Introduction

Estimates of 60 to 100% higher demand on agricultural products by 2050 compared to 2000 (Alexandratos and Bruinsma 2012) put tremendous pressure on global food security mission. The World Food summit-FAO (1996) stated: “Food security exists when all people, at all the time, have physical, social, and economic access to sufficient, safe and nutritious food, which meets their dietary needs and food preferences for an active and healthy life”. Enhanced production and productivity of the semi-dwarf, photoperiod-insensitive, fertilizer-responsive, non-lodging wheat and rice varieties produced during the Green Revolution helped avert food shortage in the 1960s (Pingali 2012). Fertilizers, agrochemicals and farm machinery also contributed, but ensuing excessive use of synthetic fertilizers/pesticides adversely affected soil and human health (Pingali 2012). Currently, yield stagnation in 25–40% of the croplands even in agriculturally advanced nations (Ray et al. 2012), decreasing agricultural land area, water and labour issues and postharvest losses aggravate food insufficiency scenarios, all of which aggravate the challenge of feeding ~ 10 billion people by 2050 (Tripathi et al. 2019).

Climate change vagaries further compound agricultural problems. Environmental stresses of heat, cold, drought, flooding and salinity are becoming more severe and frequent. Heat and drought stress decreased cereal production by ~ 6% between 2000 and 2007 (Lesk et al. 2016). Heat stress from rising surface temperature over the years will adversely affect plant physiology, development, reproduction and yield (Bailey-Serres et al. 2019). A 1 °C rise in temperature can cause ~ 8% yield loss of milled rice (Lyman et al. 2013). Arable land degradation due to salinity affects ~ 62 Mha (20%) of the world’s irrigated lands, corresponding to a loss of ~ $27 billion/annum (https://unu.edu/media-relations/releases/world-losing-2000-hectares-of-farm-soil-daily-to-salt-induced-degradation.html). Salinity in arid and semi-arid farms is due to salt retention after heat-induced evaporation, and in the coastal farmlands due to the incursion of seawater in the deltas due to receding river waters during weak monsoons.

Climate change also influences and aggravates biotic stresses, e.g., bacterial, fungal, viral infections, insect and pest infestation. Worldwide, 25–40% of rice and corn and 10–30% of wheat is lost to plant diseases (Savary et al. 2019). The recent crop and economic losses due to Fall Army Worm infestations, even for Bt-corn, illustrate the gravity of the situation (Bengyella et al. 2020). A better understanding of the relationships between biotic stress factors and the climate, and possible remedial solutions are necessary.

Postharvest losses account for significant reductions in the supply chain. About one-third of edible food at the farmgate level is lost annually (1.4 billion tons, ~ USD 1 trillion) due to inadequate postharvest handling and storage (Sawicka 2019). Decreasing postharvest losses would be inseparable from increasing food security (http://www.fao.org/docrep/004/y3557e/y3557e08.htm).

Unsustainable agricultural activity per se causes many problems. Nearly 70% of groundwater withdrawals are for irrigated agriculture (CAST 2019) and water extraction rate exceeding natural replenishment progressively depletes the water table. Expensive water abstraction machinery raises the cost of food and harms the environment by drawing water from deeper sources, further threatening food security (Dalin et al. 2017). Thus, addressing the land, water, labour and postharvest problems under climate change vagaries must include improved agronomic management and best practices. Systems-based landscape level cropping patterns and farm resilience go hand-in-hand with improving crop yield. The balance between intensification and diversification is important for the environment/biodiversity and sustainability. A multifaceted, trans-disciplinary approach for enhancing sustainable food production is necessary (Hellin et al. 2020a) where conventional breeding and agronomy are supported not only by modern genetic engineering and/or genome-scale breeding and precision agriculture technologies, but also by appropriate inputs from socio-economic and policy dimensions (Hellin et al. 2020b).

