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Varatharajan T, Dass A, Choudhary AK, Sudhishri S, Pooniya V, Das TK, Rajanna GA, Prasad S, Swarnalakshmi K, Harish MN, Dhar S, Singh R, Raj R, Kumari K, Singh A, Sachin KS, Kumar P. Integrated management enhances crop physiology and final yield in maize intercropped with blackgram in semiarid South Asia. Front Plant Sci 2022; 13:975569. [PMID: 36212325 PMCID: PMC9538492 DOI: 10.3389/fpls.2022.975569] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 08/31/2022] [Indexed: 06/16/2023]
Abstract
Photosynthesis, crop health and dry matter partitioning are among the most important factors influencing crop productivity and quality. Identifying variation in these parameters may help discover the plausible causes for crop productivity differences under various management practices and cropping systems. Thus, a 2-year (2019-2020) study was undertaken to investigate how far the integrated crop management (ICM) modules and cropping systems affect maize physiology, photosynthetic characteristics, crop vigour and productivity in a holistic manner. The treatments included nine main-plot ICM treatments [ICM1 to ICM4 - conventional tillage (CT)-based; ICM5 to ICM8 - conservation agriculture (CA)-based; ICM9 - organic agriculture (OA)-based] and two cropping systems, viz., maize-wheat and maize + blackgram-wheat in subplots. The CA-based ICM module, ICM7 resulted in significant (p < 0.05) improvements in the physiological parameters, viz., photosynthetic rate (42.56 μ mol CO2 m-2 sec-1), transpiration rate (9.88 m mol H2O m-2 sec-1) and net assimilation rate (NAR) (2.81 mg cm-2 day-1), crop vigour [NDVI (0.78), chlorophyll content (53.0)], dry matter partitioning toward grain and finally increased maize crop productivity (6.66 t ha-1) by 13.4-14.2 and 27.3-28.0% over CT- and OA-based modules. For maize equivalent grain yield (MEGY), the ICM modules followed the trend as ICM7 > ICM8 > ICM5 > ICM6 > ICM3 > ICM4 > ICM1 > ICM2 > ICM9. Multivariate and PCA analyses also revealed a positive correlation between physiological parameters, barring NAR and both grain and stover yields. Our study proposes an explanation for improved productivity of blackgram-intercropped maize under CA-based ICM management through significant improvements in physiological and photosynthetic characteristics and crop vigour. Overall, the CA-based ICM module ICM7 coupled with the maize + blackgram intercropping system could be suggested for wider adoption to enhance the maize production in semiarid regions of India and similar agroecologies across the globe.
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Affiliation(s)
- T. Varatharajan
- Indian Agricultural Research Institute, Indian Council of Agricultural Research, New Delhi, India
| | - Anchal Dass
- Indian Agricultural Research Institute, Indian Council of Agricultural Research, New Delhi, India
| | - Anil K. Choudhary
- Indian Agricultural Research Institute, Indian Council of Agricultural Research, New Delhi, India
- Central Potato Research Institute, Indian Council of Agricultural Research, Shimla, India
| | - S. Sudhishri
- Indian Agricultural Research Institute, Indian Council of Agricultural Research, New Delhi, India
| | - V. Pooniya
- Indian Agricultural Research Institute, Indian Council of Agricultural Research, New Delhi, India
| | - T. K. Das
- Indian Agricultural Research Institute, Indian Council of Agricultural Research, New Delhi, India
| | - G. A. Rajanna
- Indian Agricultural Research Institute, Indian Council of Agricultural Research, New Delhi, India
- Directorate of Groundnut Research, Indian Council of Agricultural Research, Ananthapur, India
| | - Shiv Prasad
- Indian Agricultural Research Institute, Indian Council of Agricultural Research, New Delhi, India
| | | | - M. N. Harish
- Indian Agricultural Research Institute, Indian Council of Agricultural Research, New Delhi, India
- Farm Science Centre, Indian Institute of Horticultural Research, Indian Council of Agricultural Research, Gonikoppal, India
| | - Shiva Dhar
- Indian Agricultural Research Institute, Indian Council of Agricultural Research, New Delhi, India
| | - Raj Singh
- Indian Agricultural Research Institute, Indian Council of Agricultural Research, New Delhi, India
| | - Rishi Raj
- Indian Agricultural Research Institute, Indian Council of Agricultural Research, New Delhi, India
| | - Kavita Kumari
- Indian Agricultural Research Institute, Indian Council of Agricultural Research, New Delhi, India
| | - Arjun Singh
- Indian Agricultural Research Institute, Indian Council of Agricultural Research, New Delhi, India
- National Research Centre for Banana, Indian Council of Agricultural Research, Tiruchirappalli, India
| | - K. S. Sachin
- Indian Agricultural Research Institute, Indian Council of Agricultural Research, New Delhi, India
| | - Pramod Kumar
- Indian Agricultural Research Institute, Indian Council of Agricultural Research, New Delhi, India
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