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Article

The Effect of Maturity Period on Grain Yield, Biomass Production, and Harvest Index in Sorghum

by
Byamungu Lincoln Zabuloni
*,
Hussein Shimelis
and
Seltene Abady Tesfamariam
African Centre for Crop Improvement, School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Private Bag X01, Scottsville, Pietermaritzburg 3209, South Africa
*
Author to whom correspondence should be addressed.
Agronomy 2026, 16(6), 610; https://doi.org/10.3390/agronomy16060610
Submission received: 6 February 2026 / Revised: 4 March 2026 / Accepted: 11 March 2026 / Published: 12 March 2026
(This article belongs to the Section Farming Sustainability)
Versions Notes

Abstract

Sorghum is a climate-resilient crop; however, recurrent drought and shorter rainy seasons limit its productivity. Sorghum grain yield (GY), biomass production (AGB), and harvest index (HI) are influenced by the genetic composition and plasticity of the maturity period. Limited studies have examined the effect of the maturity period on these traits. This study evaluated 106 diverse sorghum genotypes to determine the effect of maturity period on these traits to identify contrasting genotypes for breeding and production. Field trials were conducted during the 2023/24 and 2024/25 seasons using a 10 × 11 alpha lattice design. During season I, late-maturing genotypes produced GY and AGB values 28.8% and 51.2% higher than early-maturing genotypes and 34.9% and 54.4% higher than medium-maturing genotypes, respectively, but recorded 19.24% and 12.28% lower HIs than the early- and medium-maturing genotypes, respectively. In season II, late-maturing genotypes had a 10.43% and 34.49% lower GY and HI, respectively, yet a 92.69% higher AGB than early-maturing genotypes. Compared with medium-maturing types, late-maturing genotypes had a 2.32% and 24.1% lower GY and HI, respectively, but a 52.96% higher AGB. The findings demonstrated that the effect of maturity period on sorghum GY, AGB, and HI is strongly influenced by the genetic potential for crop maturation and environmental conditions. Genotypes AS232, AS603, and AS580 combined early maturity and higher GY, AGB, and HI values, making them promising candidates for cultivation and breeding in drought-prone agroecologies.

1. Introduction

Sorghum [Sorghum bicolor (L.) Moench] is a drought-tolerant crop that originated in Africa and is now the fifth most important cereal crop globally after maize, rice, wheat, and barley [1]. It supports the livelihoods of more than 750 million people globally, primarily serving as a staple food in Sub-Saharan Africa (SSA) and Asia [2,3]. It contributes to nearly 70% of the daily calorie requirements in SSA and Asia [4]. Sorghum is valued as a hardy crop, which can produce harvestable grains under harsh and drought-prone conditions where other cereal crops fail [5,6]. These attributes make it suitable to mitigate the risks of crop losses posed by climate change and ideal for cultivation in arid and semi-arid regions.
Sorghum is used for food, feed, industrial raw materials, biogas and bioethanol production, and local, regional, and international trade [7]. It also has several human health benefits, such as being gluten-free and rich in its nutritional composition, including minerals and vitamins [8]. Sorghum grain is rich in phenolic compounds with various human health benefits against chronic diseases, such as diabetes, cancer, and obesity [9,10]. Sorghum has a C4 photosynthesis pathway and is valued for bioenergy and forage production owing to its efficient solar energy capture and conversion [11,12].
Annual global sorghum production is 61.46 million tons from an area of approximately 40.2 million hectares. The United States of America, Nigeria, India, Mexico, Brazil, and Ethiopia are the largest sorghum producers with an annual grain production of 8.07, 6.4, 4.74, 4.49, 4.43, and 4.01 million tons, in that order [8]. The mean grain yield of sorghum in SSA and Asia is low (about 1 ton /ha), compared to average yields of 3.8 and 2.5 tons/ha reported in the USA and globally, respectively [8,13]. In South Africa, over the past 25 years, sorghum production has declined by 72% due to several reasons [14].
The low yields of sorghum in Africa are mainly due to the dwindling rainy seasons and heat stress associated with climate change that affect food systems and livelihoods in semi-arid regions [15]. It is projected that due to climate change, sorghum production will decline by 32% globally and 41% in SSA by 2080 [3,16]. Therefore, there is a need for sustainable strategies to enhance sorghum productivity to improve food security and livelihoods in drought-prone areas.
Breeding early-maturing and high-yielding genotypes has been reported as one of the strategies to improve sorghum production and productivity while mitigating the impacts of drought stress in semi-arid regions [17]. Early-maturing ideotypes perform better in regions with short rainfall durations, as they complete their vegetative and reproductive growth stages before severe moisture deficit and high-temperature stresses. However, shorter vegetative and reproductive phases lead to yield penalties [18,19]. High grain yields are linked to better harvest indices [20]. Harvest index is defined as the ratio of an economic yield to total biomass and is a quantitative trait conditioned by polygenes [20,21]. Sorghum genotypes with high harvest indices play a crucial role in drought mitigation by optimising biomass allocation and improving grain yield efficiency [22].
Sorghum biomass production, grain yield, and harvest index performance are largely influenced by genetic composition and plasticity for harvest maturity [23,24]. The maturity period refers to the period spanning from crop establishment or planting to the completion of grain filling, marked by the attainment of peak grain weight [25]. Sorghum can be classified as early-maturing (90 to 110 days), intermediate (111 to 140 days), and late (over 140 days) based on its maturity period [25,26].
Increased grain yield and biomass production have been achieved through the adoption of late-maturing or full-season genotypes [23]. Short-duration genotypes often exhibit reduced grain yield and biomass potential compared with their late-maturing counterparts [27,28]. A prolonged maturity period provides more days for photosynthesis, enabling the crop to more efficiently use resources such as radiation, temperature, water, and soil nutrients, leading to higher grain yield and biomass production [29,30]. For example, [28] evaluated the effect of maturity duration on grain and dry matter yields of sorghum genotypes and reported an increase in panicle and biomass yields of 46.6% and 95.43% from the short-maturing and the late-maturing genotypes, respectively. Also, in favourable environments, late-maturing sorghum genotypes yielded 21.9% more grain than the early-maturing ones [31]. However, a non-significant relationship between sorghum maturity and grain yield, biomass, and harvest index were reported [24].
From the above reports, it can be deduced that the relationship between sorghum maturity period and the assessed yield-related traits is variable. Further, compared with wheat and maize crops, there are still limited studies that have examined and fully elucidated the effect of the maturity period on these traits to guide sorghum variety design for diverse market segments [32,33,34]. Therefore, this study evaluated 106 genetically diverse sorghum genotypes to determine the effects of maturity period on grain yield, biomass production, and harvest index and to identify contrasting genotypes for breeding and production. The results of the study will provide valuable insights to guide future sorghum breeding efforts aimed at developing locally adapted, high-yielding varieties with diverse product profiles based on maturity regimes.