Rice at the centre stage of global food security efforts

Rice is an important grain crop supporting over half of the world's population. About 85% of rice from ~ 164 Mha is used for human consumption compared to 72% wheat from ~ 214 Mha (http://www.knowledgebank.irri.org/ericeproduction/Importance_of_Rice.htm). Rice is special among cereals because: (a) unlike other cereals it is largely used as grain rather than flour, (b) it is the staple crop of the majority of the poor and hungry population targeted by the global sustainable development goals (http://ricecrp.org/rice-and-the-sdgs/). Millions of small holder and landless farmers rely solely on rice production for their food and livelihood. However, an estimated decline in average rice acreage from 164 Mha in 2017 to 155 Mha by 2050 (Shahbandeh 2019) coupled with estimated yield losses due to biotic/abiotic stresses and post-harvest losses should trigger rapid response alarms.

Rice is second to corn in providing global caloric intake and fourth after corn, wheat, dairy and eggs as a source of protein, because cereals account for the large part of dietary protein intake. Also, rice can grow in the widest range of eco-geographies and environment where other crops cannot (http://ricepedia.org/rice-as-a-crop/where-is-rice-grown). Thus, rice as a source of calories and protein is the bedrock component in a balanced diet for the world’s poor. Improving rice quantity and nutritional quality thus promises the easiest route to socio-economic transformation of the vulnerable groups. Over a period of 25 years (1985–2010), improved rice varieties generated through International Rice Research Institute (IRRI)’s efforts amount to a Net Present Value of USD 9.91, 4.27 and 4.85 billion in Indonesia, Philippines and Vietnam, respectively (Brennan and Malabayabas 2011). This substantially improved the status of the extremely poor over the 25 years in these countries, which are now progressive transition economies. Thus, rice must be improved for its nutritional quality to address the double burden of micronutrient deficiency and obesity prevalent in disparate sets of populations in the transition economies.

The looming food crisis driven by demography and climate change can be averted by concerted multidisciplinary research for a pipeline of transforming innovations with socio-economic impacts. Cogently connected up-, mid- and down-stream science of molecular, organismal and topographical considerations, respectively, must be responsive to societal imperatives of prosperity and equity for relevance and value. Most up- and mid-stream plant research never reaches the targeted farmers/customers, and when it does, it is rarely monitored and evaluated for learning and impact on the society. A circular research model starting from socio-economic understanding of climate, market and policy change-based product profile, leading to product development and deployment must end with socio-economic impact assessment.

Using rice as an example we discuss some tested and potential strategies for sustainably enhancing crop productivity and system resilience under the progressively challenging environment. Plant biotechnological and breeding approaches for combating stresses, followed by the role of precision agriculture in water, land, nutrients and postharvest management are considered. The scope to integrate these into landscape-level solutions and facilitate socio-economic transformations is explored. Figure 1 captures a proposed framework where rice research goes all the way from genes and genotypes to potentially influencing policies for clear impact on prosperity, guided by the relevant drivers and enablers.

Fig. 1
figure 1

A proposed framework showcasing how rice-based agrifood systems can help to achieve sustainable developmental goals (SDGs) and bring about transformational shifts in the quality of life and environment. The framework also suggests that rice research can be directed to influence upcoming policies for zero hunger and good health

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Sustainable rice yield increase underpins global food and nutritional security

The Green Revolution rice (IR8) and wheat (Rojo64) varieties are archetypical examples of how the breeding of elite crop varieties made a difference (Nelson et al. 2019). There is a rich history of attempts at increasing yield, but not quality. Such increase in grain varieties unwanted by customers is a waste of resources. Hence, increasing yield towards a product profile is now the desirable aim (Custodio et al. 2019). Interfacing conventional and modern approaches is important to fast-track such a process (Kohli et al. 2019) using the following ‘breeding by design’ approaches.

