Drought Recovery Responses in Grain Sorghum: Insights into Genotypic Variation and Adaptation

Abstract

In Uganda, rain-fed crops frequently encounter cycles of drought stress followed by rewatering. Thus, with escalating fluctuations in water supply, drought recovery has become a critical focus for future sorghum drought phenotyping, genetics, and breeding research. However, there is currently a low knowledge of the drought recovery potential of prospective genotypes in Uganda’s National Sorghum Improvement Program. The present study aimed to assess the response of selected genotypes to rewatering after drought. Sixteen sorghum genotypes and two check varieties were evaluated under two contrasting moisture regimes: well-watered and drought stress-rewatering in a split-plot layout using a randomized complete block design (RCBD). Watering regimes were assigned to whole plots, while sorghum genotypes were assigned to subplots, with three replications. The results showed highly significant effects (p < 0.05) of drought stress on key agronomic traits, decreased dry weight, grain weight, and biomass yield by 39%, 43% and 37%, respectively, and delayed flowering by an average of 11 days. Key genotype-specific traits associated with drought recovery included rapid rehydration, compensatory growth, and maintenance of high relative chlorophyll content, all of which were essential for optimizing yields after stress. Leveraging drought tolerance indices, genotypes were ranked by their recovery potential and further classified into four distinct groups (A–D) based on their yield performance and stability under the two watering regimes. Genotypes in category A demonstrated high yield stability and strong recovery potential. Conversely, genotypes in category D exhibited the poorest recovery response. Overall, the information generated from this study will support future sorghum breeding efforts for drought resilience.

1. Introduction

Climate models predict increasingly frequent and severe rainfall fluctuations, prompting growing interest in exploring crop recovery potential as a strategy to maintain stable agricultural productivity amid changing climatic conditions [1,2,3]. These unpredictable patterns of alternating drought and rainfall events create significant risks for crop productivity, especially in areas vulnerable to water scarcity [4]. In Uganda, where rain-fed agriculture predominates [5], this vulnerability is especially acute. Staple crops such as sorghum (Sorghum bicolor), essential for both food and income security, face considerable challenges [6,7].

Sorghum’s inherent drought tolerance has made it a resilient crop in arid and semi-arid regions of Uganda [8,9]. However, its long-term productivity under fluctuating water conditions depends not only on its drought resistance but also on its ability to recover once water becomes available. Extensive research has focused on drought tolerance, avoidance, and escape mechanisms [10,11,12], along with molecular studies that have identified stress-inducible transcription factors, late embryogenesis abundant (LEA) proteins, and anti-oxidant enzymes that protect cellular structures during water stress [13,14,15]. However, the physiological and growth responses of sorghum to rehydration and their implications for productivity remain comparatively understudied [16,17], despite insights from related crops such as maize and sugarcane [18,19]. Recovery from drought involves processes such as water uptake, leaf re-expansion, photosynthetic restoration, and biomass accumulation, all of which play a crucial role in maintaining yield stability [17,20].

In Uganda, the National Sorghum Improvement Program has largely prioritized resistance mechanisms (namely, tolerance, avoidance, and escape), assessing genotype performance under random drought scenarios typical of Target Production Environments (TPEs), such as the Karamoja region. Although this approach has yielded valuable insights into drought resistance, limited attention has been given to how sorghum genotypes recover once water availability is restored [17]. Yet, understanding recovery-related traits is essential for developing more resilient sorghum varieties, particularly in the context of climate change. Evaluating genotypic variation in drought recovery responses presents a promising opportunity to enhance breeding programs. By identifying genotypes with superior recovery potential, researchers can equip breeders with reliable indicators for selecting drought-resilient crops. Traits related to post-drought growth, physiological resilience, and yield recovery can serve as critical selection criteria for developing varieties suited to variable water conditions [21].

This study aimed to evaluate the recovery responses of selected sorghum genotypes following drought stress, focusing on growth, morpho-physiological traits, and yield parameters after rehydration. We hypothesized that significant variation would exist among genotypes in these traits, providing valuable insights into genotypic recovery adaptation mechanisms. The findings will contribute to the development of sorghum varieties with enhanced drought resilience, supporting food security in vulnerable regions.

2. Materials and Methods

2.1. Description of the Study Area

The study was conducted at the National Semi Arid Resources Research Institute (NaSARRI), Serere, Uganda. NaSARRI-Serere is located at 1°39′ N and 33°27′ E and has an elevation of 1038 m above sea level. The native soils are sandy, with low water-holding capacity and limited organic matter content, typical of a semi-arid environment. The area experiences a bimodal type of rainfall, with an annual mean of 1427 mm and wide inter-annual fluctuations. The mean annual temperature is 24 °C, with a minimum of 17.9 °C and a maximum of 34.4 °C. The relative humidity ranges between 72% and 84% [22].

2.2. Planting Materials

This study evaluated a diverse set of sorghum genotypes selected from the breeding program at NaSARRI based on their prior performance under random drought conditions. A total of 16 genotypes and 2 checks were used to assess their drought recovery potential. The checks were chosen based on farmer preference and documented performance. NAROSORGH 4 (E17), known for its strong drought resistance traits [23], served as the positive check, while ETEREMA (E4), a more susceptible local landrace, was the negative check. The selected genotypes represented a spectrum of resistance levels, ranging from resistant to moderately resistant and susceptible (

Table 1. Description of the sorghum genotypes used in the study.