2. Materials and Methods

2.1. Plant Materials, Study Sites, and Growing Seasons

The study used 106 genetically diverse sorghum genotypes. The genotypes were collected from various producing countries, including the United States of America, India, Ethiopia, and South Africa. The test genotypes were selected for their genetic variation in grain yield, maturity, and biomass production [35] to enable evaluation of the relationship between the maturity period and grain yield, biomass, and harvest index. Table 1 summarises the detailed descriptions of the genotypes used in this study. The genotypes were field-evaluated at the Ukulinga research farm of the University of KwaZulu-Natal in Pietermaritzburg (29°37′ S; 30°16′ E; 775 m a.s.l.) during the main crop season in 2023/24 and 2024/25 (October to March). The Pietermaritzburg area is semi-arid, with warm to hot summers and a 10-year average daily maximum temperature of 26.5 °C. The annual average rainfall is 790 mm, mostly occurring between October and April [36], while approximately 20% of precipitation occurs during winter [37]. The soil at the Ukulinga site is classified as loam, fertile and friable, with good drainage, with a pH of about 4.67, as described in Table 2. Table 3 presents the weather data for the experimental site during each growing season respectively.

2.2. Experimental Design

During each season, the test genotypes were evaluated using a 10 × 11 alpha lattice design with two replications to efficiently evaluate the large number of genotypes, reduce environmental variability, and increase the precision of genotype comparison. Each of the nine incomplete blocks contained 11 genotypes, while the 10th incomplete block had seven genotypes, which were allocated through randomization. Each genotype was planted on a three-metre-long row plot of 12 plants, with a 90 cm inter-row and 25 cm intra-row spacing. Two seeds were planted and thinned to one plant two weeks after emergence. Osmocote slow-release fertiliser (Dynatrade, Johanesburg, South Africa) was applied directly as a basal fertiliser at the following rates: 120 kg/ha of urea (18% N), 60 kg/ha of superphosphate (6% P2O5), and 60 kg/ha of potassium chloride (12% K2O). Hand weeding and supplementary irrigation were applied throughout the crop-growing season following the sorghum production guidelines in South Africa [39].

2.3. Data Collection

The following data were collected: days to 75% maturity (DTM), recorded as the number of days from planting to when 75% of the plants of a genotype in a plot had fully ripened, showing leaf senescence and formation of black layer at the base of the grain of each panicle; grain yield (GY) was measured on a plot basis, estimated in kg/m2 from the harvested grains of the middle 10 tagged plants in an experimental unit of 2.25 m2, and subsequently converted to tons per hectare (t/ha) after adjusting to 12.5% grain moisture content. Above-ground biomass (AGB) was recorded in kg/m2 as the mass of straw, oven-dried at 80 °C for 72 h, from the selected plants and converted to t/ha. The harvest index (HI) was calculated using the following formula:
HI   =   G Y G Y + A G B   ×   100
where HI is the harvest index (%), GY is the grain yield (t/ha), and AGB is the dry above-ground biomass (t/ha).

2.4. Data Analysis

2.4.1. Analysis of Variance (ANOVA)

The collected data were analysed using GenStat 23rd edition software, following the lattice procedure [40]. A combined analysis of variance was conducted across seasons after testing the homogeneity of variance using Levene’s procedure [41]. Trait mean values of the test genotypes were compared using Fisher’s least significant difference (LSD) method at a 5% significance level.

2.4.2. Classifying the Maturity Group

To classify the tested genotypes based on maturity groups, a normal distribution curve analysis was performed using IBM SPSS Statistics 30.0 software, following [42]. Using the mean and standard deviation (µ ± σ) of the maturity periods, the 106 genotypes were classified into three categories. The genotypes with maturity periods within the first standard deviation relative to the population mean were identified as medium-maturing, those below this range were identified as early-maturing, and those above it as late-maturing genotypes. Due to a significant genotype-by-season interaction (Table 3), the standard deviations for the maturity period differ between the two seasons. This could be attributed to environmental factors, including day and night temperature fluctuations, and rainfall variability, which can affect growth rate, flowering and grain-filling period. Two different standard deviations in genotype maturity periods in this study. In season I, using the mean and standard deviation of the days to 75% maturity (147 ± 10 days), the test genotypes with maturity periods within 137 and 157 days were categorised as medium-maturing, those below 137 days as early-maturing, and those above 157 days as late-maturing genotypes. In season II, using the mean and standard deviation (157 ± 13 days), the test genotypes maturing between 144 and 170 days were classified as medium-maturing, those below 147 as early-maturing, and those above 167 days as late-maturing.

2.4.3. Relative Performance of Test Genotypes for GY, AGB, and HI Based on DTM

The relative performances of the assessed genotypes based on the effect of DTM on GY, AGB, and HI were evaluated and calculated within and between maturity groups. Relative performance was computed following [43], using the formula: Kw (%) = ([wB-wA]/wA) × 100, where K represents the relative genotype performance as a percentage, w represents the traits GY, AGB, or HI, and B represents the value of the traits (w) of the late-maturing genotypes of each category, which were used as a reference. A represents the values of the traits (w) of the early-/medium-maturing genotypes. A negative value of K indicates that the late-maturing genotypes performed less favourably than the early-/medium-maturing ones, whereas a positive value signifies that the late-maturing genotypes exhibited superior performance compared to the early-/intermediate-maturing ones. To determine the relative performance of the genotypes within a given maturity group, the variable B corresponded to the value of the traits (w) of the latest-maturing genotype in that specific group, while A represented the value of the traits (w) of a given (early-maturing) genotype within the same group. When comparing the genotypes among the maturity groups (early-, medium-, and late-maturing), B corresponded to the mean value of the traits (w) of the late-maturing group, which served as the reference, and A represented the mean value of the traits (w) of the early- and medium-maturing groups.

3. Results

3.1. Analysis of Variance of the Effects of Genotype and Test Environment

Combined ANOVA revealed a significant (p < 0.001) effect of the genotype-by-season interaction and genotype main effects for all assessed traits (Table 4). This allowed genotype comparison and classification into comparative maturity groups.

3.2. Deciphering the Maturity Groups

Table 5, Table 6, Table 7 and Table 8 summarise the three maturity groups and performance in GY, AGB, and HI among the 106 sorghum entries evaluated at Ukulinga during the 2023/24 (season I) and 2024/2025 (season II) growing seasons, in that order. During the season I evaluation (Table 5), the assessed genotypes were classified into early-maturing (10% of the test genotypes, with a maturity period of 135 to 136 days), medium-maturing (77%, 137 to 157 days), and late-maturing (12%, 158 to 197 days). Early-maturing genotypes had a mean of 136 days, a grain yield of 3.03 t/ha, an above-ground biomass of 7.15 t/ha, and a harvest index of 32% (Table 5). Medium-maturing genotypes exhibited a mean DTM, GY, AGB, and HI of 145 days, 2.89 t/ha, 7 t/ha, and 29.5%, respectively (Table 6). Contrarily, late-maturing genotypes exhibited mean DTM, GY, AGB, and HI values of 169 days, 3.9 t/ha, 10.81 t/ha, and 25.87%, respectively (Table 8). During season II, the test genotypes were categorised into early-maturing (12% of test genotypes, 119 to 143 days), medium-maturing (74.5%, 144 to 170 days), and late-maturing (13%, 171 to 189 days) genotypes. Early-maturing types exhibited an average DTM, GY, AGB, and HI of 137 days, 3.6 t/ha, 7.35 t/ha, and 33.44%, respectively (Table 5). Medium-maturing genotypes recorded a mean DTM, GY, AGB, and HI of 156 days, 3.29 t/ha, 9.26 t/ha, and 28.86% (Table 7), while late-maturing genotypes had values of 177 days, 3.22 t/ha, 14.16 t/ha, and 21.9%, respectively (Table 8).