Conventional hybridization

This time-tested strategy was crucial in developing high yielding rice varieties, but it did not reduce agrochemical and water inputs. Rice varieties released in India between 1974 and 1994 exhibited genetic gain of 1.2% for irrigated rice, but rainfed upland farms on marginal soils registered 1.3% yield decrease (Muralidharan et al. 1996). Conventional breeding is dependent on the available genetic variability, including from the wild relatives. Such efforts resulted in genetic yield increase of 1.9% even under severe reproductive-stage drought in India (Kumar et al. 2021). Breeding for improved submergence tolerance generated ‘FR13A’ rice, which was 100% tolerant to 7-day complete submergence but had poor agronomic characteristics (Ahmed et al. 2013). ‘FR13A’ was improved to generate commercially successful varieties ‘IR 49,830-7-1-2-2’ and ‘Sudhir’ (Khan et al. 2015). The cloning of Sub1A gene resulted in improved mega-variety ‘Swarna-Sub1’ tolerant to 14 day-submergence (Bailey-Serres et al. 2010).

Ideotype breeding

The rice varieties generated through conventional breeding after 1990 were resistant to many diseases and pests, but lacked grain yield advantage (Muralidharan et al. 2019). Ideotype breeding envisioned modification of the plant architecture to enhance yield. Yield improved because of decreased lodging in ‘IR8’ rice (Nelson et al. 2019). The ‘New Plant Type (NPT)’ envisioned 200–250 grains/panicle, without unproductive tillers or unfilled lower spikelets (Khush 2013). However, its grain quality was inferior and hence, the product undesirable. Marketable grain quality must always accompany yield increase. China’s ‘super’ rice exemplifies ideotype breeding, where the F1 hybrid varieties are a combination of ideotype and intersubspecific heterosis (Peng et al. 2008; Yuan 2017). The hybrid had NPT features, namely, increased grain numbers, reduced tillering and improved lodging resistance. Further improvement was made by achieving the top three leaves of the canopy, instead of the lone flag leaf, to supply increased photosynthates to the large panicles (Peng et al. 2008). Taken together, the NPT and ‘super’ rice exemplified that ideotype breeding could break yield barriers.

Molecular breeding

The advent of molecular technologies and PCR in the 1980s improved on older tools, e.g., restriction fragment length polymorphism and led to several PCR-based markers that were used to trace genomic segments relevant to crop improvement. Subsequently, genome sequencing led to identifying numerous DNA-based markers for marker-assisted selection (MAS). This helped in screening for difficult, expensive or time-consuming traits at any growth stage while distinguishing heterozygotes. Molecular markers served to understand polygenic traits with quantitative trait loci (QTLs). The merger of MAS with QTLs contributed significantly towards boosting yield (Segami et al. 2016) and improving the nutritional quality of rice (Mahender et al. 2016). QTLs are known for yield component traits, e.g., panicles/plant, grains/panicle and grain weight. For panicle number QTLs pn4, pn6 (Rahman et al. 2008) and qPN2 were identified from an eight-way multi-parent advanced generation intercross (MAGIC) population (Meng et al. 2016). Introduction of GW6 to indica variety ‘HJX74’ caused 10.44% yield increase by promoting grain width and weight (Shi et al. 2020). In most studies, information on grain quality was missing. Recently, a gene has been identified that increases secondary branches in the upper parts of the panicle, generating more filled spikelets, and thus increasing the yield of good quality grains (Pasion et al. 2021).

Pyramiding of QTLs or their causative genes in a single elite cultivar can integrate multiple traits. Pyramiding sd1 (semi-dwarf gene), Sub1A (submergence tolerance), Pi9 (blast resistance) and Xa21 and Xa27 (bacterial blight resistance) in ‘Khao Dwak Mali 105’, an elite Thai aromatic rice, led to semi-dwarf, lodging- and submergence-tolerant plants (Luo and Yin 2013). The semi-dwarf, biotic and abiotic stress tolerant aromatic ‘Temasek Rice’ variety requires low inputs, which further exemplifies the gene pyramiding power of MAS (http://www.tlv.sg/news/singapore%E2%80%99s-temasek-rice-developed-by-tll-scientists-for-regional-food-security/).