GTP	Code	Source & Origin	DTM	D.R
ASARECA 13-1 X Framida-1-1-3-1/22B	E1	B.L (NaSARRI)-Uganda	Early maturity	R
ICSX152666-B-2-7-3-1-1-1	E8	ICRISAT-Kenya	Medium maturity	R
ICSX 162719-1-4-1-1-1	E9	ICRISAT-Kenya	Medium maturity	R
IESV16 143-1-3-1	E10	Ethiopia	Medium maturity	R
NAROSORGH 4 (positive check)	E17	Released variety-Uganda	Medium maturity	R
SSGA/RAP/349	E18	L.V (Karamoja)-Uganda	Early maturity	R
ASARECA 13-1 X NAROSORGH3-1-1-1-1/22B	E2	B.L (NaSARRI)-Uganda	Early maturity	M.R
ASARECA13-1 X NAROSORGH3-1-1-5-1/22B	E3	B.L (NaSARRI)-Uganda	Early maturity	M.R
MAZDA 105 Enyankore	E12	L.V (Masindi)-Uganda	Late maturity	M.R
NAROSORGH 1 X FRAMIDA-1-1-5-1/22B	E13	B.L (NaSARRI)-Uganda	Medium maturity	M.R
NAROSORGH1 X NAROSORGH3-1-1-1-1/22B	E14	B.L (NaSARRI)-Uganda	Medium maturity	M.R
NAROSORGH1 X NAROSORGH3-1-1-5-1/22B	E16	B.L (NaSARRI)-Uganda	Medium maturity	M.R
ETEREMA (negative check)	E4	L.V (Teso)-Uganda	Medium maturity	S
GE16/2/20B X IESV92041SH (SSEA 18B#6)	E5	B.L (NaSARRI)-Uganda	Medium maturity	S
ICSV 142001	E6	ICRISAT-India	Medium maturity	S
ICSX 152005-SB-5-3-2-1	E7	ICRISAT-Kenya	Medium maturity	S
IESV 214006DL	E11	ICRISAT-Ethiopia	Medium maturity	S
NAROSORGH1 X NAROSORGH3-1-1-1-1/22B	E15	B.L (NaSARRI)-Uganda	Early maturity	S

GTP: Genotype, DTM: Days to maturity, D.R: Drought resistance, R: Resistant, M.R: Moderately resistant, S: Susceptible, L.V: Land race variety, B.L: Breeding line.

).

2.3. Experimental Setup and Management

The experiment was conducted in a rainout shelter used for drought screening at NaSARRI, following a split-plot arrangement in an RCBD. The two main treatments (whole plots) were well-watered and drought stress-rewatering treatments. Each whole plot was subdivided into 18 subplots (sorghum genotypes), with each genotype replicated three times.

The soil used in the pots was sourced from the experimental station’s fields and enriched with fully decomposed organic manure. Sowing was carried out on 13 April 2024, by placing three pairs of seeds equidistantly in 5 L pots. Two weeks later, at the 3-leaf stage, thinning was performed to retain the three most vigorous seedlings in each pot, which were maintained up to physiological maturity.

Manual weeding was performed, and irrigation was managed according to the specified watering regimes. For the well-watered regime, pots were irrigated every two days (at a rate of 1 L per pot) until the plants reached physiological maturity. Under the drought stress-rewatering regime, plants received regular irrigation until 23 May 2024, 36 days after emergence (at the panicle development stage), after which irrigation was withheld for 10 consecutive days to impose drought stress. This duration was chosen to induce substantial drought stress in the pots without causing plant death. After the drought period, plants were fully irrigated until they grew and reached physiological maturity (Figure 1).

2.4. Data Collection and Measurement

Data were collected at four-day intervals during both the drought stress period and the recovery phase, which extended up to 15 days after rewatering. Key parameters measured included leaf length, leaf width and internode length measured in centimeters using a 30 cm ruler on all three plants within each pot, while plant height was measured using a 250 cm wooden ruler. Leaf inclination angle was measured as the angle between the stem and the blade of the second fully expanded leaf using a geometric protractor. The total number of green leaves per plant was counted at physiological maturity in water stress-rewatering and in well-watered conditions. Relative chlorophyll content was measured as a proxy using a SPAD-502Plus chlorophyll meter (Konica Minolta, SPAD-502Plus, Osaka, Japan). Two fully expanded green leaves, each pair from the lower, middle, and upper portions of each plant, were measured. Three readings per leaf were taken at the base, middle, and tip, and the mean SPAD value across all sampled leaves was recorded. The stem diameter of the first internode from the ground was measured in millimeters from each plant using a digital vernier caliper (GRIFFCHEM, Digital Caliper 0–150 mm, Ningbo, Zhejiang, China).

Leaf rolling, leaf inclination angle, and epicuticular wax density are important traits linked to drought stress responses in plants [24,25]. Leaf rolling was visually assessed and scored on a 1–5 scale following established methodologies [26,27], where 1 = no visible rolling, 2 = slight rolling, 3 = moderate rolling, 4 = strong rolling, and 5 = extreme rolling with complete adaxial infolding of the leaf margins into a thorn-like or cylindrical shape [28]. Epicuticular wax density was estimated through visual scoring of stem and leaf glaucousness-a proxy for wax accumulation as described by [29,30]. A scale of 1–3 was employed, where 1 = non-glaucous (low wax density), 2 = moderately glaucous (moderate wax density), and 3 = highly glaucous (high wax density). On the other hand, drought recovery response was assessed through visual scoring that reflected each genotype’s ability to rehydrate and resume growth within 12 h of rewatering. A 1–5 scale was applied, where 1 = very rapid recovery with full leaf turgor and visible growth resumption, 2–3 = rapid to moderate recovery with partial restoration of leaf and stem vigor, 4 = poor recovery with persistent wilting and limited growth resumption, and 5 = no recovery with plants showing near-death symptoms.

