 14.68** 17.40** 1417** 598.98** 208.61**
D×G 10 21.26ns 536.8** 272.04** 17.53** 14.87* 0.25ns 0.134ns 355ns 12.01ns 33.05ns
T×G 5 1.08ns 255.2ns 75.64ns 1.43ns 3.6ns 0.59ns 0.763ns 461ns 20.97ns 52.37ns
Y×D×G 10 13.35* 495.8** 347.3** 2.66ns 3.36ns 0.25ns 0.094ns 328ns 22.05ns 105.27**
Y×T×G 5 5.52ns 226.7ns 65.05 1.21ns 0.65ns 0.63ns 0.57ns 506ns 27ns 22.25ns
D×T×G 10 2.27ns 196.6ns 48.61 1.39ns 2.22ns 0.22ns 0.162ns 573ns 6.99ns 18.35ns
Y×D×T×G 10 2.87** 185.5ns 29.40ns 2.3** 3.08** 0.37** 0.22** 574ns 12.31** 17.09ns
Residual 120 0.76 115.3 98.71 0.54 0.83 0.14 0.074 430 2.12 30.62

ns, * and **: non-significant, significant at 5% and 1% probability level. APX (Ascorbate peroxidase); Chl a (Chlorophyll a); Chl b (Chlorophyll b); H2O2 (Hydrogen peroxide); MDA (Malondialdehyde); RWC (Relative water content); SOD (Superoxide dismutase).

Chlorophyll a (A) and Chlorophyll b (B) (mean ± SE) under ZT and CT across sowing dates (Sept., Oct., Nov.) over two years.

Grouped bar chart with four panels compares spring chlorophyll a and b concentrations (in micrograms per square centimeter) for CT and ZT tillage systems in 2018-2019 and 2019-2020; concentrations are highest in 2018-2019, with ZT generally higher than CT, especially in September and October.

SOD activity with a delay in the time of sowing in both zero and conventional tillage treatments was reduced during the two years of the experiment, but the content of H2O2 and MDA increased. Under zero tillage treatments, plants had higher SOD activity and lower contents of H2O2 and MDA during spring sampling than in winter sampling over both years. However, with a delay in the time of sowing, differences between spring and winter sampling were not evident in this regard (Table 9).

Means of RWC, Chl a, Chl b, and grain yield of the dryland wheat cultivars at different dates of sowing over two years.

RWC-spring, LSD 5%= 1.04 Sardari Baran Rizhav Saji Rascon Gerdish
Y1 Sept. 61.84 d 62.53 e 57.69 c 57.26 56.47 d 55.59 d
Oct. 62.45 d 66.02 d 58.45 c 53.13 54.69 e 54.32 e
Nov. 54.41 e 53.33 f 52.33 e 50.59 52.91 f 53.24 f
Y2 Sept. 76.52 a 77.55 a 63.24 a 61.59 68.84 a 68.28 a
Oct. 75.00 b 76.04 b 60.31 b 57.96 66.33 b 65.47 b
Nov. 70.80 c 71.84 c 56.86 cd 54.65 63.36 c 62.25 c
Chl a-spring, LSD 5%= 13.19
Y1 Sept. 148.28 145.87 132.57 131.49 120.96 117.9
Oct. 205.4 164.89 131.26 134.42 117.88 117.04
Nov. 140.12 140.33 112.49 117.79 110.37 108.13
Y2 Sept. 121.00 132.50 87.83 68.50 108.33 104.00
Oct. 110.50 122.67 76.17 58.67 97.17 92.83
Nov. 101.83 113.17 68.00 50.83 90.00 86.33
Chl b-spring, LSD 5%= 14.33
Y1 Sept. 92.61 95.62 63.89 66.8 72.79 80.62
Oct. 73.84 83.92 73.03 81.08 61.33 68.12
Nov. 83.44 74.02 63.64 78.76 56.27 55.12
Y2 Sept. 56.71 58.3 31.01 26.59 43.85 37.28
Oct. 58.67 54.08 28.07 22.96 41.33 34.47
Nov. 52.86 53.15 24.63 19.65 38.37 31.25
Grain Yield, LSD 5%=700.6
Y1 Sept. 1447 1397 1668 1591 2106 1983
Oct. 1576 1595 1609 1276 1776 1559
Nov. 1364 1770 1587 1337 1382 1652
Y2 Sept. 4066 4001 3095 1686 2427 2527
Oct. 2631 2301 2209 1784 2412 2265
Nov. 2009 2227 1645 1432 1951 1715

Chl a (Chlorophyll a) µg·cm−2; Chl b (Chlorophyll b) µg·cm−2; and RWC % (Relative water content).