Genomic breeding

Use of very high-density MAS underpins breeding by genomic selection (GS). Data correlating high-throughput genotyping and phenotyping on a test population are used by computer models to predict performance from the genotype. Multitude of DNA markers define a genotype and a combination of markers can predict the performance of traits. Low coverage sequencing of a large number of rice accessions can feed the GS models for increased prediction accuracy on the performance of individuals from biparental or multiparental populations. GS is useful for complex traits controlled by multiple genes and its prediction accuracy saves time and resources spent on phenotyping. Different prediction models can be tested and the most effective one identified for improving a complex trait, e.g., for rice blast disease resistance. Combining the GS approach with genome-wide association studies (GWAS) was shown to be more effective and such GS models work better for some traits (Spindel et al. 2015).

Genetic engineering

The availability of genome sequences and efficient functional genomics tools, including insertion mutagenesis and genome-wide expression profiling have helped identify candidate genes for crop improvement. Biswal et al. (2017) provide details of rice crop improvement by overexpression or silencing of many genes. High Mobility GroupB (HMGB) genes were identified from rice (Wu et al. 2003a, b), and overexpression of this class of genes conferred stress tolerance to Arabidopsis (Kwak et al. 2007). The ‘Golden Rice’ project shows how biofortification of rice with β-carotene by genetic engineering can prevent Vitamin A deficiency aimed at preventing blindness in children (http://www.goldenrice.org/). Similarly, Fe-biofortified ‘IR64’ rice with 15 µg/g Fe in polished grain has been generated (Trijatmiko et al. 2016). Genetic engineering approaches have also been exploited for manipulating plant architecture for improving rice crop yield. RNAi-mediated suppression of OsPIN5b, an auxin carrier protein, leads to pleiotropic effects, such as, higher tiller number, longer panicles and higher grain yield (Lu et al. 2015). A recent review has highlighted modulation of miRNAs as a potential genetic engineering tool for enhancing rice yield by manipulation of plant architecture (Kaur et al. 2020). The recent approval for cultivation of the Golden Rice in the Philippines and its prior approval for consumption in Australia, Canada and New Zealand are encouraging for the appropriate use of GM tools for rice crop improvement. Collectively, these examples highlight the potential contribution of genetic engineering in identifying new gene families and utilizing them for rice improvement.

Genome editing

This technique exploits site-specific nucleases (SSNs) to precisely add, delete or substitute DNA bases in selected genes. The SSNs include zinc finger nucleases (ZFNs), transcriptional activator-like effector nucleases (TALENs) and clustered regularly interspaced short palindromic repeats (CRISPR)-associated endonuclease Cas9 (CRISPR/Cas9; Manghwar et al. 2019). Identification of CRISPR/Cpf1 has opened up new avenues for genome editing because of its better DNA cleavage efficiency over CRISPR/Cas9 (Zetsche et al. 2015). Base editor technology that enables direct conversion of target bases without the need for DNA-strand break has been developed (Komor et al. 2016). CRISPR/Cas9 tool has broadened the horizon of rice yield improvement programs. Knocking out genes that limit yield and quality parameters, e.g., GS3, DEP1 and Gn1a caused significant increase in rice production with plants having dense erect panicles, larger grains, and enhanced grain number (Li et al. 2016). The editing tool also enables pyramiding null mutants in a single cultivar. Simultaneous mutation of GW2, GW5 and TGW6 (triple null) using CRISPR/Cas9 editing caused 29.3% increase in grain weight (Xu et al. 2016). CRISPR/Cas9 is being used to generate large-scale rice mutant libraries for functional genomics and genetic improvement (Meng et al. 2017).