3.3. Maturity Groups and Relative Performance of the Test Genotypes for GY, AGB, and HI

Table 5 and Table 9 present the comparative responses of the test genotypes within and between the maturity groups for GY, AGB, and HI when assessed during the 2023/24 and 2024/25 growing seasons, respectively.

3.3.1. Relative Performance Within Early-Maturing Genotypes

During season I, the early-maturing genotypes exhibited negative relative performance values for GY (Table 5), indicating that they performed better than the late-maturing genotype in that category. The gain in GY ranged from 32% (ACCI-S-116) to 65% (ACCI-S-106) (Table 5). For AGB, 55% of the assessed early-maturing genotypes outperformed the late-maturing genotype in that group, displaying >10% higher biomass. However, only a few genotypes produced a 19% to 82% AGB, lower than the late-maturing genotype (AS362). The late-maturing genotype exhibited a comparatively lower HI than 80% of the early-maturing genotypes. The HI declined from 34% to 170% in the late-maturing genotype. In season II, 54% of the early-maturing genotypes exhibited a negative relative performance for GY, suggesting that they outyielded the late-maturing genotype of the group (Table 5). The gain in GY ranged from 13.38% (AS581) to 55% (AS603), with most of the early-maturing genotypes producing a >30% higher GY than the late-maturing genotype (AS628) of the group.
Table 5. Genotype per se performance for DTM, GY, AGB, and HI and relative performance among the early-maturing sorghum entries evaluated at Ukulinga during the 2023/24 and 2024/25 growing seasons.
Table 5. Genotype per se performance for DTM, GY, AGB, and HI and relative performance among the early-maturing sorghum entries evaluated at Ukulinga during the 2023/24 and 2024/25 growing seasons.
Sr. No.Maturity Group and Name of GenotypeTraitsRelative Performance [K (%)]Sr. No.Maturity Group and Name of GenotypeTraitsRelative Performance [K (%)]
Early MaturityDTMGYAGBHIKGYKAGBKHIEarly MaturityDTMGYAGBHIKGYKAGBKHI
Season ISeason II
1ACCI-S-1041354.228.7532.09−63.76−32.45−36.651AS2321194.606.4641.74−38.17104.27−57.69
2ACCI-S-1051353.927.9133.23−60.96−25.3−38.832AS6031226.3012.5533.43−54.855.22−47.17
3 ACCI-S-108 1362.263.1441.89−32.4788.26−51.473AS6001344.2310.2029.30−32.7229.39−39.72
4ACCI-S-1091362.644.4037.53−42.1934.31−45.844ACCI-S-1161362.117.5523.1234.8874.93−23.6
5ACCI-S-1121364.256.8838.29−64.02−14.09−46.925AS5811373.285.2239.10−13.38153.17−54.82
6ACCI-S-1161362.263.7437.59−32.2357.83−45.916ACCI-S-108137.52.185.0930.0230.23159.25−41.17
7ACCI-S-1181363.034.9737.93−49.6319.02−46.47ACCI-S-1181392.834.6737.340.61182.62−52.7
8AS5721363.477.7231.01−55.93−23.4−34.448ACCI-S-1091412.704.3738.765.56202.11−54.43
9AS6011361.4117.247.548.69−65.72169.69ACCI-S-1121414.658.1436.09−38.8562.29−51.07
10ACCI-S-106 136.54.387.9635.03−65.13−25.77−41.9710ACCI-S-1051414.617.6535.74−38.3472.53−50.59
11AS362136.51.535.9120.33 11AS5721411.894.8628.0450.34171.82−37.01
Max1374.3817.2441.89 12AS5731434.535.5844.39−37.13136.67−60.21
Min1351.413.147.54 13AS628143.52.8513.2017.66
SD0.491.093.849.90 Max143.56.3013.2044.39
Mean136 3.037.1532.04 Min1191.894.3717.66
SD7.651.322.977.58
Mean136.543.607.3533.44
Notes: DTM: Days to 75% maturity; AGB: above-ground biomass (t/ha); GY: grain yield (t/ha); HI: harvest index (%); Sr. No.: serial number; KGY: relative performance for grain yield; KABG: relative performance for above-ground biomass; KHI: relative performance for HI; Max: maximum; Min: minimum; SD: standard deviation. For AGB, the late-maturing genotype exhibited a >5% higher performance than all the assessed genotypes in that group. Conversely, for HI, the late-maturing genotype had an approximately 23% to 60% lower performance than all the evaluated genotypes in that category (Table 5).
Table 6. Genotype per se performance for DTM, GY, AGB, and HI and relative performance among the medium-maturing sorghum entries evaluated at Ukulinga during the 2023/24 growing season.
Table 6. Genotype per se performance for DTM, GY, AGB, and HI and relative performance among the medium-maturing sorghum entries evaluated at Ukulinga during the 2023/24 growing season.
Sr. No.Maturity Group and Name of GenotypeTraitsRelative Performance [K (%)]Sr. No.Maturity Group and Name of GenotypeTraitsRelative Performance [K (%)]
Medium MaturityDTMGYAGBHIKGYKAGBKHIMedium MaturityDTMGYAGBHIKGYKAGBKHI
1AS6301371.393.4028.48−26.84−1.02−18.6522AS6211411.964.3630.85−48.38−22.75−24.91
2AS567137.54.5410.5929.96−77.66−68.22−22.6723AS350141.52.033.5435.87−49.96−4.85−35.42
3 AS571137.51.515.1722.94−33.01−34.890.9824AS611141.51.799.9615.30−43.32−66.2451.36
4AS580137.53.826.7136.15−73.47−49.86−35.9125AS3481420.954.3018.086.89−21.6928.14
5AS427138.52.905.5934.05−64.99−39.82−31.9626AS3541421.293.3427.89−21.670.58−16.94
6AS616138.54.278.1034.77−76.26−58.45−33.3827AS5961423.0110.3822.14−66.34−67.594.61
7ACCI-S-1131391.663.8130.58−38.97−11.61−24.2428SS631421.083.1025.91−6.588.44−10.58
8AS3601392.494.3137.70−59.33−21.88−38.5529AS564142.51.544.1926.97−34.22−19.7−14.1
9AS5651393.659.3427.06−72.19−63.98−14.3730AS576142.52.565.5031.49−60.36−38.83−26.44
10AS5731394.058.0433.51−74.98−58.15−30.8631AS597142.52.185.3228.90−53.52−36.78−19.83
11AS5881391.835.0526.58−44.63−33.44−12.8532AS3411431.163.5325.15−12.8−4.83−7.89