This study further employed the Drought Recovery Index (DRI) [31,32] to assess morpho-physiological traits, including plant height, stem diameter, internode length, and relative chlorophyll content. The DRI was computed using the formula DRI = log (A) + 2 log (B) [32], where A denotes the relative trait value measured at the end of the drought period, and B represents the relative trait value measured two weeks after rewatering. The relative trait values were computed as follows:

$$\mathrm{R}\mathrm{e}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{v}\mathrm{e} \mathrm{T}\mathrm{r}\mathrm{a}\mathrm{i}\mathrm{t} \mathrm{V}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e}={\displaystyle \frac{\mathrm{M}\mathrm{e}\mathrm{a}\mathrm{n} \mathrm{t}\mathrm{r}\mathrm{a}\mathrm{i}\mathrm{t} \mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e} \mathrm{i}\mathrm{n} \mathrm{d}\mathrm{r}\mathrm{o}\mathrm{u}\mathrm{g}\mathrm{h}\mathrm{t} \mathrm{s}\mathrm{t}\mathrm{r}\mathrm{e}\mathrm{s}\mathrm{s}-\mathrm{r}\mathrm{e}\mathrm{w}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{r}\mathrm{i}\mathrm{n}\mathrm{g} \mathrm{a}\mathrm{t} \mathrm{p}\mathrm{o}\mathrm{i}\mathrm{n}\mathrm{t} \mathrm{i}}{\mathrm{M}\mathrm{e}\mathrm{a}\mathrm{n} \mathrm{t}\mathrm{r}\mathrm{a}\mathrm{i}\mathrm{t} \mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e} \mathrm{i}\mathrm{n} \mathrm{w}\mathrm{e}\mathrm{l}\mathrm{l} \mathrm{w}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{r}\mathrm{e}\mathrm{d} \mathrm{c}\mathrm{o}\mathrm{n}\mathrm{d}\mathrm{i}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{s} \mathrm{a}\mathrm{t} \mathrm{p}\mathrm{o}\mathrm{i}\mathrm{n}\mathrm{t} \mathrm{i}}},$$

where i represents either measurement point A or B. At physiological maturity, panicle length, panicle width and panicle exertion were also measured using a 30 cm ruler. Yield traits, including grain yield harvested from the pot, grain weight after threshing and 100-seed weight, were measured after drying using a digital electronic balance (SF-400, maximum capacity 5 kg, readability 1 g, Zhejiang, China). To obtain the above-ground biomass yield, all three plants were cut at the soil level after harvesting the panicles, dried at 70 °C in an oven for 3 days, and then weighed using the same weighing scale. The harvest index was calculated as the ratio of grain yield to total aboveground biomass, expressed as a percentage (%).

2.5. Statistical Analyses

Statistical analyses were performed following the procedure described by [33]. The collected data were entered into Microsoft Excel spreadsheets, summarized, and saved as comma-delimited (CSV) files, then imported into R software (version 4.3.1) [34] for all the statistical analyses. Homogeneity of variances and normality of the residuals were tested using the Shapiro–Wilk test. A generalized linear model, implemented with the lmerTest package [35], was used to obtain the estimated marginal means (EMMs), which were used in multivariate analyses and trait comparisons across genotypes and watering regimes. Furthermore, Student’s t-tests were performed to assess statistical differences in yield traits between the two watering regimes. Principal component analysis (PCA) based on the correlation matrix was performed using the prcomp () function from R’s base stats package, which computes principal components by decomposing the data matrix into uncorrelated components. The eigenvectors derived from the PCA were used to identify the variables that had a strong relationship with a specific principal component. The PC biplot was then generated using the ggbiplot package in R [36] to describe and group sorghum genotypes based on their response to drought and rewatering. Yield improvement and stability are the ultimate goals of any breeding program. Tolerance/resistance indices were calculated following the methodology outlined by [37] and analyzed using the Hmisc package [38] to assess their correlations with each other and with grain yield under both stress-recovery and well-watered conditions. Indices showing strong correlations with grain yield in both conditions were considered key predictors of genotypic drought recovery responses.

For the ranking of genotypes based on recovery potential, multiple drought selection indices were computed and used rather than relying on a single criterion, as noted by [39]. For each genotype, ranks were assigned across all indices, and the mean rank ($\overline{\mathrm{R}}$), standard deviation of ranks (σR), and rank sum (ΣR) were calculated. The rank sum (ΣR = $\overline{\mathrm{R}}$ + σR) served as the final ranking criterion, with lower values indicating superior recovery performance and higher values denoting poorer recovery. Using this approach, genotypes were ordered from those exhibiting the best recovery (lowest rank sums) to those with the weakest recovery (highest rank sums). The calculated tolerance and resistance indices were further analyzed to explore their intercorrelations and their relationship with grain yield under both drought stress-rewatering and well-watered conditions [37,40]. This approach facilitated the determination of the effective selection indices.

3. Results

3.1. Effect of Drought Stress and Rewatering on Morphological, Agronomic and Functional Traits

The agro-physiological performance of sorghum genotypes varied markedly between stress-rewatering and well-watered conditions (

Table 2. Key agronomic and functional stress response traits measured in the study.