A systems approach in up-, mid- and down-stream science is essential for impact

Designing effective projects depends on streamlining the upstream discovery component for proof-of-concept to midstream validation of a scaled model, downstream deployment and final impact assessment. The discovery component is facilitated by molecular data such as genome sequences, and integrative science such as understanding photosynthesis in terms of optimal water and assimilate utilization.

Upstream discovery science

The 3000 rice genome project

The genomic information gathered so far has helped to identify numerous genes to challenge the existing yield barriers. Transgenic rice lines generally stop at functional validation due to the tough regulatory barriers, limiting their commercialization. However, superior alleles can be discovered from a wider gene pool, and after transgenic validation, be used in conventional breeding to introgress the trait to the desired elite background. To harness the vast genetic diversity available within wild and domesticated rice, IRRI, the Chinese Academy of Agricultural Sciences and Beijing Genomics Institute sequenced over 3000 rice genomes (3K-RGP 2014). Molecular breeders and genetic engineers can use the generated sequence data, single nucleotide polymorphisms (SNP) and structural variations—deletions, duplications, inversions and translocations—among the 3010 rice genomes (Wang et al. 2018). Using the 3K-RGP information, tight linkage between semi-dwarf mutant gene, sd1 and drought susceptibility genes was discovered in all semi-dwarf varieties, and the linkage could be broken in some naturally occurring or breeding lines (Vikram et al. 2015).

Enhancing photosynthetic efficiency

Photosynthesis is the primary determinant of plant growth, development and yield. Genetic manipulation to enhance photosynthesis has been attempted in three processes: photosynthetic efficiency, photorespiration, and electron transport. Photorespiration was targeted because it decreases carbon assimilation (Walker et al. 2016a, b) and the GOC bypass (named for three enzymes: glycolate oxidase, oxalate oxidase, catalase) was established in rice chloroplast using a multi-gene assembly, which resulted in improved characteristics (Table 1). Photosystem components, including electron transport system (Table 1; Ramamoorthy et al. 2018; Zulfugarov et al. 2014) and biophysical CO2 concentrating mechanisms (CCM) have been genetically modified. Rubisco converts nearly 90% carbon into biomass but its slow catalytic rate and competing oxygenation reaction are limiting factors for carbon fixation (Erb and Zarzycki 2018). In cyanobacteria and algae, conversion of bicarbonate into CO2 occurs in a compartment to increase the CO2 available for Rubisco. Similarly, C4-plants possess a CCM to enrich CO2 around Rubisco (Karki et al. 2013). Computational modeling and transgenesis in model plants suggested prospects of engineering algal CCM in rice (Table 1). Accordingly, the C4 rice project aims to generate varieties possessing C4 photosynthesis (Ermakova et al. 2020; Karki et al. 2013; Nomura et al. 2005). Since the inception of the international C4 rice consortium in 2008, substantial progress has been made in identifying several unknown components of C4 biochemistry. An important contribution of the consortium includes the transcriptomes of bundle sheath and mesophyll cells of multiple C3 and C4 plant species (Schuler et al. 2016). The data helped to identify putative candidate genes with their cell-type specific expressions and metabolite shuttling between the two cell types. However, some of the key aspects, such as, photosynthetic functionalization of the bundle sheath still remains an important step for C4 rice development (Ermakova et al. 2020). Greater ATP requirement for C4 photosynthesis is another challenge that needs to be addressed to achieve C4 rice. Contemporary successes in manipulating photosynthesis were contextualized for their downstream socio-economic impacts (Kohli et al. 2020). Parallel research on nutrient and water use efficiencies is recommended, e.g., how stomatal density promotes photosynthesis, water use efficiency and drought tolerance.