12AS6171391.113.1326.24−8.997.46−11.733AS3551431.323.7925.78−23.02−11.27−10.15
13AS6251392.665.6432.00−61.84−40.39−27.634AS557143.53.247.0231.68−68.71−52.06−26.88
14AS6291391.112.9427.45−8.9814.35−15.6235AS575143.52.406.1928.13−57.76−45.64−17.63
15AS6321392.835.9332.33−64.22−43.25−28.3536AS578143.53.497.4232.19−70.96−54.66−28.02
16AS5701402.134.4532.93−52.37−24.47−29.6537AS3491441.302.3735.28−22.2141.98−34.33
17AS5791402.565.1633.22−60.47−34.81−30.2638AS587144.54.9410.2932.69−79.47−67.31−29.12
18AS5811401.673.8829.83−39.47−13.18−22.3339AS589144.53.209.8524.79−68.31−65.86−6.56
19AS3611411.722.4840.89−40.9935.51−43.3440AS593144.53.347.4731.83−69.64−54.94−27.22
20AS5691412.718.1924.85−62.58−58.94−6.7741AS615144.52.746.9128.23−62.97−51.28−17.93
21AS5851412.346.2327.34−56.78−46.01−15.2642AS618144.54.246.8138.38−76.07−50.61−39.63
Continue
43AS3471451.996.9221.94−48.95−51.45.5966AS5841501.365.6219.45−25.28−40.0919.08
44AS3521451.432.5335.90−29.332.81−35.4767AS5941503.897.8433.16−73.93−57.08−30.12
45AS558145.53.367.6430.57−69.87−55.95−24.2168AS6031506.3012.5533.43−83.92−73.19−30.71
46AS592145.51.199.7820.49−15.05−65.6113.0669AS599150.54.1013.4023.40−75.26−74.89−0.98
47AS627145.52.506.3327.81−59.38−46.87−16.770AS606150.52.476.4226.29−58.91−47.56−11.89
48AS5631464.4713.7024.87−77.34−75.45−6.8471AS1491510.863.7018.8917.78−8.9522.65
49AS6191463.715.1644.91−72.71−34.84−48.4172AS610151.52.226.7025.19−54.32−49.75−8.03
50AS6231464.379.7930.88−76.83−65.65−24.9673AS559152.52.664.8435.54−61.92−30.46−34.81
51AS6241467.3413.2735.60−86.18−74.65−34.9274AS568152.52.588.6622.99−60.79−61.150.78
52AS6781465.007.8836.17−79.74−57.31−35.9575AS342154.51.893.8134.08−46.34−11.76−32.03
53AS229146.56.428.2444.45−84.21−59.18−47.8876AS6041552.365.6329.55−57.07−40.21−21.61
54AS358 146.51.342.7632.68−24.1822.11−29.1177AS6281554.816.9540.90−78.92−51.57−43.36
55AS4241471.984.6529.94−48.81−27.61−22.6378AS6341551.996.8722.65−49.08−51.052.27
56AS5601473.008.2727.07−66.26−59.33−14.4279AS6561555.4013.7428.03−81.23−75.51−17.36
57AS5611473.576.3836.49−71.63−47.28−36.5180AS3561563.156.7231.92−67.83−49.94−27.41
58SS561473.8214.8420.46−73.44−77.3213.2281AS6491561.915.8823.65−46.83−42.75−2.04
59AS147147.52.549.3520.99−60.06−64.0210.3582AS353156.51.013.3623.17
60AS232147.54.606.4641.74−77.97−47.95−44.5 Max156.507.3420.5044.91
61AS4221484.318.8132.85−76.5−61.8−29.47 Min137.000.862.3715.30
62AS5621484.5110.3528.84−77.55−67.49−19.65 SD5.161.423.416.12
63AS5901485.0020.5019.00−79.72−83.5821.93 Mean145.092.897.0029.50
64AS6221485.1215.3824.99−80.21−78.12−7.29
65AS651148.54.138.8331.64−75.47−61.88−26.77
Notes: DTM: Days to 75% maturity; AGB: above-ground biomass (t/ha); GY: grain yield (t/ha); HI: harvest index (%); Sr. No.: serial number; KGY: relative performance for grain yield; KABG: relative performance for above-ground biomass; KHI: relative performance for HI; Max: maximum; Min: minimum; SD: standard deviation.
Table 7. Genotype per se performance for DTM, GY, AGB, and HI and relative performance among the medium-maturing sorghum entries evaluated at Ukulinga during the 2024/25 growing season.
Table 7. Genotype per se performance for DTM, GY, AGB, and HI and relative performance among the medium-maturing sorghum entries evaluated at Ukulinga during the 2024/25 growing season.
Sr. No.Maturity Group and Name of GenotypeTraitsRelative Performance [K (%)]Sr. No.Maturity Group and Name of GenotypeTraitsRelative Performance [K (%)]
Medium MaturityDTMGYAGBHIKGYKAGBKHIMedium MaturityDTMGYAGBHIKGYKAGBKHI
1AS5801446.7911.1037.97−62.22−66.848.1521AS6171513.827.1634.36−32.8−48.5919.5
2AS5671442.183.6237.5217.451.639.4522AS5871514.6714.6829.71−45.1−74.9338.21
3 AS5971442.484.2037.133.19−12.4610.5723AS6561517.2129.6519.85−64.43−87.59106.91
4ACCI-S-1041442.555.6727.440.45−35.0849.6624AS4221511.338.1514.0093.4−54.82193.37
5AS5761452.763.3945.87−7.048.6−10.4925AS5771512.3924.148.997.47−84.76356.56
6AS5651462.833.2742.57−9.2412.72−3.5326AS5631511.0816.126.05136.45−77.17578.26
7AS6211464.346.2740.73−40.98−41.300.8227AS5711521.632.2741.7557.5662.08−1.64
8AS6151464.057.8233.54−36.69−52.9422.4228AS3561521.402.4935.9983.1947.8514.08
9AS5881473.194.6240.85−19.74−20.280.5229AS6271524.7310.6730.67−45.84−65.5133.87
10SS631474.617.6935.95−44.33−52.1114.2130AS5691535.007.3942.18−48.68−50.19−2.66
11AS6481472.456.0428.894.54−39.0342.1131AS5701532.724.8136.41−5.76−23.4412.79
12ACCI-S-1061471.896.7921.5735.96−45.7890.3532AS4241541.206.4015.79113.7−42.47160
13AS6291481.792.7339.8243.6134.773.1233AS427154.53.648.2530.41−29.47−55.3835.04
14AS6301481.492.6236.267240.4513.2434AS5781554.1913.9624.24−38.78−73.6469.4
15AS5751484.478.9633.37−42.58−58.923.0635AS6011552.227.0522.9115.54−47.8279.23
16AS5841481.553.6831.6465.7−0.129.7836AS678155.52.354.1236.279.15−10.6113.22
17AS5851481.585.2223.2961.89−29.4476.2937AS4211563.2311.5021.92−20.61−68.0187.31
18AS6221482.6723.0510.38−3.93−84.04295.7438AS568156.57.0427.4920.38−63.56−86.61101.51
19AS625148.58.1516.6732.81−68.56−77.9225.1439AS5791571.613.7430.5859.61−1.4934.27
20AS5961490.9312.806.80174.72−71.24504.140AS5821573.7411.1727.16−31.42−67.0551.18
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41SS561570.723.0319.15257.0521.39114.4263AS599163.54.0017.2127.00−35.93−78.6252.09