GTP	BMS (g)	BMW (g)	DWS (g)	DWW (g)	GWS (g)	GWW (g)	HSWS (g)	HSWW (g)	HIS	HIW	SPADS	SPADW	FD50S	FD50W
E1	67.00	126.00	44.33	63.00	31.33	51.67	2.30	2.45	46.77	41.01	35.01	36.33	73	69
E2	59.67	174.33	57.67	74.67	38.00	60.67	2.10	2.88	63.69	34.8	35.43	41.27	76	63
E3	134.33	116.67	41.33	58.00	31.67	45.67	3.30	2.24	23.57	39.14	37.13	36.50	74	60
E4	64.50	118.33	34.50	50.00	20.67	37.67	0.97	1.60	32.04	31.83	35.68	39.88	72	61
E5	60.33	103.00	52.00	80.00	37.33	56.67	1.28	2.37	61.88	55.02	38.51	39.07	73	64
E6	120.00	110.33	36.67	62.67	30.33	49.00	2.75	2.35	25.28	44.41	36.34	39.25	78	59
E7	45.00	85.50	4.67	38.00	3.33	31.33	0.55	2.03	7.41	36.64	30.15	38.71	70	63
E9	96.33	148.67	27.33	56.33	20.00	41.33	2.99	2.66	20.76	27.80	38.40	38.39	75	64
E8	105.67	135.50	31.67	65.33	33.33	50.67	1.88	2.71	31.55	37.39	38.67	38.78	82	66
E11	54.33	90.67	36.67	84.00	28.67	73.00	1.33	2.46	52.76	80.51	34.93	39.05	71	66
E10	83.67	114.67	40.00	57.67	32.00	42.33	2.25	1.68	38.25	36.91	37.06	37.17	67	60
E12	84.00	153.67	35.33	44.00	27.67	32.00	1.45	2.15	32.94	20.82	39.75	43.18	69	60
E13	66.33	138.33	48.67	60.33	37.00	45.67	1.55	2.79	55.78	33.02	35.31	36.42	74	60
E17	59.33	108.67	47.33	77.67	30.33	54.00	1.40	2.34	51.12	49.69	35.22	38.70	68	61
E14	72.33	130.50	42.33	85.67	26.67	69.33	1.03	2.14	36.87	53.13	35.95	41.15	73	62
E15	66.00	129.33	45.00	61.00	33.67	52.33	1.94	2.06	51.01	40.46	37.32	40.31	72	60
E16	73.00	106.33	61.33	91.67	45.00	79.67	1.47	2.13	61.64	74.93	35.87	37.45	74	62
E18	56.00	93.67	36.00	72.33	25.67	57.33	1.59	2.18	45.83	61.20	35.43	38.04	77	64
Average	75.99	121.34	40.16	65.69	29.59	51.69	1.79	2.29	41.06	44.37	36.23	38.87	73	62
Change (∆T)	37%		39%		43%		22%		7%		7%		11 days

GTP: Genotype, BM_s: Biomass yield under stress-rewatering, BM_w: Biomass yield under well-watering, DW_s: Dry weight under stress-rewatering, DW_w: Dry weight under well-watering, GW_s: Grain weight under stress-rewatering, GW_w: Grain weight under well-watering, HSW_s: 100-seed weight under stress-rewatering, HSW_w: 100-seed weight under well-watering, HI_s: Harvest index under stress-rewatering, HI_w: Harvest index under well-watering, SPAD_s (Soil–Plant Analysis Development; measure of relative chlorophyll content) under stress-rewatering, SPAD_w: SPAD under well-watering, FD_50s: Days to 50% flowering under stress-rewatering, FD_50w: Days to 50% flowering under well-rewatering, Change (∆T): Percentage reduction in mean trait performance under stress-rewatering relative to well-watered, days to 50% flowering is expressed as absolute increase in number of days. All weight related traits were measured in grams (g).

). A similar pattern was observed for morphological and morpho-physiological stress-adaptive traits evaluated in the study (Appendix A). Drought stress led to a notable reduction in all measured traits compared to the well-watered control, underscoring the severe impact of water limitation on sorghum growth and yield

Among the yield traits, the results of the t-test indicated that the majority of the measured traits were strongly affected by the watering regime. Biomass, dry weight and grain weight were significantly higher under the well-watered regime compared to water-stressed conditions (p < 0.0001). The 100-seed weight was also significantly affected by the watering regime, although at a lower level of significance (p < 0.05, *). These results indicate that water stress has a substantial impact on most yield-related traits in sorghum (Figure 2).

3.2. Variation in Drought Recovery Responses Among Sorghum Genotypes Based on Plant Height (PLH), Relative Chlorophyll Content (SPAD), Stem Diameter (SD) and Internode Length (INTL)

The variation in genotypes’ responses was evident during drought stress and recovery phases (Figure 3). Drought stress caused reductions in SPAD value and stem diameter during stages 1–4 of treatment (T) and declines in plant height and internode length during stages 1–3 (T). However, following rewatering beyond these stages, these traits exhibited greater variability among genotypes during the recovery phase compared to the stress period.

Genotypes E15 and E12, from the susceptible and moderately resistant groups, respectively, consistently maintained high SPAD values (Figure 3ii) throughout both stress and recovery phases, indicating strong potential to sustain photosynthetic activity. A similar trend was observed in plant height (Figure 3i) for these genotypes. In contrast, E7 exhibited a rapid decline in SPAD value during the stress phase, with minimal recovery after rewatering. E18 exhibited strong performance under both stress and well-watered conditions, particularly in maintaining stem diameter, but demonstrated limited internode length (Figure 3iv) during the recovery, indicating a unique response in structural growth. Meanwhile, E14 and E3 showed rapid increases in stem diameter (Figure 3iii) upon rewatering. Overall, the genotypes displayed diverse recovery mechanisms, with some genotypes, like E15, excelling in tissue rehydration and quickly resuming growth, while others, such as E7, showed more limited recovery capacity.

3.3. Evaluation of Drought Recovery Indices to Determine the Recovery Potential of Sorghum Genotypes Based on Post-Stress Response Traits

The values of DRI varied considerably among genotypes, indicating differing recovery efficiencies (

Table 3. Drought recovery indices for internode length, relative chlorophyll content, stem diameter and plant height across the different genotypes.

