Rice is a major staple food of Asia, where 92% of world rice is produced and consumed. Irrigated lowland rice consumes up to 5,000 liters of water to produce one kilogram of rice (IRRI). This is not sustainable in future as the per capita water availability is expected to decline by 15 to 54% by the year 2025 (Guerra et al. 1998). Besides, rainfed lowland and upland rice is cultivated in about 45% of the rice grown area in the country, which are subjected to intermittent soil moisture deficit that causes severe yield loss. Temperatures below 20ºC affect seedling establishment, fertilization and reproductive development (Yoshida, 1978) of Boro rice grown in North-Eastern India, rice cultivated in hills and late sown/transplanted rice in the plains of North India.

In order to design rice genotypes with higher yield and greater stability under moisture deficit and low temperature stresses, the phenotype-genotype gap must be bridged. Conventional phenotyping approaches are time consuming, less accurate and often associated with sacrifice of valuable genetic material. Modern high throughput non-destructive phenomics offers a solution to these problems. Hence, the project proposes to study the soil-moisture deficit and low temperature stress tolerance phenome taking rice as a model which can be expanded to more traits and crops based on the knowledge and experience gained in rice.


A long-term vision is to accelerate gene discovery and genetic improvement of crops for agriculturally important traits by integrating precision phenomics with the fast emerging genomic information.


Non-destructive and real-time phenome analysis will provide greater precision to understand nature of moisture-deficit and low temperature stress tolerance and thus help efficient utilization of germplasm and genomic resources for genetic enhancement of rice.

Selection of the crop and the stresses for phenomics

Rice crop was selected for phenomics in this project because of its importance as a major food crop, availability of diverse germplasm resources, the need to enhance water use efficiency and low temperature stress tolerance, and the vast available background knowledge of its physiology, genetics and genomics. Moisture deficit and low temperature stress tolerance phenome of temperate and tropical germplasm of Oryza sativa L. spp indica will be studied.

A.     Soil-moisture deficit stress

Soil moisture deficit stress is defined as “the soil moisture deficit at the root zone that significantly reduces/inhibits crop growth, development and yield”. Plants will be grown in rainout shelters (Arkin et al., 1975, 1976) or in climate controlled glass house of phenomics facility. Imposition of moisture deficit stress and evaluation of stress tolerance will be carried out according to the methods outlined by International Rice Research Institute (IRRI), Philippines (Fischer et al., 2003). Drought susceptibility index (Fischer and Maurer, 1978) analysis will be used to rank the genotypes for their moisture deficit stress tolerance.

B.     Low temperature stress

The temperatures below 20ºC affect seedling growth, fertilization and reproductive development for rice (Yoshida, 1978). Daily mean maximum and minimum temperature of the target region for the last 20 years will be used to simulate the normal temperature environment in climate controlled green houses. To impose low temperature stress in climate controlled green houses, the temperature during the critical growth stages will be decreased by 3°C. Change in temperature will be gradual and will be simulated in sinusoidal form. Cell membrane stability, chlorophyll fluorescence, growth and yield components will be recorded in high volume low-end phenotyping facilities. Genotypes will be ranked based on yield stability calculated in terms of stress susceptibility index (Fischer and Maurer, 1978).

Use of high precision phenomics facility

For precision phenotyping of both moisture deficit and low temperature stress tolerance, the following approach will be employed using non-destructive real time phenomics facility after imposing stresses: i) Different established imaging techniques such as high definition color imaging, near infrared imaging, far infrared imaging and fluorescence imaging will be used to monitor soil and plant water status, water use, physiological state of photosynthetic machinery, plant growth and yield traits, ii) effort will be made to measure carbohydrates and protein content using hyperspectral imaging after necessary standardization, iii) at maturity (about 30% grain moisture content), yield and yield component will be recorded, and the results of phenotyping of germplasm from regional hubs will be correlated with the image based precision phenotypes obtained at the central hub to identify reliable parameters and understand the components of stress tolerance phenome.

Scope for expansion of phenomics facility in the next phase

Since it is the learning phase, the proposed phemincs project aims to establish a medium capacity phenomics facility with a moving-field controlled environment glasshouse for 544 pots, with an imaging station. In the next phase, additional moving-field controlled environment glasshouses can be built and linked to the existing imaging station through appropriate conveyer system. Imaging station can also be upgraded to include high resolution NMR-based imaging of roots in soil. All the software for image analysis will be updated in the next phase. The hands-on expertise gained in the initial learning phase of phenomics will be the foundation for future expansion of phenomics research to include more traits and crops.

Operational model

The project would operate in the model of hub and spoke (Figure 1). National Research Centre on Plant Biotechnology (NRCPB) and Indian Agricultural Research Institute (IARI), where the high precision phenomics facility will be located, will be the central hub. The central hub will have active involvement of plant physiologists and soil physicist. There will be two regional hubs: one on moisture stress tolerance and another on low temperature stress tolerance. The participating centres in the regional hubs will carry out large scale phenotyping of germplasm and will act as feeder facilities for the Central hub with regard to short-listed germplasm.  Indian Agricultural Statistics Research Institute (ISARI) and Indian Institute of Technology (IIT) located at New Delhi will develop new designs for image capture and analysis, provide the computational support and help in creation of phenome data base. This project will utilize the expertise and facilities of National Agricultural Bioinformatics Grid (NABG) at IASRI, New Delhi, for phenome database development, management and its use. Further, the proposed project will exchange phenome information and germplasm with National Initiative on Climate Resilient Agriculture (NICRA) project. Phenotypic images obtained in open field imaging techniques and genotypes identified in NICRA will be validated in precision phenomics facility. Similarly, genotypes and phenome information obtained in the phenomics facility can be used by NICRA. The precision phenomics information on moisture deficit stress and low temperature stress tolerance of rice will be made available to the programmes on rice improvement in the National Agricultural Research System (NARS).  

Figure 1. The Operational Model


Consultancy and human resource development

Consultants from Australian Plant Phenomics Facility (APPF) and Jülich Phenomics Centre (JPC) will be invited at three different stages namely establishment of phenomics facility, standardization of operation and data analysis for one week duration each. Three scientists, one each in the area of biophysical aspects image capture and analysis, biological aspects of phenomics and computational aspects of phenomics will be trained at Australian Plant Phenomics facility, Jülich Phenomics Centre and Cold-Spring Harbor Lab, respectively, for a duration of three months. Six scientists will visit different phenomics facilities for one week duration each to gain knowledge on different aspects of phenomics.