42AS3611582.584.2836.97−0.70−14.0811.0764AS6321644.517.0838.93−43.17−48.005.47
43AS6131582.804.9236.29−8.51−25.1913.1565AS6231646.1815.0129.31−58.50−75.4740.09
44AS6181583.7612.4635.10−31.85−70.4617.0066AS6061642.508.4822.762.68−56.5780.42
45AS3601581.664.4325.3454.34−16.9062.0567AS5921653.138.2626.75−18.14−55.4353.49
46AS5941580.856.3511.79202.19−42.00248.1668AS5621651.5710.4513.4263.30−64.78205.90
47AS589158.54.5411.7430.37−43.53−68.6635.1969AS561165.52.827.3529.00−9.13−49.8941.58
48AS6101594.719.1334.00−45.51−59.7020.7870AS6791665.8610.5337.16−56.21−65.0410.48
49AS6161596.8113.3533.77−62.33−72.4321.5971AS354166.50.644.1113.40302.70−10.52206.32
50AS6511602.974.9137.14−13.62−25.0610.5772AS3421681.855.2525.2438.91−29.9062.67
51AS1491604.738.8634.86−45.83−58.4617.8073AS147168.55.0911.7230.73−49.58−68.6033.64
52AS3471601.8010.3714.7942.46−64.50177.5774AS560168.53.2910.7323.75−22.00−65.7172.91
53AS6191612.785.8033.05−7.80−36.5924.2475AS6521696.5623.8521.58−60.92−84.5790.31
54AS355161.53.515.0541.09−26.85−27.12−0.0776AS564169.54.035.8441.33−36.35−36.97−0.66
55AS649161.52.519.3918.362.23−60.80123.6777AS611169.54.7115.6924.90−45.61−76.5464.91
56AS2291624.527.8236.63−43.24−52.9112.1078AS559169.55.6124.9818.25−54.31−85.27124.97
57ACCI-S-1131621.533.4632.6767.526.3025.7079AS3531702.563.6841.06
58AS491623.0611.5220.81−16.18−68.0497.32 Max1708.1529.6545.87
59AS5931623.3316.1816.92−22.99−77.25142.66 Min1440.642.276.05
60AS3491633.244.8737.06−20.91−24.3910.79 SD7.651.696.099.62
61AS3501632.864.9536.33−10.27−25.6413.01 Mean156.473.309.2628.86
62AS3481632.6110.9119.20−1.62−66.25113.87
Notes: DTM: Days to 75% maturity; AGB: above-ground biomass (t/ha); GY: grain yield (t/ha); HI: harvest index (%); Sr. No.: serial number; KGY: relative performance for grain yield; KABG: relative performance for above-ground biomass; KHI: relative performance for HI; Max: maximum; Min: minimum; SD: standard deviation.
Table 8. Genotype per se performance for DTM, GY, AGB, and HI and relative performance among the late-maturing sorghum entries evaluated at Ukulinga during the 2023/24 and 2024/25 growing seasons.
Table 8. Genotype per se performance for DTM, GY, AGB, and HI and relative performance among the late-maturing sorghum entries evaluated at Ukulinga during the 2023/24 and 2024/25 growing seasons.
Sr. No.Maturity Group and Name of GenotypeTraitsRelative Performance [K (%)]Sr. No.Maturity Group and Name of GenotypeTraitsRelative Performance [K (%)]
Late MaturityDTMGYAGBHIKGYKAGBKHILate MaturityDTMGYAGBHIKGYKAGBKHI
Season ISeason II
1SS521580.753.9915.80776.29497.6336.571AS558170.53.8514.0621.51−76.06−54.51−41.41
2AS491612.507.8924.09162.11202.40−10.452AS6241724.368.1934.72−78.83−21.89−63.71
3 AS6001624.2311.0327.7455.13116.10−22.223AS634173.55.539.0837.86−83.33−29.54−66.72
4AS6121622.9611.4720.55121.34107.854.984SS521743.2011.0222.51−71.19−41.95−44.02
5AS6131622.437.2625.65170.28228.40−15.885AS3411741.535.9219.40−39.567.98−35.04
6AS6791622.657.4226.36147.27221.18−18.166AS352174.53.854.3446.17−76.0447.30−72.71
7AS6021632.318.0622.75183.49196.01−5.157AS590174.54.6638.0610.91−80.21−83.1915.48
8AS6481665.6311.4932.8816.5107.48−34.398AS6021754.3311.2929.69−78.68−43.32−57.57
9AS5771717.3913.0736.13−11.2582.46−40.289AS3581771.454.7923.13−36.4033.66−45.53
10AS5911715.4712.9129.7419.9984.65−27.4610AS6121784.1321.4817.34−77.67−70.22−27.32
11AS582171.53.338.2428.9597.21189.56−25.4811AS5911783.5126.5912.72−73.75−75.94−0.93
12AS4211844.5413.8524.1644.4172.23−10.7112AS557178.50.6919.613.3834.37−67.37272.51
13AS6521976.5623.8521.58 13AS6041843.1017.4314.76−70.26−63.30−14.66
Max1977.3923.8536.13 14AS3621890.926.4012.60
Min1580.753.9915.8 Max1895.5338.0646.17
SD10.981.934.865.37 Min170.50.694.343.38
Mean168.53.910.8125.87 SD4.881.509.6511.71
Mean176.613.2214.1621.91
Notes: DTM: Days to 75% maturity; AGB: above-ground biomass (t/ha); GY: grain yield (t/ha); HI: harvest index (%); Sr. No.: serial number; KGY: relative performance for grain yield; KABG: relative performance for above-ground biomass; KHI: relative performance for HI; Max: maximum; Min: minimum; SD: standard deviation.
Table 9. Genotype per se performance for DTM, GY, AGB, and HI and relative performance between the maturity groups of the sorghum entries evaluated at Ukulinga during the 2023/24 and 2024/25 growing seasons.
Table 9. Genotype per se performance for DTM, GY, AGB, and HI and relative performance between the maturity groups of the sorghum entries evaluated at Ukulinga during the 2023/24 and 2024/25 growing seasons.
Sr. No.Maturity GroupsMean Values of the TraitsRelative Performance [K (%)]Sr. No.Maturity GroupsMean Values of the TraitsRelative Performance [K (%)]
DTMGYAGBHIKGYKAGBKHI DTMGYAGBHIKGYKAGBKHI
Season ISeason II
1Early maturity136 3.037.1532.0428.7551.24−19.241Early maturity136.543.607.3533.44−10.4392.69−34.49
2Medium maturity145.092.897.0029.5034.8854.35−12.282Medium maturity156.473.309.2628.86−2.3652.96−24.10
3 Late maturity168.53.910.8125.87 3Late maturity176.613.2214.1621.91
Notes: DTM: Days to 75% maturity; AGB: above-ground biomass (t/ha); GY: grain yield (t/ha); HI: harvest index (%); Sr. No.: serial number; KGY: relative performance for grain yield; KABG: relative performance for above-ground biomass; KHI: relative performance for HI; Max: maximum; Min: minimum; SD: standard deviation.