Table 1 List of potential target genes for manipulating photosynthesis in rice & proposed strategies for engineering CCM
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Combating biotic stresses

Annually 25 to 40% of rice is lost to pests and diseases (Sparks et al. 2012). Fungal blast caused by Mangaporthe oryzae and bacterial leaf blight caused by Xanthomonas oryzae pv oryzae (Xoo) severely reduce rice yield. Genetic analyses identified more than 100 genes conferring resistance to M. oryzae (Sharma 2012). Resistant lines were developed by introgressing blast resistance genes Piz-5 and Pi-54 into Basmati rice restorer line ‘PRR78’ (Singh et al. 2013). Furthermore, blight (Xa-13, Xa-21) and blast (Pi-54, Pi-1) resistance genes were pyramided into the mega-variety ‘Tellahamsa’ conferring resistance against both pathogens (Jamaloddin et al. 2020). Xoo acts by secreting transcription-activator-like effectors that bind to specific promoter sequences and induce sucrose transporter (SWEET) genes. This host susceptibility function was blocked by CRISPR/Cas9 editing of five SWEET gene-promoters in ‘Kitaake’ rice resulting in robust broad-spectrum resistance against Xoo (Oliva et al. 2019). New genetic tools, e.g., small interfering RNA and host-induced gene silencing have also been utilized (Guo et al. 2019).

Brown planthopper (BPH) also affects rice crop substantially by feeding inside the panicle stalk causing unfilled grains called “white heads”. Several QTLs and genes for BPH resistance are known. Constitutive expression of Bacillus thuringiensis genes [cryIA(b), cryIA(c)] increased BPH-resistance without yield penalty (Tu et al. 2000). Ideally, lines with multiple stress tolerance/resistance without yield penalty can be achieved by introgressing multiple polygenic traits governed by QTLs, a challenging but possible approach being attempted by refining the marker technologies (Platten et al. 2019). Table 2 lists some genes that regulate abiotic stress tolerance and grain yield that may be used to drive future crop improvement strategies.

Table 2 Gene families regulating abiotic stress tolerance and agronomic traits in rice
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Combating abiotic stresses

Abiotic stress tolerance can rarely be treated as a single trait unlike biotic stresses. Thus, heat stress accompanies drought, salinity causes physiological dehydration, drought exacerbates nutrient stress, flooding imparts oxygen and nutrient stresses, and redox stress accompanies most stresses. Due to such complex polygenic control of tolerance, QTLs are at the forefront of effective solutions, e.g., Saltol for Na+/K+ ratio (Gregorio 1997) conferring salinity tolerance to seedlings. Genetic engineering approaches have also played an important role in improving the abiotic stress tolerance of rice. Rice plants overexpressing OsDREB transcription factors showed enhanced tolerance to salinity stress (Mallikarjuna et al. 2011). Similarly, overexpression of OsSAPK4 accumulates less Na+ and Cl− and shows improved photosynthesis (Diedhiou et al. 2008). Other genes for salt tolerance in rice (Hoang et al. 2016) include, NHX1 from the mangrove Avicennia officinalis (Krishnamurthy et al. 2019), OsTPS8 (Vishal et al. 2019) and OsCYP94B1 from rice (Krishnamurthy et al. 2020).

A large effect QTL (LEQ) qDTY12.1 explained nearly 51% of the genetic variance for grain yield under drought (Dixit et al. 2015). The need for the entire QTL containing multiple genes to confer stress tolerance provided a mechanistic explanation, which was supported by proteomic and metabolomic studies on qDTY12.1 (Raorane et al. 2015a, b). For drought stress, transcription factors and genes targeting root morphology and root system architecture have also been considered (Biswal et al. 2017).

