Morphophysiological changes of rice genotypes in agriphotovoltaic system

Introduction

Rice (Oryza sativa L.) is a primary cereal crop for nearly half of the global population. Rice is a staple food for a large portion of the global population, particularly in less developed countries. India is the world's second-largest producer of rice and the largest exporter of rice in the world. In India rice is grown on an area of 478.28 lakh hectares with production of 1378.25 lakh tons with productivity of 2882 kg/ha for year 2023-24 (Annual Report, Ministry of Agriculture, Government of India 2024-25) [1] . Agriphotovoltaic (APV) systems integrate agricultural production with photovoltaic electricity generation on the same land area. This approach provides an opportunity to produce renewable energy while continuing crop cultivation. However, photovoltaic panels modify the quantity and spatial distribution of solar radiation reaching the crop and consequently alter the microclimatic conditions experienced by plants. Yun et al. (2025) [2] reported that rice grown under APV conditions showed changes in growth and development associated with the modified radiation environment. Solar radiation is a major factor regulating crop growth because it provides the energy required for photosynthesis and influences leaf development, plant architecture and crop phenology. Under APV systems, radiation received by the crop varies according to panel height, panel arrangement and the distance of plants from the photovoltaic panels. Barron-Gafford et al. (2019) [3] reported that photovoltaic panels reduced incoming solar radiation beneath the array and modified the crop microclimate, while Adeh et al. (2019) [4] demonstrated that partial shading under agrivoltaic systems altered light availability and crop growing conditions. Changes in radiation can influence important morphological characteristics of rice, including leaf thickness, number of leaves, plant height and flag leaf area. The response depends on the intensity of shading and the genetic characteristics of the crop. Yun et al. (2025) [2] reported changes in rice plant height and leaf morphology under APV conditions and demonstrated that rice plants respond morphologically to the modified light environment. APV systems also modify canopy and soil temperature by reducing the amount of solar radiation reaching the crop and soil surface. These changes in the thermal environment can influence crop development and phenological processes such as flowering and maturity. In addition, altered radiation availability affects photosynthetic pigments. Increased chlorophyll concentration under shaded conditions has been reported in agrivoltaic systems by Gonocruz et al. (2021) [5] , while Yun et al. (2025) [2] reported changes in chlorophyll a and chlorophyll b under reduced radiation.

Therefore, the present investigation was conducted to evaluate the morph-physiological changes of rice genotypes in agriphotovoltaic system, with particular emphasis on leaf thickness, number of leaves per plant, days to 50% flowering, days to maturity, plant height, flag leaf area, canopy temperature, soil temperature, photosynthetically active radiation and chlorophyll content. Leaf thickness was calculated from three tagged plants per replication from each genotype, and from each panel including control condition was determined by using a vernier measurement. leaf was segmented in base, middle and top of leaf mean was calculated in mm, at 30, 60 and 90 DAS. Total numbers of leaves were determined by counting the leaves from the top to bottom of all the tillers on a hill and the mean values of the three hills were taken from each genotype and was expressed per hill basis (at flowering). Count number of days required, from sowing to bear 50% flowering on spike. Number of days required for complete maturity, when percentage of milky grain was less than 1 percent, Moisture content of grain less than 20 percent. Plant height (at flowering) was measured in centimeters from ground level to the tip of flag leaf and average values were used for analysis. Three plant samples were taken from the experimental plot at 50% flowering stage. The maximum length and width of flag leaves were measured, for leaf area, a factor 0.75 (at flowering) was used. Canopy temperature was measured using infrared thermometer 0.5-2 m above the canopy. Soil temperature record using thermometer. Chlorophyll extraction through dimethyl sulpoxide (DMSO) (Kumari et al., 2018) [6] . The statistical analysis of data was carried out by the standard method (Panse et al., 1985) [7] .

Materials and methods

Results and discussion

Morpho-phsiological parameter

Leaf thickness was significantly influenced by the agriphotovoltaic (APV) treatments at 30, 60 and 90 DAS, whereas genotype and genotype × APV interaction effects were non-significant at all three stages. At 30 DAS, the maximum leaf thickness was recorded under P 0 (0.250 mm), followed by P 3 (0.241 mm), while the minimum was recorded under P 4 (0.184 mm). At 60 DAS, P 0 again recorded the maximum value (0.272 mm), followed by P 6 (0.254 mm) and P 3 (0.253 mm), whereas P 4 recorded the minimum (0.201 mm). At 90 DAS, the maximum leaf thickness was recorded under P 0 (0.317 mm) and the minimum under P 4 (0.213 mm). Genotype and genotype × APV interaction remained non-significant at each stage detailed in table -1.