3.3.2. Relative Performance Within Medium-Maturing Genotypes

During season I (Table 6), approximately 99% of the assessed genotypes in that group exhibited a negative relative performance for GY, with better GYs than the late-maturing genotype (AS353). The late-maturing genotype exhibited a GY decline varying from 6% to 86% compared to the early-maturing genotypes. For AGB and HI, the late-maturing genotype performed worse than 80% of the early-maturing genotypes by approximately 1 to 84% and 1 to 48%, respectively. In season II (Table 7), more than 60% of the genotypes achieved a >1% higher GY and AGB than the late-maturing genotype (AS353) in that category. The reductions in GY and AGB in the late-maturing genotype ranged from 1% to 62% and 1% to 86%, respectively. Conversely, for HI, the late-maturing genotype outperformed the early-maturing genotypes. The gain in HI ranged from 1% to 504%.

3.3.3. Relative Performance Within Late-Maturing Genotypes

In season I (Table 8), more than 90% of the early-maturing genotypes exhibited a positive relative performance for GY, indicating their better performance than the late-maturing genotype (AS652) in that group. The GY reduction in the late-maturing genotype ranged from 16% to 183.5%. For AGB, the late-maturing genotype outperformed all the early-maturing genotypes, with the gain in biomass production exceeding 72%. Conversely, for HI, the late-maturing genotype exhibited a lower relative performance than more than 80% of the early-maturing genotypes, with a decrease in HI in the late-maturing genotype ranging from 5 to 40%. In season II, the late-maturing genotype (AS362) underperformed relative to more than 80% of the early-maturing genotypes in GY, AGB, and HI. The losses in GY, AGB, and HI ranged from 36% to 83%, 20% to 83%, and 1% to 73%, respectively (Table 8).

3.3.4. Relative Performance Between the Maturity Groups

The overall comparison of the relative performance of early- and medium-maturing genotypes against the late-maturing genotypes showed that, in season I, the late-maturing genotype group produced a 28.75% and 51.24% higher GY and AGB, respectively, than the early-maturing types. However, for HI, the late-maturing genotype category exhibited a 19.24% lower performance. The late-maturing genotype group further produced a 34.88% and 54.35% higher GY and AGB, respectively, compared to the medium-maturing genotype group on average, but showed a 12.28% lower HI (Table 9). In season II, the late-maturing genotype group expressed 10.43% and 34.49% lower GYs and HIs, respectively, than the early-maturing group. Conversely, the late-maturing genotype group had a 92.69% higher AGB compared to the early-maturing genotype category. Relative to the medium-maturing group, the late-maturing genotype group had 2.36% and 24.1% lower GY and HI values, respectively, while exhibiting a 52.96% higher biomass production (Table 9).

4. Discussion

Sorghum is a climate-resilient crop, essential for food, feed, bioenergy, and industrial applications [1,7]. It supports the livelihoods of over 750 million people in marginal agroecological regions of South Asia and SSA [2]. Recurrent droughts and shorter rainy seasons have significantly impacted sorghum yields, and the crop is not utilised to its full genetic potential [15]. There is a need to breed locally adapted and high-yielding genotypes for diverse product profiles. The grain yield, biomass production, and harvest index of sorghum are influenced by the genetic composition and plasticity of the maturity period [23]. There is scant information that examines the effect of maturity period on grain yield, biomass production, and harvest index to guide sorghum variety profiles and design for diverse market segments. This study evaluated 106 genetically diverse sorghum genotypes to determine the effect of the maturity period on grain yield, biomass production, and harvest index to identify contrasting genotypes for breeding and production.

4.1. Variability of Test Sorghum Genotypes for Maturity, Grain Yield, Biomass Production, and Harvest Index

The current study recorded marked genotype variation when assessing the test genotypes across the two growing seasons for DTM, GY, AGB, and HI (Table 4). Genotype responses for DTM, GY, AGB, and HI were also influenced by genotype x season interactions, suggesting that the performance of genotypes varied across different seasons. The observed variations could be attributed to differences in the genetic makeup of the assessed genotypes and the varying seasonal conditions, which were characterised by an irregular rainfall distribution during the crop’s growth stages (Table 3). Environmental influences play a significant role in phenotypic variations, and the differential responses of genotypes to environmental conditions contribute to the observed variability [43]. These results align with those of [24,44,45], who reported a significant genotype x environment (G x E) interaction on the DTM, GY, AGB, and HI of sorghum genotypes under rainfed conditions. Understanding the effect of G x E and predicting the phenotypic response to various environments are vital to improving the selection efficiency in sorghum breeding programmes. The low CV values, 3.97, 33.35, 37.74, and 20.81 computed for DTM, GY, AGB, and HI, respectively (Table 4), suggest relatively less experimental error and higher genetic worthiness of the assessed sorghum genotypes. Furthermore, the high coefficients of determination (R2) of 90.4, 82.9, 86.5, and 81.8 for DTM, GY, AGB, and HI, respectively, indicate a strong relationship among the assessed traits, which was primarily explained by genetic components (Table 4).

4.2. The Relative Performances of Test Genotypes for GY, AGB, and HI Based on Maturity Groups

4.2.1. Relative Performance Within Early-Maturing Genotypes

The late-maturing genotype achieved a lower performance for GY and HI than most of the early-maturing genotypes in season I and II. In contrast, for AGB, genotypes showed a relative performance variability across the two seasons. In season I, the late-maturing genotype underperformed the early-maturing genotypes, whereas in season II, the late-maturing genotype outperformed the early-maturing genotypes. These results suggest that the early-maturing genotypes exhibited greater physiological efficiency in assimilate partitioning toward grain production, as evidenced by their higher HI values. This indicates that although late-maturing genotypes often accumulate greater biomass, which would typically enhance assimilate partitioning toward grain yield [46], only a smaller proportion of their total biomass was directed towards grain production. Previous reports have indicated that compared with early-maturing genotypes, late-maturing ones often accumulate high biomass at the expense of flower formation and grain production [47,48]. These results align with [32], which reported short-season maize hybrids outperforming full-season ones in GY. Ref. [20] also noted that the excessive vegetative growth and biomass accumulation in late-maturing genotypes often hinder effective reproductive transition, thereby diminishing grain yield efficiency and ultimately lowering the HI.

4.2.2. Relative Performance Within Medium-Maturing Genotypes

Early-maturing genotypes performed better than the late-maturing genotype across the seasons. In seasons I and II, early-maturing genotypes outperformed the late-maturing genotype in GY and AGB. For HI, early-maturing genotypes showed higher performance than the late-maturing genotype during season I, whereas in season II, the late-maturing genotype surpassed the early-maturing ones. These results align with [20,47,48]. The variation observed in HI, where the late-maturing genotype exceeded most early-maturing genotypes in season II, may be attributed to differences in weather conditions between the two growing seasons. Season II likely provided more favourable environmental conditions for the late-maturing genotype, thereby enhancing the efficiency of assimilate remobilisation during the grain-filling period. Under favourable post-flowering conditions, late-maturing genotypes, particularly those with the stay-green trait, can maintain prolonged photosynthetic activity during grain filling, thereby ensuring a continuous supply of assimilates to developing grains, which can lead to increased grain yield and improved harvest index [49].

4.2.3. Relative Performance Within Late-Maturing Genotypes

Across the late-maturing group, the late-maturing genotypes exhibited higher performances for GY and AGB and lower values of HI than the early-maturing genotypes in season I. Whereas, during season II, the late-maturing genotype produced lower a GY, AGB, and HI than the early-maturing genotypes. The trend in relative performance in season I can be attributed to the longer growth duration of late-maturing genotypes, which enabled extended photosynthetic activity and assimilation, ultimately enhancing the potential for biomass and grain yield [30,43]. In season II, although late-maturing genotypes are generally deemed to accumulate greater biomass, which would typically enhance assimilate partitioning toward grain yield [46], this group’s late-maturing genotype exhibited comparatively lower performance than the early-maturing genotypes. This could be attributed to genotype makeup and the weather conditions during the growing season, aligning with [20,47,48].