Engineering of OsRR22 by CRISPR/Cas9 led to significantly high salinity tolerance at the seedling stage (Zhang et al. 2019). Development of mutant alleles of drought and salt tolerance (DST) by CRISPR/Cas9 editing in ‘MTU1010’ indica cultivar also resulted in moderate tolerance to osmotic stress and high tolerance to salt stress (Kumar et al. 2020). Adaptation to low temperature has also been achieved by editing TIFY1a and 1b genes (Huang et al. 2017). CRISPR/Cas9-mediated knockout of osmotic stress/ABA-activated protein kinase 2, OsSAPK2, revealed a critical role of OsSAPK2 in ABA signalling cascade and hence, in abiotic stress tolerance, as the mutant plants were susceptible to stress conditions (Lou et al. 2017). CRISPR/Cas9 also improves abiotic stress tolerance by knocking out transcription factors negatively regulating tolerance-responsive genes. The knockout of R2R3-type OsMYB30 by CRISPR/Cas9 increased grain yield and cold tolerance in mutant as compared to wild-type rice plants (Zeng et al. 2020). Identification and functional characterization of these and other such genes will help in gene editing for rice crop improvement.

Manipulating hormonal signalling

Advances in the knowledge of genetic networks underpinning hormone signalling pathways have also played a vital role in improving our understanding of abiotic and biotic stress responses (Hoang et al. 2016; Kumar 2013; Verma et al. 2016). Different plant hormones function independently as well as with complex signal interactions to stimulate an effective response against the different stresses faced. One of the earlier findings exhibiting significant reduction of endogenous bioactive GAs in response to salinity stress provided a vital breakthrough about the integral role of plant hormones in ameliorating stress responses (Achard et al. 2006). GA biosynthetic mutant, ga1-3, also showed enhanced survival in salt stress conditions. GA signalling also impacts reactive oxygen species (ROS) levels, as DELLA proteins, the negative regulators of GA signalling, stimulate the expression of genes encoding ROS detoxification enzymes (Achard et al. 2008). More recently, it has been shown that GA can rescue seed germination in mutant rice line with impaired brassinosteroid signalling that otherwise fails to initiate seed germination (Li et al. 2020).

With the genomic information, we now know that the breeding efforts that led to the successful Green Revolution rice variety ‘IR8’ arose from inadvertent loss of function of SD1 gene. SD1 encoded a key enzyme GA20 oxidase necessary for gibberellin (GA) biosynthesis, and the plants with this mutation have reduced amount of bioactive GA leading to semi-dwarf phenotype (Ashikari et al. 2002). The DELLA family of GA signalling intermediates consists of five members in Arabidopsis and two genes in corn. However, based on the constitutive GA response phenotype of slr1 mutants, there appears to be only one member of the DELLA family in rice, namely, SLR1 (SLENDER RICE 1). Additionally, two sequences homologous to SLR1: SLR1-like1 and -2 (SLRL1, SLR2) have been identified in rice genome databases. Although SLRL1 and SLRL2 contain regions with high similarity to the C-terminal conserved domains in SLR1, they lack the N-terminal conserved region of the DELLA proteins. Transgenic rice plants overexpressing SLRL1 or SLRL2 also exhibited a GA‐insensitive dwarf phenotype, indicating that the proteins may function as repressors of GA signalling (Liu et al. 2007; Itoh et al. 2005). These findings suggest that GA signalling pathway intermediates are prime candidates for crop breeding to modify plant height.

Auxins, another major developmental hormone, are also modulated by salinity stress as the stress influences the growth and direction of root growth. About 31 OsIAA genes, genes encoding repressors of auxin signalling, and 25 OsARF genes, genes encoding transcriptional activators of auxin signalling, in rice were found to be induced by salinity stress (as well as in drought; Song et al. 2009). The activation of OsPIN3t, the auxin transporter, providing drought tolerance to rice plants and its knockdown resulting in crown root abnormalities at the seedling stage also offered a strong piece of support to the role of auxin signalling in abiotic stress responses (Zhang et al. 2012).

Cytokinins, generally known for stimulating cell division and differentiation, are also found to be linked to different abiotic stresses. Plants that overexpress Cytokinin oxidase (CKX) exhibited higher tolerance to drought stress (Werner et al. 2010), a phenomenon also shown by mutants having decreased cytokinin content. On the contrary, another study showed that expression of the cytokinin biosynthetic gene, Isopentenyltransferase (IPT), also resulted in enhanced drought tolerance in rice (Peleg et al. 2011). This signifies that both increase and decrease of endogenous cytokinin levels and possibly their signalling intermediates should be explored in efforts to improve stress tolerance in plants.