	Drought Recovery Index (DRI)
GTP	INTL	SPAD	SD	PH
E1	−0.35	0.09	0.20	−0.46
E2	−0.31	−0.09	−0.30	−0.50
E3	−0.37	0.01	0.28	−0.30
E4	−0.11	−0.08	−0.22	−0.37
E5	−0.30	0.03	−0.31	−0.35
E6	−0.39	0.02	−0.07	−0.27
E7	−0.10	−0.40	−0.13	−0.28
E9	−0.25	0.09	−0.26	−0.33
E8	−0.32	0.04	−0.21	−0.17
E11	−0.35	−0.05	−0.05	−0.11
E10	−0.22	0.11	−0.25	−0.20
E12	−0.32	−0.03	−0.02	−0.47
E13	−0.27	0.13	−0.22	−0.18
E17	−0.25	0.00	−0.15	−0.33
E14	−0.15	−0.02	−0.01	−0.27
E16	−0.28	0.07	−0.16	−0.43
E15	−0.29	0.07	−0.19	−0.40
E18	−0.48	−0.04	−0.12	−0.60

GTP: Genotype, INTL: Internode length, SPAD: Relative chlorophyll content, SD: Stem diameter, PH: Plant height.

). Genotypes with lower DRI values exhibited poor recovery potential across the assessed traits.

Generally, the genotypes displayed strong recovery for relative chlorophyll content (SPAD) and stem diameter, while exhibiting relatively poor recovery for internode length and plant height. Relative chlorophyll content recovery was most pronounced in the genotypes E13 (0.13), E10 (0.11), E9 (0.09), and E1 (0.09). Conversely, E7 and E2 displayed the poorest recovery, with DRIs of −0.40 and −0.09, respectively. For plant height, genotypes E11 (−0.11), E8 (−0.17), E13 (−0.18), and E10 (−0.20) exhibited relatively good recovery. However, E18 (−0.60) and E2 (−0.50) demonstrated the weakest recovery. Stem diameter is an indication of the potential to rehydrate the tissues after drought stress. Genotypes E3 (0.28) and E1 (0.20) exhibited good rehydration capacity, while E5 (−0.31) and E2 (−0.30) had the poorest.

3.4. Biplot Analysis of Sorghum Genotypes to Visualize Trait Contributions and Identify Lines with Strong Performance Under Stress-Rewatering and Non-Stress Conditions

The two principal components explained 48% of the total variation in the drought stress-rewatering treatment and 46% under well-watered treatment. The biplots clustered genotypes according to their responses under both watering regimes (Figure 4).

In the drought stress-rewatering regime, the genotypes were categorized into six distinct clusters (Figure 4A). Specifically, cluster 4 included genotypes E3, E9, E8 and E6. These genotypes were characterized by high biomass yield, 100-seed weight, and generally greater leaf numbers, but they exhibited a lower harvest index. Genotypes E2 and E13 were grouped in cluster 5 and closely associated with E16, which uniquely formed cluster 2. These genotypes exhibited the highest values for key yield traits, including dry weight, grain weight, harvest index, panicle length, and panicle width. They also demonstrated a rapid rewatering response, achieving the lowest mean recovery scores (2.00) within 12 h of rehydration.

Cluster 1, represented solely by genotype E7, exhibited distinct and unfavorable traits. It recorded the lowest grain yield, harvest index, 100-seed weight, and biomass yield, along with the poorest recovery 12 h post-rewatering. Additionally, this genotype had the highest degree of leaf rolling, a manifestation of drought susceptibility, the lowest relative chlorophyll content, and the smallest number of green leaves. E7, therefore, stood out as the most susceptible genotype, displaying the weakest recovery potential.

Under well-watered conditions, the genotypes exhibited limited clustering, forming only two distinct groups (Figure 4B). Clustering was largely driven by yield potential, with cluster 1 comprising genotypes that produced the highest grain yield, dry weight, and other yield-related traits. Cluster 2 included genotypes with comparatively lower yield performance. Notably, within cluster 2, the genotype E12 displayed a distinct response, separating from the other members of the cluster. This genotype recorded the highest relative chlorophyll content, plant height and biomass yield, clearly standing out from all other genotypes.

Overall, the PCA results revealed that the genotypes exhibited diverse recovery patterns, reflected in the distinct clustering, thereby demonstrating a high degree of variability in their responses to drought and rewatering.

3.5. Ranking of Sorghum Genotypes to Identify Lines with Superior Drought Recovery Using Multiple Indices and the Identification of Effective Selection Indices

The drought tolerance indices exhibited diverse patterns of correlation with grain yield under both stress-rewatering and well-watered conditions, with relationships differing in strength and direction (

Table 4. Pearson correlation coefficients among different drought tolerance and susceptibility indices.

	Ys	Yp	SSI	GM	TOL	MPI	YSI	HM	STI	YI	MB	GMB	BI	BSI
Ys	1
Yp	0.58 *	1
SSI	−0.68 **	0.16	1
GM	0.92 ***	0.85 ***	−0.37	1
TOL	−0.12	0.74 ***	0.75 ***	0.28	1
MP1	0.84 ***	0.93 ***	−0.20	0.98 ***	0.44	1
YSI	0.68 **	−0.16	−1.00 ***	0.37	−0.75 ***	0.20	1
HM	0.96 ***	0.77 ***	−0.48 *	0.99 ***	0.14	0.95 ***	0.48 *	1
STI	0.96 ***	0.77 ***	−0.48 *	0.99 ***	0.14	0.95 ***	0.48 *	1.00 ***	1
YI	1.00 ***	0.58 *	−0.68 **	0.92 ***	−0.12	0.84 ***	0.68 **	0.96 ***	0.96 ***	1
MB	0.29	−0.23	−0.60 **	0.10	−0.53 *	−0.02	0.60 **	0.18	0.18	0.29	1
GMB	0.27	−0.24	−0.58 *	0.08	−0.52 *	−0.04	0.58 *	0.15	0.15	0.27	0.98 ***	1
BI	0.18	−0.20	−0.42	0.04	−0.39	−0.05	0.42	0.10	0.10	0.18	0.79 ***	0.88 ***	1
BSI	0.08	−0.08	−0.16	0.02	−0.16	−0.02	0.16	0.05	0.05	0.08	0.40	0.53 *	0.87 ***	1