4.2.4. Relative Performance Between the Maturity Groups

Comparison of the maturity groups during season I demonstrated that late-maturing genotypes showed higher GY and AGB values, but lower HIs than the early- and medium-maturing groups. These findings are consistent with those of [28], who reported increases of 46.6% and 95.43% in panicle yield and biomass, respectively, from short- to late-maturing genotypes. An evaluation of the effect of maturity period on sorghum GY across varying climatic conditions reported that under favourable environments, late-maturing genotypes yielded 21.9% more grain than the early-maturing ones [31]. Across season II, the late-maturing group exhibited a lower GY and HI than the early- and medium-maturing groups, yet produced a higher AGB. These results suggest that the environmental conditions during season II, possibly related to rainfall distribution or temperature, did not favour the late-maturing genotypes. The current findings align with previous research by [50], who indicated that late-maturing genotypes may suffer a yield penalty under less favourable environments, as their prolonged growth period increases their exposure to drought or terminal heat stress. Furthermore, ref. [32] reported that short-season maize hybrids outperformed the full-season ones in GY. However, the results contradict those of [28,31]. The higher biomass accumulation in late-maturing genotypes compared to early- and medium-maturing genotypes reflects prolonged vegetative growth. A prolonged maturity period extends photosynthetic activity and assimilate accumulation, ultimately enhancing biomass production [51]. However, the lower HI of late-maturing genotypes points to limited efficiency in transferring assimilates to the grains.

5. Conclusions

This current study evaluated 106 genetically diverse sorghum genotypes to determine the effect of maturity period on grain yield, biomass production, and harvest index, to identify contrasting genotypes for breeding and production. The present findings demonstrated that the effect of maturity period on sorghum grain yield, biomass, and harvest index is strongly influenced by the genetic potential for crop maturation and environmental conditions. Late-maturing genotypes exhibited distinct responses in grain yield, biomass production, and harvest index gains across the growing seasons relative to early- and medium-maturing genotypes, likely due to the crop’s genetic makeup and the marked even rainfall distribution and temperature patterns. The study found genotypes such as AS232, AS603, and AS580 combined early maturity (133, 136, and 141 days), superior GY (4.6, 6.3, and 5.3 t/ha), AGB (6.47, 12.55, and 8.9 t/ha), and HI (41.74, 33.43, and 37.06%), respectively, in both the seasons, providing valuable genetic resources for breeding sorghum ideotypes that enhance sorghum productivity under drought-prone conditions.

6. Study Limitations

The current findings highlight interactions between maturity period and yield-related traits; the broader applicability of these findings requires confirmation through multi-environment trials encompassing diverse climatic conditions and soil types. Additionally, the study primarily relies on statistical analyses of phenotypic data, with limited investigation into the physiological and molecular mechanisms underlying maturity-related effects. Future research should integrate physiological measurements, such as photosynthetic efficiency and carbon isotope discrimination, alongside genetic approaches, such as QTL mapping, to provide a more integrative understanding of the mechanisms driving maturity-related differences in performance.

Author Contributions

Conceptualization, H.S.; methodology, B.L.Z.; software, B.L.Z. and S.A.T.; validation, B.L.Z., H.S. and S.A.T.; formal analysis, B.L.Z.; investigation, B.L.Z.; resources, H.S.; data curation, B.L.Z.; writing—original draft preparation, B.L.Z.; writing—review and editing, B.L.Z., S.A.T. and H.S.; visualisation, B.L.Z., S.A.T. and H.S.; supervision, H.S.; funding acquisition, H.S. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the Department of Science, Technology, and Innovation (DSTI) and the Technology Innovation Agency (TIA) of South Africa through the African Center for Crop Improvement (ACCI); [PhD funding].

Institutional Review Board Statement

The authors confirm that the research meets the required ethical guidelines, including adherence to the legal requirements of the study country.

Data Availability Statement

The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author.

Acknowledgments

The authors thank the overall support of the African Center for Crop Improvement (ACCI) of the University of KwaZulu-Natal (UKZN) and the sorghum pre-breeding project of the Sorghum Cluster Initiative (SCI) through the Sorghum Trust, the Department of Science, Technology, and Innovation (DSTI), and the Technology Innovation Agency (TIA) of South Africa.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper.