 Discussion

Mechanistic link between ZT, soil microclimate, and leaf function: Residue−retaining ZT buffers near−surface temperatures and conserves soil moisture, reducing freeze–thaw amplitude and vapor pressure deficit. These microclimatic effects limit ROS generation in chloroplasts, preserve the oxygen−evolving complex, and sustain downstream electron transport. Concordant increases in SOD/APX/CAT and improvements in OJIP−derived indices under ZT support a coordinated redox–photosynthesis synergy under cold exposure.

Limitations and future directions: (i) Microclimate and soil water were not logged at high frequency; integrating sensors will clarify ZT–environment coupling. (ii) Applicability across soil textures and residue loads requires multi−site validation. (iii) Only one facultative genotype was included; expanding genotype classes will test generality. (iv) Multi−omics (transcriptome/metabolome) can resolve regulatory nodes linking ROS metabolism to PSII stability.

ZT improves PSII function under cold stress

Across field measurements, ZT was associated with lower ABS/RC and Fo/Fm and higher ETo/RC, Fv/Fm, and Fv/Fo, consistent with more open reaction centers, reduced basal energy losses, and improved downstream electron transport. Δ−band analyses (K–J, J–I, I–P) further indicated that ZT supported donor−side oxygen−evolving complex activity and acceptor−side turnover, which are commonly impaired by cold (Strasser, 1997; Tsimilli−Michael and Strasser, 2013). These findings align with prior reports that microclimate buffering and water conservation can sustain photosynthesis under stress in conservation systems (Živčák et al., 2014; Hemmat and Eskandari, 2006).

 Antioxidant defense and oxidative status

ZT plots showed higher SOD/APX/CAT activities and lower H2O2 and MDA, indicating enhanced ROS scavenging and reduced lipid peroxidation. These biochemical shifts parallel improvements in PSII performance, supporting the view that ZT modulates cellular redox through moisture conservation and moderated temperature regimes—key drivers of ROS production during freeze–thaw cycles (Aebi, 1984; Nakano and Asada, 1981; Dhindsa et al., 1981; Ruelland et al., 2009). The coherence between fluorescence indices and antioxidant markers strengthens the mechanistic link between soil management and photosynthetic resilience.

 Role of sowing date

September sowing consistently yielded the most favorable physiological and agronomic outcomes: higher RWC (Figure 4), improved PSII indices, stronger antioxidant activity, and greater yield stability across years. Early sowing likely extends the acclimation window, allowing root and canopy development before severe cold events, while residue cover under ZT stabilizes near−surface temperatures and reduces evaporative losses (Sarkar and Singh, 2007; Van Wie et al., 2013). Conversely, November sowing curtailed acclimation time, increased oxidative load, and reduced yield, matching remote−sensing and field evidence for cold−related phenology disruptions (Wang et al., 2017; Guo et al., 2019).

 Cultivar responses

Winter cultivars (Sardari, Baran) sustained pigments and antioxidant activities better than spring durums (Saji, Rascon, Gerdish) under cold, consistent with their longer vegetative phases and capacity for re−acclimation (Han et al., 2013; Sairam et al., 2001). While genotype performance varied by year and sowing date, the directional advantages under ZT suggest that conservation management can amplify intrinsic cold tolerance, particularly when paired with early sowing.

 Implications for climate−resilient agronomy

The combined physiological (OJIP, PSII parameters) and biochemical (ROS, antioxidants) evidence shows that ZT + early sowing mitigates cold stress and stabilizes grain yield in rainfed wheat. These results complement broader CA literature on yield stability, hydrology, and climate mitigation (Hemmat and Eskandari, 2006; Van Wie et al., 2013; Fiorentini et al., 2024; Nurbekov et al., 2024). Practically, the findings support residue retention, minimal disturbance, and early planting as cornerstone recommendations for cold−prone, water−limited environments.