The consistent reduction in leaf thickness under P 4 was associated with the stronger shading at this position. P 4 received the lowest mean PAR (156.56 µmol m -2 s -1 ), whereas P 0 received 1975.00 µmol m -2 s -1

. Reduced radiation under shaded conditions decreases mesophyll development and produces thinner leaves (Tani et al., 2014; Marrou et al., 2013) [9,8] .

Number of leaves per plant (Nos)

The number of leaves per plant at flowering was significantly influenced by APV treatments, whereas genotype and genotype × APV interaction effects were non-significant. The maximum number of leaves was recorded under P 0 (33.33), which was statistically at par with P 3 (32.44). The minimum number was recorded under P 1 (15.78 l), which was statistically at par with P 4 (18.56) (Table -1).

Reductions in leaf number under shaded agrivoltaic conditions have also been reported in French bean (Cossu et al., 2021) [10] , lettuce (Marrou et al., 2013) [8] and pak choi (Hsiao et al., 2023) [11] .

Days to 50% flowering (Nos)

Days to 50% flowering were significantly influenced by genotype and APV treatment, whereas genotype × APV interaction was non-significant. G 3 recorded the maximum mean duration to 50% flowering (85.24), followed by G 2 (83.95), while G 1 recorded the minimum (70.90). Among APV treatments, flowering occurred earliest under P 0 (74.33), followed by P 3 (76.22) and P 6 (79.11). The maximum duration was recorded under P 4 (87.11 days), followed by P 5 (83.89) and P 1 (81.3) (Table -1). Similar delays in flowering under modified light environments were reported in chilli pepper (Hassanien et al., 2022) [12] , tomato (Scarano et al., 2024) [13] and mung bean (Ukwu et al., 2025) [14] .

Days to maturity (Nos)

Days to maturity were significantly influenced by genotype and APV treatment, while genotype × APV interaction was non-significant. G 3 recorded the maximum mean duration to maturity (134.05), followed by G 2 (123.5) and G 1 (115.48). Among the APV treatments, the earliest maturity was recorded under P 0 (110.00), followed by P [15] and wheat (Marrou et al., 2013b) [16] , while Thum et al. (2025) [17] reported a 10-11 day delay in rice maturity under APV conditions.

Plant height was significantly influenced by genotype, APV treatment and genotype × APV interaction. Among the genotypes, G 1 recorded the maximum overall mean plant height (93.74), followed by G 3 (86.84) and G 2 (75.50). Among APV treatments, P 0 recorded the maximum mean plant height (99.81), followed by P 3 (95.24) and P 6 (94.74), whereas P 4 recorded the minimum (61.77) (Table -1). The significant genotype × APV interaction demonstrated that plant height responded differently according to the combination of genotype and panel position. The tallest plants were recorded in G 1 P 0 (115.57), followed by G 1 P 6 (108.40) and G 1 P 3 (106.73). The shortest plants were recorded in G 3 P 4 (59.00), followed by G 2 P 4 (61.40) and G 1 P 4 (64.90). The reduction in plant height under the strongly shaded treatments was related to the lower availability of PAR. Reduced light interception restricts photosynthesis and carbohydrate production, limiting the assimilates available for cell division and internode elongation. Reduced light availability also alters gibberellin metabolism and decreases the accumulation of bioactive gibberellins involved in internode elongation, resulting in reduced stem elongation (Lestari et al., 2020) [18] . Nos-Numbers, PH-Plant Height, LA-Leaf area, CT-Canopy Temperature, ST-Soil Temperature, PAR-Photosynthetically Active Radiation, NS-Non Significant

Flag leaf area at flowering was significantly influenced by APV treatment, whereas genotype and genotype × APV interaction effects were non-significant. P 0 recorded the maximum mean flag leaf area (37.07), followed by P 3 (36.57) and P 6 (34.97). P 4 recorded the minimum value (23.62), followed by P 5 (26.23) and P 1 (26.35). The maximum flag leaf area under P 0 corresponded with the maximum radia-tion availability, while the minimum under P 4 corresponded with the lowest PAR. P 0 received 1975.00 µmol m -2 s -1 PAR, whereas P 4 received 156.56 µmol m -2 s -1 . Reduced radiation restricted leaf expansion and resulted in a smaller flag leaf area at the strongly shaded position. The reduction was particularly pronounced between P 0 (37.07) and P 4 (23.62) (Table -1).

Microclimatic and radiation parameters

Canopy temperature (0C)

Canopy temperature was significantly influenced by the agriphotovoltaic (APV) treatments, whereas genotype and genotype × APV interaction effects were non-significant. The maximum mean canopy temperature was recorded under the open-field treatment P 0 (26.20), followed by P 6 (24.5) and P 3 (23.9). The lowest canopy temperature was recorded under P 4 (22.03°), followed by P 1 (22.47) and P 5 (22.81) (Table -1). Similar reductions in rice canopy temperature under shaded conditions have been reported where reduced radiation lowered daytime canopy temperature relative to the control (Wang et al., 2015) [19] .