Ys: Grain yield under stress, Yp: Grain yield under well watering, GM: Geometric mean, SSI: Stress susceptibility index, TOL: Tolerance, MPI: Mean productivity index, YSI: Yield Stability Index, HM: Harmonic Mean, STI: Stress tolerance Index, YI: Yield Index, MB: Mean biomass, GMB: Geometric mean biomass, BI: Biomass index, BSI: Biomass Stability Index. *** = p ≤ 0.001, ** = p ≤ 0.005 and * = p < 0.05.

).

The results show that yield under stress-rewatering (Ys) was strongly and positively associated with yield under well-watered conditions (Yp), with a correlation coefficient of 0.58. Several indices, including Geometric Mean (GM), Mean Productivity Index (MPI), Harmonic Mean (HM), Stress Tolerance Index (STI), and Yield Index (YI), showed strong positive correlations with grain yield in both watering regimes. In contrast, the stress susceptibility index (SSI) and Yield Stability Index (YSI) were significantly linked only to yield under stress, with correlation values of −0.68 and 0.68, respectively. While biomass-related indices such as Mean Biomass (MB), Geometric Mean Biomass (GMB), Biomass Index (BI), and Biomass Stability Index (BSI) did not have statistical significance, they tended to correlate positively with yield under stress and negatively with grain yield in well-watered conditions.

Each genotype was ranked based on its performance across the different drought selection indices. The initial ranking considered only grain yield-related indices (

Table 5. Ranking of sorghum genotypes from strongest to weakest recovery based on grain yield-related indices.

Genotype’s Rank (R) for Each Index
GTP	GM	SSI	TOL	MPI	YSI	HM	STI	YI	$\overline{\mathbf{R}}$	σR	ΣR	F.R
E5	3	5	9	5	5	3	3	3	4.50	2.07	6.57	1
E15	6	7	7	6	7	5	5	5	6.00	0.93	6.93	2
E8	8	6	6	8	6	7	7	6	6.75	0.89	7.64	3
E13	7	2	2	11	2	6	6	4	5.00	3.16	8.16	4
E2	2	8	12	3	8	2	2	2	4.88	3.91	8.78	5
E1	10	10	10	9	10	8	8	9	9.31	0.88	10.2	6
E6	11	9	8	12	9	11	11	10	10.19	1.36	11.55	7
E16	1	11	16	1	11	1	1	1	5.38	6.23	11.61	8
E17	9	12	13	7	12	9	9	10	10.19	2.03	12.22	9
E3	13	4	4	13	4	12	12	8	8.75	4.23	12.98	10
E10	14	3	3	14	3	13	13	7	8.75	5.26	14.01	11
E18	12	15	15	9	15	14	14	15	13.69	1.98	15.67	12
E11	4	16	18	2	16	4	4	12	9.50	6.65	16.15	13
E9	16	14	11	15	14	16	16	17	14.88	1.89	16.76	14
E12	15	1	1	16	1	15	15	13	9.63	7.19	16.82	15
E14	5	17	17	4	17	10	10	14	11.75	5.34	17.09	16
E4	17	13	5	17	13	17	17	16	14.38	4.17	18.55	17
E7	18	18	14	18	18	18	18	18	17.50	1.41	18.91	18

GTP: Genotype, GM: Geometric mean, SSI: Stress susceptibility index, TOL: Tolerance, MPI: Mean productivity index, YSI: Yield Stability Index, HM: Harmonic Mean, STI: Stress Tolerance Index, YI: Yield Index, $\overline{\mathrm{R}}$: Mean Rank, σR: Standard deviation of Rank, ΣR: Rank sum, F.R: Final/overall rank of the genotype.

), followed by a final ranking that incorporated both grain yield- and biomass-related indices (

Table 6. Ranking of sorghum genotypes from strongest to weakest recovery based on grain and biomass yield-related indices.

Genotype’s Rank (R) for Each Index
GTP	GM	SSI	TOL	MPI	YSI	HM	STI	YI	MB	GMB	BI	BSI	$\overline{\mathbf{R}}$	σR	ΣR	F.R
E8	8	6	6	8	6	7	7	6	3	3	3	3	5.50	1.98	7.48	1
E15	6	7	7	6	7	5	5	5	10	10	11	16	7.92	3.29	11.20	2
E3	13	4	4	13	4	12	12	8	1	1	1	1	6.17	5.10	11.26	3
E13	7	2	2	11	2	6	6	4	7	9	10	17	6.92	4.42	11.34	4
E1	10	10	10	9	10	8	8	9	11	11	9	14	9.96	1.60	11.56	5
E6	11	9	8	12	9	11	11	10	6	4	2	2	7.96	3.61	11.57	6
E5	3	5	9	5	5	3	3	3	15	15	13	9	7.33	4.74	12.07	7
E2	2	8	12	3	8	2	2	2	5	6	14	18	6.83	5.37	12.21	8
E16	1	11	16	1	11	1	1	1	13	12	7	5	6.67	5.69	12.36	9
E10	14	3	3	14	3	13	13	7	9	7	6	4	8.00	4.47	12.47	10
E17 (Check)	9	12	13	7	12	9	9	10	14	14	15	12	11.38	2.48	13.85	11
E12	15	1	1	16	1	15	15	13	4	5	5	11	8.50	6.20	14.70	12
E14	5	17	17	4	17	10	10	14	8	8	8	10	10.67	4.58	15.25	13
E18	12	15	15	9	15	14	14	15	16	16	16	8	13.79	2.62	16.42	14
E9	16	14	11	15	14	16	16	17	2	2	4	6	11.08	5.88	16.97	15
E4 (Check)	17	13	5	17	13	17	17	16	12	13	12	13	13.75	3.47	17.22	16
E11	4	16	18	2	16	4	4	12	17	17	17	7	11.17	6.41	17.57	17
E7	18	18	14	18	18	18	18	18	18	18	18	15	17.42	1.38	18.80	18