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Table 1. Description of sorghum genotypes used in the study.
Table 1. Description of sorghum genotypes used in the study.
Genotype DesignationPedigreeSourceCountrySeed ColourGenotype DesignationPedigreeSourceCountrySeed Colour
AS49MN 1618 (Tall)UK-SGVT 07-10-RedACCI-S-116WD 116 Hd16ACCIRSABrown
AS3422MC 6 AOIN 122USDAUSABrownACCI-S-118WD 118 Hd18ACCIRSABrown
AS3477MC 1 AOIN 158USDAUSABrownAS147MRS94ACCIRSAMixed
AS348SurenoUSDAUSABrownAS149R8602ACCIRSARed
AS3498MC 11 AOIN 143USDAUSABrownAS22997-AGB-FSDT-150 A--Brown
AS35013MC 35 SABN 1004USDAUSABrownAS23202-AGB-FSDT-12 B--Brown
AS35215MC 27 SABN 1020USDAUSABrownAS678E112--Brown
AS353 16MC 37 SABN 1054USDAUSABrownAS679E119--Brown
AS35417MC 33 SABN 1092USDAUSAWhiteAS648EC 3281ARC-SARSABrown
AS35518MC 23 SABN 1098USDAUSABrownAS649EC 3218ARC-SARSALight brown
AS356Sevr FeterttaUSDAUSABrownAS651LP 1344ARC-SARSALight brown
AS35884 EON 361USDAUSARed to brownAS652LP 1392ARC-SARSABrown
AS360SC 430 11EUSDAUSARed to brownAS656MP 2078ARC-SARSALight brown
AS361DoradoUSDAUSABrownAS634MammopaneARC-SARSABrown
AS362SRN 39USDAUSAWhiteSS52SS52ARC-SARSACream
AS3411MC 2 AOIN 101USDAUSABrownSS56SS56ARC-SARSAGrey
ACCI-S-104WD 104 Hd4ACCIRSABrownSS63SS63ARC-SARSABrown
ACCI-S-105WD 105 Hd5ACCIRSABrownAS421#5 235466-EthiopiaLight brown
ACCI-S-106WD 106 Hd6ACCIRSABrownAS422#49 169830-EthiopiaBrown
ACCI-S-108WD 108 Hd8ACCIRSABrownAS424Hormat-EthiopiaLight brown
ACCI-S-109WD 109 Hd9ACCIRSARed to brownAS427SRN 39 Fraimida-EthiopiaWhite
ACCI-S-112WD 112 Hd12ACCIRSABrownAS557IESV 92001 DLICRISATIndiaBrown
ACCI-S-113WD 113 Hd13ACCIRSAWhiteAS558IESV 92008 DLICRISATIndiaBrown
AS559IESV 92021 DLICRISATIndiaBrownAS589MP 5476NPGRC-SARSABrown
AS560IESV 92028 DLICRISATIndiaRedAS590MP 4265NPGRC-SARSALight brown
AS561IESV 92165 DLICRISATIndiaBrownAS591MP 4052NPGRC-SARSABrown
AS562IESV 94021 DLICRISATIndiaRed to brownAS592MP 2055NPGRC-SARSAWhite
AS563IS 2331ICRISATIndiaBrownAS593MP 5518NPGRC-SARSABrown
AS564MR#22 × IS 8613ICRISATIndiaBrownAS594MP 4259NPGRC-SARSABrown
AS565NW 5405NPGRC-SARSABrownAS596MP 5541NPGRC-SARSAWhite
AS567NW 5333NPGRC-SARSABrownAS597MP 1990NPGRC-SARSALight brown
AS568NW 5464NPGRC-SARSABrownAS599MP 2048NPGRC-SARSALight brown
AS569NW 5436NPGRC-SARSABrownAS600MP 4161NPGRC-SARSABrown
AS570NW 5454NPGRC-SARSABrownAS601LP 1455NPGRC-SARSADark brown
AS571NW 5430NPGRC-SARSABrownAS602LP 1450NPGRC-SARSALight brown
AS572NW 5393NPGRC-SARSABrownAS603LP 4312NPGRC-SARSABrown
AS573NW 5337NPGRC-SARSABrownAS604LP 1948NPGRC-SARSALight brown
AS575EC 3416NPGRC-SARSARed to brownAS606LP 4441NPGRC-SARSAWhite
AS576EC 3414NPGRC-SARSABrownAS610LP 1394NPGRC-SARSABrown
AS577EC 3262NPGRC-SARSAWhiteAS611LP 1481NPGRC-SARSABrown
AS578EC 3319NPGRC-SARSABrownAS612LP 1473NPGRC-SARSABrown
AS579EC 2922NPGRC-SARSABrownAS613LP 4303NPGRC-SARSARed
AS580EC 3364NPGRC-SARSARed to brownAS615KZ 5088NPGRC-SARSABrown
AS5813403NPGRC-SARSARed to brownAS616KZ 5287NPGRC-SARSARed to brown
AS5822975NPGRC-SARSABrownAS617KZ 5233NPGRC-SARSABrown
AS584EC 2934NPGRC-SARSAWhiteAS618KZ 5258NPGRC-SARSABrown
AS585EC 2985NPGRC-SARSABrownAS619KZ 5237NPGRC-SARSABrown
AS587MP 4154NPGRC-SARSABrownAS621KZ 5246NPGRC-SARSARed to brown
AS588MP 4276NPGRC-SARSABrownAS622KZ 4606NPGRC-SARSABrown
AS623KZ 4531NPGRC-SARSALight brown
AS624KZ 5274NPGRC-SARSARed to brown
AS625KZ 5281NPGRC-SARSARed to brown
AS627KZ 5097NPGRC-SARSABrown
AS628KZ 5245NPGRC-SARSABrown
AS629FS 4942NPGRC-SARSABrown
AS6304909NPGRC-SARSAWhite
AS6324891NPGRC-SARSABrown
Note: -: unknown data; ACCI: frican Center for Crop Improvement; ARC-SA: Agricultural Research Council of South Africa; ICRISAT: International Crops Research Institute for the Semi-Arid Tropics/India; NPGRC-SA: National Plant Genetic Resources Centre of South Africa; RSA: Republic of South Africa; USA: United States of America; USDA: United States Department of Agriculture.
Table 2. Physico-chemical properties at Ukulinga research farm Soil.
Table 2. Physico-chemical properties at Ukulinga research farm Soil.
PropertyValues
pH (KCl)4.67
Carbon (%)4.45
Nitrogen (%)0.268
C/N16
Clay (%)39.0
Bulk density (g cm−3)1.29
Extractable P (mg kg−1)2.73
Extractable K (cmolc kg−1)0.063
Exchangeable Ca (cmolc kg−1)2.24
Exchangeable Mg (cmolc kg−1)2.24
Exchangeable acidity (cmolc kg−1) 1.60
Source: [38].
Table 3. Weather conditions at Ukulinga research farm during the 2023–2025 growing seasons.
Table 3. Weather conditions at Ukulinga research farm during the 2023–2025 growing seasons.
YearMonthRainfall TmaxTminRhmaxRhmin
2023/2024October146.5624.5112.5697.7845.87
November482815.89847.4
December192.525.616.299.559.5
January126.527.516.999.755
February69.327.817.698.952.9
March27.929.316.89946.5
2024/2025October63.825.512.396.538.8
November199.426.715.599.449.8
December96.329.217.999.851.8
January126.429.718.499.950.7
February144.627.918.699.757.8
March174.428.117.899.954.7
Source: “https://agromet.ukzn.ac.za:5355/Weather/index.html (accessed on 24 July 2025)”, Rainfall (mm), Tmax: maximum temperature (°C), Tmin: minimum temperature (°C), Rhmax: maximum relative humidity (%), Rhmin: minimum relative humidity.
Table 4. Combined analysis of variance, mean squares, and significant tests for the assessed traits among 106 sorghum genotypes evaluated during the 2023/24 and 2024/25 growing seasons.
Table 4. Combined analysis of variance, mean squares, and significant tests for the assessed traits among 106 sorghum genotypes evaluated during the 2023/24 and 2024/25 growing seasons.
Source of VariationDFDTMGYAGBHI
Incomplete block9297.21 ***5.48 ***50.90 ***29.76 ns
Replication1369.85 **0.11 ns6.12 ns95.11 ns
Genotype105321.92 ***5.28 ***79.77 ***180.31 ***
Season19930.91 ***9.10 **506.56 ***70.04 ns
Genotype * season105167.03 ***3.40 ***25.46 ***106.87 ***
Residual19336.401.1310.4836.21
Trial statistics
CV (%) 3.9733.3537.7420.81
LSD (5%) 1.160.200.621.16
R2 (%) 90.4082.9086.5081.80
** and *** denote significance at p < 0.01 and p < 0.001, respectively; ns: non-significance; DF: degrees of freedom; DTM: days to 75% maturity; GY: grain yield; AGB: above-ground dry biomass; HI: harvest index; CV: coefficient of variation; LSD: least significant difference; R2: coefficient of determination.
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Zabuloni, B.L.; Shimelis, H.; Tesfamariam, S.A. The Effect of Maturity Period on Grain Yield, Biomass Production, and Harvest Index in Sorghum. Agronomy 2026, 16, 610. https://doi.org/10.3390/agronomy16060610

AMA Style

Zabuloni BL, Shimelis H, Tesfamariam SA. The Effect of Maturity Period on Grain Yield, Biomass Production, and Harvest Index in Sorghum. Agronomy. 2026; 16(6):610. https://doi.org/10.3390/agronomy16060610

Chicago/Turabian Style

Zabuloni, Byamungu Lincoln, Hussein Shimelis, and Seltene Abady Tesfamariam. 2026. "The Effect of Maturity Period on Grain Yield, Biomass Production, and Harvest Index in Sorghum" Agronomy 16, no. 6: 610. https://doi.org/10.3390/agronomy16060610

APA Style

Zabuloni, B. L., Shimelis, H., & Tesfamariam, S. A. (2026). The Effect of Maturity Period on Grain Yield, Biomass Production, and Harvest Index in Sorghum. Agronomy, 16(6), 610. https://doi.org/10.3390/agronomy16060610

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