Soil temperature (0C)

Soil temperature was significantly influenced by the APV treatments, whereas genotype and genotype × APV interaction effects were nonsignificant. The maximum mean soil temperature was recorded under P 0 (30.4), followed by P 3 and P 6 (29.37 °C each). The lowest soil temperature was recorded under P 4 (26.10), followed by P 1 (26.56) and P 5 (27.08) (Table -1). The reduction in soil temperature under the APV treatments resulted from the lower amount of direct solar radiation reaching the soil surface. P 4 , which recorded the lowest soil temperature, also received the lowest PAR.

Photosynthetically active radiation (umolm-2 s -1 )

Photosynthetically active radiation (PAR) was significantly influenced by genotype, APV treatment and genotype × APV interaction. Among the APV treatments, P 0 recorded the maximum mean PAR (1975.00), followed by P 3 (1333.67) and P 6 (1105.11) (Table -1). The lowest PAR was recorded under P 4 (156.56), followed by P 1 (189.00) and P 5 (268.56). Among the genotypes, G 2 recorded the maximum mean PAR (837.43), followed by G 1 (772.48) and G 3 (663.6). The significant genotype × APV interaction demonstrated variation in the radiation environment among genotype × panel-position combinations. The maximum PAR was recorded in G 2 P 0 (2081.00), whereas the lowest was recorded in G 3 P 4 (151.67). The pronounced reduction in PAR at positions close to the panels resulted from interception of incoming solar radiation by the photovoltaic modules. Agrivoltaic systems create spatially variable light environments because the crop receives alternating periods and locations of direct and shaded radiation.

Photosynthetic parameter

Chlorophyll content

Chlorophyll content at flowering was significantly influenced by the APV treatments, whereas genotype and genotype × APV interaction effects were non-significant. Among the APV treatments, P 4 recorded the maximum mean chlorophyll content (3.49), which was statistically at par with P 1 (3.42) (Table -1). The minimum value was recorded under P 0 (1.21), followed by P 6 (1.22). Maximum leaf chlorophyll under agrivoltaic conditions compared with open-field conditions was also reported by Gonocruz et al. (2021) [5] .

Conclusion

Based on the findings of the present investigation, agriphotovoltaic (APV) systems substantially modified the radiation and microclimatic environment and consequently influenced the morpho-physiological and phenological responses of rice genotypes. The magnitude of these responses varied primarily with panel height and the position of the crop relative to the photovoltaic panels. The open-field condition (P 0 ) generally recorded higher leaf thickness, number of leaves, plant height, flag leaf area, Canopy Temperature, Soil Temperature and PAR, whereas conditions subjected to greater shading, particularly P 4 (0.5 m from the centre of the 1.25 m panel), exhibited pronounced reductions in these parameters. The lowest PAR under P 4 (156.56 µmol m -2 s -1 ) was associated with reduced leaf thickness, leaf number, plant height and flag leaf area, indicating a strong morphological response to restricted radiation availability. APV conditions also altered crop phenology, with delayed 50% flowering and maturity under the more shaded treatments. Among the genotypes, CR Dhan 103 (G 1 ) exhibited comparatively greater plant height, whereas CR Dhan 415 (G 3 ) required a longer duration to flowering and maturity. The significant genotype × APV interaction for plant height and PAR further indicates that rice genotypes differed in their responses to the spatially variable radiation environment created by the photovoltaic panels. APV was characterized by lower canopy and soil temperatures relative to the open-field condition, particularly at positions receiving greater shading. In contrast, chlorophyll content increased markedly under the shaded APV conditions, with the highest value recorded under P 4 (3.49 mg g -1 ).

Acknowledgement

AcknowledgementThe present study was conducted as a part of a collaborative research project funded and supported by GIZ Germany along with VNMKV, Parbhani in carrying out the present investigation and the processing charges. All the observations were taken at Agriphotovoltaic Research Project, Manwat, Parbhani District using the necessary facilities available at Department of Plant Physiology, College of Agriculture, VNMKV Parbhani.