GTP: Genotype, GM: Geometric mean, SSI: Stress susceptibility index, TOL: Tolerance, MPI: Mean productivity index, YSI: Yield Stability Index, HM: Harmonic Mean, STI: Stress tolerance Index, YI: Yield Index, MB: Mean biomass, GMB: Geometric mean biomass, BI: Biomass index, BSI: Biomass Stability Index, $\overline{\mathrm{R}}$: Mean Rank, σR: Standard deviation of Rank, ΣR: Rank sum, F.R: Final/overall rank of the genotype.

).

3.6. Classification of Genotypes by Performance Under Stress-Rewatering and Non-Stress Conditions Using Drought Selection Indices

Based on the classification approach outlined by [41] and as applied by [39], genotypes were grouped into four categories according to their grain yield performance under drought stress-rewatering (hereafter referred to as stress) and well-watered (non-stress) conditions, using the drought selection indices (

Table 7. Grouping of the sorghum genotypes according to their performance under different moisture conditions.

Group	GTP	GWw (g)	GWs (g)
Stress and non-stress (A)	E16	79.67	45.00
	E2	60.67	38.00
	E5	56.67	37.33
	E17	54.00	30.33
	E15	52.33	33.67
Non-stress conditions (B)	E11	73.00	28.67
	E14	69.33	26.67
	E18	57.33	25.67
Stress conditions (C)	E1	51.67	31.33
	E8	50.67	33.33
	E6	49.00	30.33
	E13	45.7	37.00
	E3	45.67	31.67
	E10	42.33	32.00
Poor performer in both stress and non-stress (D)	E7	31.33	3.33
	E4	37.67	20.67
	E12	32.00	27.67
	E9	41.33	20.00
Mean Grain yield		51.69	29.59

GTP: Genotype, GW_w: Grain yield in grams under non-stress, GW_s: Grain yield in grams under stress.

). Group A comprised genotypes with high yields in both stress and non-stress conditions. These were primarily distinguished by high STI, GM, YI and HM, reflecting strong performance across both environments. Group B included those producing high yields exclusively under non-stress conditions. They were characterized by high MPI and HM, showing good productivity under optimal watering, but with high TOL and SSI, which indicated strong sensitivity to stress. Group C consisted of genotypes maintaining good yields under stress. These genotypes were defined by high Ys, YSI, and YI, showcasing strong drought tolerance, while moderate MPI showed their average performance under non-stress conditions. Finally, group D encompassed those genotypes with poor performance in both stress and non-stress conditions. These were defined by low GM, HM, and MPI, reflecting consistently weak productivity.

4. Discussion of Results

This study aimed to evaluate the drought recovery potential of diverse sorghum genotypes following drought stress, in order to identify the key traits and genotypes that contribute to resilience under fluctuating water availability. Understanding recovery capacity is critical for breeding sorghum varieties capable of maintaining productivity under the increasingly variable rainfall patterns associated with climate change.

The study revealed significant genotypic variation in drought recovery potential, with important implications for breeding programs. Although portable and field-applicable wet-lab diagnostics, such as those used for pathogen detection [42] and seed-based genotyping [43], are advancing rapidly, effective and precise approaches for evaluating morphological and physiological recovery from abiotic stresses, such as drought, remain underdeveloped. This study addresses this gap by applying a practical, multi-trait-based screening method to assess drought recovery potential in sorghum. Drought stress diminished critical yield traits, including dry weight, grain weight and 100-seed weight. These reductions, observed in genotypes E7, E9 and E4, may be ascribed to poor panicle emergence, panicle blasting, ovary abortion and decreases in panicle size and grain number, traits that directly impact grain yield [44,45]. Despite post-stress growth recovery, biomass yield remained lower in drought-stressed plants compared to the control plants, consistent with the responses observed in many plant species subjected to drought stress [46,47,48]. As noted by Abid et al. (2016), this discrepancy reflects pre-drought limitations that constrain the capacity for full recovery. Notably, drought stress delayed flowering by an average of 11 days, contrasting with previous reports of accelerated flowering under drought stress in other plant species [44,49].

Plant growth slowed under drought stress but recovered across all genotypes during the rewatering phase, reflecting the high plasticity of sorghum’s growth. Growth reduction during stress was mainly attributed to a decrease in cell expansion and elongation [50,51]. Typically, this growth retardation reflects a shift in the energy budget, where maintenance processes take priority, leaving less energy available for growth. The genotypes E15 and E12 were particularly notable for sustaining relatively high SPAD values during both the stress and recovery periods, underscoring their drought tolerance characteristics. This observation is supported by prior studies showing that drought-tolerant genotypes tend to maintain higher chlorophyll levels under stress compared to susceptible ones [52,53,54]. The rapid drought-induced reduction in SPAD values across genotypes may indicate a significant loss in photosynthetic functionality at PSI and PSII reaction centers [46]. However, the rapid recovery of plants after rewatering, especially genotypes E15, E1, E13 and E10, suggests that this loss may serve a regulatory rather than a purely damaging function [46,55].