 Limitations and future work

Some whole−season effects of tillage on aggregated fluorescence parameters were modest, reflecting the complexity of field stress dynamics. Future research should integrate high−frequency microclimate monitoring, soil water dynamics, and multi−omics (transcriptome, metabolome) to resolve genotype × management × environment interactions. Extending trials to diverse edaphic contexts and quantifying economic outcomes (inputs, risk, profitability) will aid adoption.

 Conclusions

Zero tillage, especially when coupled with September sowing, consistently improves PSII electron transport, enhances antioxidant defense, and reduces oxidative damage in dryland wheat, translating into greater yield stability across years. Winter cultivars exhibit stronger cold acclimation, but conservation management benefits were observed across genotypes. Collectively, the results position ZT + early sowing as a climate−resilient management package for mitigating cold stress in rainfed wheat systems.

 Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

 Ethics statement

Field experiments complied with institutional and national guidelines; no endangered species were used.

 Author contributions

SZ: Supervision, Writing – review & editing, Writing – original draft, Project administration. HK: Methodology, Writing – original draft, Formal analysis, Investigation, Software, Data curation. RL: Writing – review & editing, Methodology, Writing – original draft.

 Acknowledgments

The authors would like to acknowledge the Sustainable Agriculture Science Center of New Mexico State University and Agricultural Dryland Agricultural Research Institute of Iran.

 Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

 Generative AI statement

The author(s) declared that generative AI was not used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

 Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

 References Abu−Hamdeh N. H. (2000). Effect of tillage treatments on soil thermal conductivity for some Jordanian clay loam and loam soils. Soil Tillage Res. 56, 145–151. doi: 10.1016/S0167-1987(00)00129-X Aebi H. (1984). Catalase in vitro. Methods Enzymol. 105, 121–126. doi: 10.1016/S0076-6879(84)05016-3 Behr J. H. Kuhl‑Nagel T. Sommermann L. Moradtalab N. Chowdhury S. P. Schloter M. . (2024). Conservation tillage with reduced N suppresses stress markers via rhizosphere microbiome feedbacks in winter wheat. FEMS Microbiol. Ecol. 100, fiae003. doi: 10.1093/femsec/fiae003 Cakmak I. Horst W. J. (1991). Effect of aluminium on lipid peroxidation, superoxide dismutase, catalase, and peroxidase activities in root tips of soybean. Physiol. Plant 83, 463–468. doi: 10.1111/j.1399-3054.1991.tb00121.x Chaudhary A. Yadav D. B. Poonia T. M. Roohi Sihag N. (2024). Conservation tillage and in−situ rice residue moderate soil temperature and improve wheat productivity under terminal heat. Int. J. Plant Production 18, 485–496. doi: 10.1007/s42106-024-00305-3 Denora M. Candido V. D’Antonio P. Perniola M. Mehmeti A. (2023). Precision nitrogen management in rainfed durum wheat: energy analysis, life-cycle assessment, and monetization. Precis. Agric. 24, 2566–2591. doi: 10.1007/s11119-023-10053-5 Dhindsa R. S. Plumb−Dhindsa P. Thorpe T. A. (1981). Leaf senescence: correlated with increased levels of membrane permeability and lipid peroxidation and decreased levels of superoxide dismutase and catalase. J. Exp. Bot. 32, 93–101. doi: 10.1093/jxb/32.1.93 Dong Z. Yang S. Li S. Fan P. Wu J. Liu Y. . (2024). Effects of no−tillage on field microclimate and yield of winter wheat. Agronomy 14, 3075. doi: 10.3390/agronomy14123075 Ejaz I. Pu X. Naseer M. A. Bohoussou Y. N. D. Liu Y. Farooq M. . (2023). Cold and drought stresses in wheat: A global meta−analysis of the 21st century. J. Plant Growth Regul. 42, 5379–5395. doi: 10.1007/s00344-023-10960-x Fiorentini M. Orsini R. Zenobi S. Francioni M. Rivosecchi C. Bianchini M. . (2024). Soil tillage reduction as a climate change mitigation strategy in Mediterranean cereal-based cropping systems. Soil Use Manage. 40, e13050. doi: 10.1111/sum.13050 Guo L. Gao J. Hao C. Zhang L. Wu S. Xiao X. (2019). Winter wheat green−up date variation and its diverse response on the hydrothermal conditions over the North China Plain, using MODIS time-series data. Remote Sens. 11, 1593. doi: 10.3390/rs11131593 Han Q. Kang G. Guo T. (2013). Proteomic analysis of spring freeze-stress responsive proteins in leaves of bread wheat (Triticum aestivum L.). Plant Physiol. Biochem. 63, 236–244. doi: 10.1016/j.plaphy.2012.12.002 Hassan M. A. Xiang C. Farooq M. Muhammad N. Yan Z. Hui X. . (2021). Cold stress in wheat: Plant acclimation responses and management strategies. Front. Plant Sci. 12. doi: 10.3389/fpls.2021.676884 Hassannejad S. Lotfi R. Ghafarbi S. P. Oukarroum A. Abbasi A. Kalaji H. M. . (2020). Early identification of herbicide modes of action by the use of chlorophyll fluorescence measurements. Plants 9, 529. doi: 10.3390/plants9040529 Hemmat A. Eskandari I. (2006). Dryland winter wheat response to conservation tillage in a continuous cropping system in northwestern Iran. Soil Tillage Res. 86, 99–109. doi: 10.1016/j.still.2005.02.003 Hobson D. Harty M. Tracy S. R. McDonnell K. (2022). Tillage depth and traffic effects on soil properties and winter wheat roots. SOIL 8, 391–412. doi: 10.5194/soil-8-391-2022 Kay B. D. VandenBygaart A. J. (2002). Conservation tillage and depth stratification of porosity and soil organic matterSoil Tillage Res 66, 107–118. doi: 10.1016/S0167-1987(02)00019-3 Koua A. P. Oyiga B. C. Baig M. M. Leon J. Ballvora A. (2021). Breeding-driven enrichment of genetic variation for key yield components and grain starch content under drought stress in winter wheat. Front. Plant Sci. 12. doi: 10.3389/fpls.2021.684205 Koua A. P. Oyiga B. C. Dadshani S. Benaouda S. Sadeqi M. B. Rascher U. . (2022). Chromosome 3A harbors several pleiotropic and stable drought-responsive alleles for photosynthetic efficiency selected through wheat breeding. Plant Direct 6, e438. doi: 10.1002/pld3.438 Koua A. P. Siddiqui M. N. Heß K. Klag N. Kambona C. M. Duarte−Delgado D. . (2023). Genome-wide dissection and haplotype analysis identified candidate loci for nitrogen use efficiency under drought conditions in winter wheat. Plant Genome 16, e20394. doi: 10.1002/tpg2.20394 Kumar D. Singh H. Raj S. Soni V. (2020). Chlorophyll a fluorescence kinetics of mung bean (Vigna radiata L.) grown under artificial continuous light. Biochem. Biophys. Rep. 24, 100813. doi: 10.1016/j.bbrep.2020.100813 Lotfi R. Pessarakli M. Gharavi−Kouchebagh P. Khoshvaghti H. (2015). Physiological responses of Brassica napus to fulvic acid under water stress: Chlorophyll a fluorescence and antioxidant enzyme activity. Crop J. 3, 434–439. doi: 10.1016/j.cj.2015.05.006 Nakano Y. Asada K. (1981). Hydrogen peroxide is scavenged by ascorbate-specific peroxidase in spinach chloroplasts. Plant Cell Physiol. 