References

1. Ministry of Agriculture and Farmers Welfare. Annual Report 2024-25. Government of India; 2025.
2. Yun SM, Seong DG, Lee JJ, Chung JS. Assessment of Rice Productivity and Solar Power Generation in Agri photovoltaic Systems. Agriculture. 2025;15:1741.
3. Barron-Gafford GA, Pavao-Zuckerman MA, Minor RL, Sutter LF, Barnett-Moreno I, Blackett DT, et al. Agrivoltaics provide mutual benefits across the food-energy-water nexus. Nature Sustainability. 2019;2(9):848-855.
4. Adeh EH, Good SP, Calaf M, Higgins CW. Solar PV power potential is greatest over croplands. Scientific Reports. 2019;9:11442.
5. Gonocruz RA, Nakamura R, Yoshino K, Homma M, Doi T, Yoshida Y, Tani A. Analysis of the Rice Yield under an Agrivoltaics System: A Case Study in Japan. Environments. 2021;8:65.
6. Kumari R, Ashraf S, Bagri GK, Khatik SK, Bagri DK, Bagdi DL. Extraction and estimation of chlorophyll content of seed treated lentil crop using DMSO and acetone. Journal of Pharmacognosy and Phytochemistry. 2018;7(3):249-250.
7. Panse VG, Sukhatme PV. Statistical Methods for Agricultural Workers, 4th Edn. I.C.A.R. Publication, New Delhi. 1985:152165.
8. Marrou H, Wery J, Dufour L, Dupraz C. Productivity and radiation use efficiency of lettuces grown in the partial shade of photovoltaic panels. European Journal of Agronomy. 2013;44:54-66.
9. Tani A, Shiina S, Nakashima K, Hayashi M. Improvement in lettuce growth by light diffusion under solar panels. Journal of Agricultural Meteorology. 2014;70(3):139-149.
10. Cossu M, Sirigu A, Deligios PA, Farci R, Carboni G, Urracci G, Ledda L. Yield response and physiological adaptation of green bean to photovoltaic greenhouses. Frontiers in Plant Science. 2021;12.
11. Hsiao CL, Wang CY, Hsu YT. Effect of stimulated photovoltaic roofs on the yield and nitrate content of Pak Choi and rape. HortScience. 2023;58(11):1297-1305.
12. Hassanien RHE, Ibrahim MM, Ghaly AE, Abdelrahman EN. Effect of photovoltaics shading on the growth of chili pepper in controlled greenhouses. Heliyon. 2022;8(2):e08877.
13. Scarano A, Semeraro T, Calisi A, Aretano R, Rotolo C, Lenucci MS, Santino A, Piro G, De Caroli M. Effects of the agrivoltaicsystem on crop production: The caseof tomato (Solanum lycopersicum L.). Applied Sciences. 2024;14:3095.
14. Ukwu U, Muller O, Meier-Grull M, Uguru M. Agrivoltaics shading enhanced the microclimate, photosynthesis, growth and yields of Vigna radiata genotypes in tropical Nigeria. Scientific Reports. 2025;15:1190.
15. Elamri Y, Cheviron B, Lopez J, Dejean C, Belaud G. Water budget and crop modelling for agrivoltaic systems: Application to irrigated lettuces. Agricultural Water Management. 2018;208:440453.
16. Marrou H, Dufour L, Wery J. How does a shelter of solar panels influence water flows in a soil-crop system? European Journal of Agronomy. 2013;50:38-51.
17. Thum CH, Okada K, Yamasaki Y, Kato Y. Impacts of agrivoltaic systems on microclimate, grain yield, and quality of lowland rice under a temperate climate. Field Crops Research. 2025;326:109877.
18. Lestari AP, Hairmansis A, Mulyaningsih ES, Sulistyowati Y. Shading tolerance of some rice genotypes under the artificial shade net. IOP Conference Series: Earth and Environmental Science. 2020;591(1):012008.
19. How to cite this article: HA K, SG S, GS P, IM M, SS N, JR B, et al. Morphophysiological changes of rice genotypes in agriphotovoltaic system. International Journal of Advanced Biochemistry Research. 2026;SP-10(10):474-479. doi: https://w ww.doi.org/10.33545/26174693.2026.v10.i10Sf.10325
20. Mishra IM Hon. Vice Chancellor, Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani, Maharashtra, India. International Journal of Advanced Biochemistry Research https://www.biochemjournal.com 26174707, 2026, 10(10), Downloaded from https://www.doi.org/10.33545/26174693.2026.v10.i10Sf.10325 by International Journal of Advanced Biochemistry Research on [06/10/2026]. See the Terms and Conditions (https://www.biochemjournal.com) for rules of use; OA articles are governed by the applicable Creative Commons License Naik SS College of Agriculture, Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani, Maharashtra, India.
21. Badole JR College of Agriculture, Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani, Maharashtra, India. DD Sawant College of Agriculture, Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani, Maharashtra, India. VV Jogdand College of Agriculture, Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani, Maharashtra, India. TD Ghormade College of Agriculture, Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani, Maharashtra, India. AW More College of Agriculture, Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani, Maharashtra, India. International Journal of Advanced Biochemistry Research https://www.biochemjournal.com 26174707, 2026, 10(10), Downloaded from https://www.doi.org/10.33545/26174693.2026.v10.i10Sf.10325 by International Journal of Advanced Biochemistry Research on [06/10/2026]. See the Terms and Conditions (https://www.biochemjournal.com) for rules of use; OA articles are governed by the applicable Creative Commons License