Dehydration is a reversible process [55], consistent with our findings that stem diameter decreased significantly during drought stress but increased across all genotypes during the recovery phase. The heightened variability in responses during the recovery phase, compared to the stress period, highlights the diverse recovery patterns and capacities across the different genotypes.

4.1. Shifts in Traits’ Significance as Adaptive Responses to Drought Stress and Recovery

Plants activate a suite of adaptive mechanisms in response to drought stress and rewatering, encompassing molecular and biochemical changes as well as complex physiological and morphological adjustments [56,57]. However, the extent of plant growth recovery following rewatering may depend on the intensity and duration of the preceding drought [56]. Grain weight, dry weight, harvest index, and panicle size-key yield-contributing traits-were grouped as the main contributors to cluster 5, which comprised genotypes E2 and E13, and were also closely linked to E16. The rapid rehydration response observed in these genotypes, likely reflecting faster recovery of the photosynthetic apparatus and thus higher photosynthetic rates, may explain their higher yields post-rewatering. While leaf rolling is known to reduce transpiration and protect the photosynthetic machinery from photodamage [50,58], our findings indicated that a high degree of leaf rolling was linked to the high susceptibility of genotype E7. As leaf rolling reduces the effective leaf area for photosynthesis [10,58], this susceptibility may be linked to reduced carbon dioxide assimilation, a tradeoff for water conservation in plants [59,60,61]. Biomass yield, on the other hand, showed stronger correlations with leaf number, leaf area, relative chlorophyll content, 100-seed weight, and days to 50% flowering. These traits were associated with genotypes E3, E6, E9 and E8, which were grouped in cluster 4. The 100-seed weight is a key yield component that reflects the source–sink relationship of photo-assimilates during the grain filling stage [62]. The strong positive correlation between 100-seed weight and biomass yield was similarly observed by [63]. Previous studies have reported a strong positive correlation between 100-seed weight and other yield components, such as dry weight, grain weight, and harvest index [64,65,66]. However, no such correlation was observed in this study. Despite the lower productivity of genotypes E12 and E9, their ability to maintain high biomass yield and relative chlorophyll content under both stress and well-watered conditions makes them particularly promising for forage breeding. Therefore, the grouping of traits under drought stress into distinct drought recovery patterns, as shown in the biplots, highlights the varying capacities of genotypes to recover after a drought event.

4.2. Strategy for Selecting Desirable Genotypes Using Drought Tolerance/Resistance Indices

Genotypes exhibit varied responses to drought stress [40,67]. Given this, various selection criteria have been proposed to identify genotypes based on their performance in both stress and non-stress conditions [37,39,40,44]. Tolerant genotypes are characterized by low SSI and TOL values, along with high MP, HM, GMP, STI, YI, and YSI values [37,39,67]. Considering the rank sum, genotypes E5, E15, E8, E13, E2, E1, E6 and E16 demonstrated the best recovery potential, outperforming the positive check E17. This was further supported by the biplot analysis, highlighting their high grain yield under stress and non-stress conditions. Conversely, genotype E7 emerged as the most susceptible, exhibiting the poorest recovery potential and performing below E4, the negative check. Based on both grain and biomass indices, the genotypes assumed new ranks. Two additional genotypes, E3 and E10, emerged among the previously high-performing genotypes, surpassing the positive check. Meanwhile, genotype E11, alongside E7, ranked below E4. Comparable to the findings of [68], we observed a highly significant positive correlation between grain yield under both stress and non-stress conditions. This suggests that during recovery, grain yield performance in optimal conditions serves as a reliable predictor for yield under stress, as also supported by previous studies [39,69].

An effective selection index should have a significant relationship with grain yield in both stress and non-stress conditions [70,71]. The correlation matrix indicated a strong positive association between grain yield in stress conditions (Ys) and in non-stress conditions (Yp), along with indices such as the Geometric Mean (GM), Mean Productivity Index (MPI), Harmonic Mean (HM), Stress Tolerance Index (STI), and Yield Index (YI). This indicates that these criteria were effective in distinguishing drought-tolerant genotypes that maintained high grain yield across both watering regimes. Consequently, these indices were deemed suitable for selecting genotypes with strong recovery potential. Conversely, biomass indices appeared to have limited relevance to grain yield performance.

5. Conclusions

This study evaluated the responses of 18 sorghum genotypes to drought stress and subsequent rewatering to determine their drought recovery potential. Our findings confirmed genotype-specific recovery patterns and the traits that are key to achieving high yields under intermittent water supply. Genotypes such as E16, E2 and E13 demonstrated rapid rehydration and compensatory growth to recover from drought stress and maximize yield. Such a good plasticity suggests that these genotypes are particularly well-suited for agroecologies which experience intense drought stress followed by short periods of heavy rainfall like the case of north-eastern Uganda. Conversely, genotypes such as E15, E5, and E8 achieved higher yields by maintaining higher relative chlorophyll content, which extended their photosynthetic activity during stress and recovery. Based on stress tolerance indices, genotypes suitable for various moisture conditions were identified, with those performing well in both stress and non-stress conditions (Category A), proving particularly valuable under fluctuating water conditions due to their yield stability and adaptability. These genotypes show strong potential as parents for drought resilience breeding efforts. In contrast, genotype E7 exhibited the poorest recovery response, while E11 experienced drastic reductions in performance during drought stress. These two genotypes could serve as reliable negative drought checks in the breeding program. Going forward, understanding the genetic control of the observed recovery responses in selected genotypes will be essential in facilitating the precise introgression of desirable recovery traits in elite breeding materials.