22, 867–880. doi: 10.1093/oxfordjournals.pcp.a076232 Neupane D. Adhikari P. Bhattarai D. Rana B. Ahmed Z. Sharma U. . (2022). Does climate change affect the yield of the top three cereals and food security in the world? Earth 3, 45–71. doi: 10.3390/earth3010004 Noort M. W. J. Renzetti S. Linderhof V. du Rand G. E. Marx−Pienaar N. J. M. M. de Kock H. L. . (2022). Towards sustainable shifts to healthy diets and food security in sub-Saharan Africa with climate-resilient crops in bread-type products: A food-system analysis. Foods 11, 135. doi: 10.3390/foods11020135 Nurbekov A. Kosimov M. Islamov S. Khaitov B. Qodirova D. Yuldasheva Z. . (2024). Zero tillage, crop residue management and winter wheat-based crop rotation strategies under rainfed environment. Front. Agron. 6. doi: 10.3389/fagro.2024.1453976 Papageorgiou G. C. Govindjee (2004). Chlorophyll a fluorescence: A signature of photosynthesis (Dordrecht: Springer). doi: 10.1007/978-1-4020-3218-9 Ruelland E. Valtier M. Zachowski A. Hurry V. (2009). Cold signaling and cold acclimation in plants. Adv. Bot. Res. 49, 35–150. doi: 10.1016/S0065-2296(08)00602-7 Sairam R. K. Chandrasekhar V. Srivastava G. C. (2001). Hexaploid and tetraploid wheat under water stress. Biol. Plant 44, 89–94. doi: 10.1023/A:1017928622281 Sarkar S. Singh S. R. (2007). Interactive effect of tillage depth and mulch on soil temperature, productivity and water use pattern of rainfed barley (Hordeum vulgare L.). Soil Tillage Res. 92, 79–86. doi: 10.1016/j.still.2006.01.014 Sergiev I. Alexieva V. Karanov E. (1997). Effect of spermine, atrazine and their combination on protective systems and stress markers in plants. C. R. Acad. Bulg. Sci. 51, 121–124. doi: 10.1046/j.1365-3040.2001.007 Skinner D. Z. Bellinger B. S. (2016). Freezing tolerance of winter wheat as influenced by extended growth at low temperatures and exposure to freeze–thaw cycles. Can. J. Plant Sci. 97, 250–256. doi: 10.1139/cjps-2016-0154 Spanic V. Mlinaric S. Zdunic Z. Katanic Z. (2021). Field OJIP responses and productivity of winter wheat under contrasting environments. Agriculture 11, 1154. doi: 10.3390/agriculture11111154 Strasser B. (1997). Donor side capacity of PSII probed by chlorophyll a fluorescence transients. Photosynth. Res. 52, 147–155. doi: 10.1023/A:1005896029778 Tsimilli−Michael M. Strasser R. J. (2013). The energy flux theory of chlorophyll fluorescence: Formulations and applications. Photosynth. Res. 117, 289–320. doi: 10.1007/s11120-013-9844-5 Van Wie J. B. Adam J. C. Ullman J. L. (2013). Conservation tillage in dryland agriculture impacts watershed hydrology. J. Hydrol. 483, 26–38. doi: 10.1016/j.jhydrol.2012.12.030 Wang S. Mo X. Liu Z. Baig M. H. A. Chi W. (2017). Understanding long−term, (1982–2013) patterns and trends in winter wheat spring green−up date over the North China Plain. Int. J. Appl. Earth Obs. Geoinf. 57, 235–244. doi: 10.1016/j.jag.2017.01.008 Wellburn A. R. (1994). The spectral determination of chlorophylls a and b, as well as total carotenoids, using various solvents with spectrophotometers of different resolution. J. Plant Physiol. 144, 307–313. doi: 10.1016/S0176-1617(11)81192-2 Živčák M. Olšovská K. Slamka P. Galambosová J. Rataj V. Shao H. B. . (2014). Application of chlorophyll fluorescence performance indices to assess the wheat photosynthetic functions influenced by nitrogen deficiency. Plant Soil Environ. 60, 210–215. doi: 10.17221/73/2014-PSE

Edited by: Sohail Abbas, Henan University, China

Reviewed by: Feilong Yan, Hebei Academy of Agriculture and Forestry Sciences (HAAFS), China

Hailong Qiu, Gansu Agricultural University, China

ABS/RC, Absorption flux per one active reaction center; APX, Ascorbate peroxidase; CAT, Catalase; Chl a , Chlorophyll a ; Chl b, Chlorophyll b; ETo/RC, the maximum electron transport flux per reaction center; FV/Fo, the activity of the water-splitting complex on the donor site of the PSII; FV/FM , the maximum quantum yield of PSII ; Fo/Fm, the maximum quantum yield of basal non-photochemical energy losses; H2O2, Hydrogen peroxide; MDA, Malondialdehyde; PSII, Photosystem II; RWC, Relative water content; ROS, Reactive oxygen species; SOD, Superoxide dismutase.