Abscisic acid (ABA) is known as the “stress hormone” as it is one of the most important messengers in facilitating adaptation of plants to different abiotic stresses. ABA regulates the expression of a myriad of stress-responsive genes including dehydrins, LEA and those responsible for the accumulation of compatible osmolytes. Overexpression of rice ABA receptors was also able to improve drought tolerance by activating stress-responsive genes (Kim et al. 2014). The importance of ABA is evident from the study involving overexpression of ABA biosynthetic gene 9-cisepoxycarotenoid dioxygenase (NCED), which causes an increase in endogenous ABA levels with corresponding reduction in stomatal density and elevated drought tolerance in transgenic Arabidopsis plants (Iuchi et al. 2001). In Arabidopsis the stomatal development is known to be regulated by several bHLH transcription factors, namely, SPEECHLESS (SPCH), MUTE, FAMA, and SCREAM (SCRM) and SCRM2 (Lau et al. 2014; Buckley et al. 2020). The feasibility of modifying genetic mechanisms associated with this developmental pathway along with some of the lesser-known genes such as SCARECROW, SHORTROOT and selected Cyclin-Dependent-Kinases has been discussed for improving drought tolerance in rice and other monocotyledons (Buckley et al. 2020).

Besides the major plant hormones mentioned above, jasmonic acid (JA), salicylic acid (SA) and ethylene (ET) also play crucial roles in regulating plant abiotic stress responses. Overexpression of Ethylene Response Factors (ERFs), considered as the effectors of ET signalling, exhibited enhanced drought tolerance, owing to the expression of stress-responsive genes including proline biosynthesis (Zhang et al. 2010). JA levels were also found to be upregulated in the roots and leaves of rice plants in response to drought and salinity stress conditions (Kiribuchi et al. 2004). Similarly, a vital SA biosynthetic enzyme was induced upon salt stress resulting in enhanced SA levels in rice seedlings (Sawada et al. 2006). Taken together, it is evident that phytohormone signalling pathways can be effectively engineered to develop stress-tolerant crops without severe yield penalties. However, more extensive work is required to completely harness the underlying potential. A key aspect that requires intensive focus is hormonal crosstalk, because, hormones are known to function in a synergistic mode, rather than acting independently.

Midstream crop and resource management science

Applying water conservation approaches

The amount of water used in rice cultivation, which is almost 50% of all agricultural irrigation, must be reduced. In one approach called Alternate Wetting and Drying (AWD), fields are subjected to intermittent rather than continuous flooding (http://www.knowledgebank.irri.org/training/fact-sheets/water-management/saving-water-alternate-wetting-drying-awd). AWD reduces 20–30% water, reduces methane and nitrous oxide emissions and improves soil quality and fertility by helping the absorption of zinc and nitrogen (Allen and Sander 2019). System of Rice Intensification (SRI) is another technology that improves water use efficiency by promoting larger root system and better root biota, thereby providing additional environmental benefits (https://www.echonet.org/the-echo-update-blog/2013/7/10/improved-rice-production-system-of-rice-intensification).

Improved cropping system management

Intensive farming with poor crop management practices has led to loss of soil fertility and nutrient deficiencies. Diversification is key to sustain rice productivity. Rice rotation with legumes/pulses is a highly productive cropping system. It is good for biological nitrogen fixation; reduction of disease, pest and weed incidence; provides protein-rich food and feed; and improves profitability as cash crops. The choice of the alternative crop (legumes, oilseeds, manure/feed) is critical and based on location, environment and synergism for higher productivity and efficient resource utilization.

Zero-tillage, a resource-conserving technology, has emerged as a key practice for improving productivity and food security while benefiting the environment (http://www.knowledgebank.irri.org/images/docs/reduced-and-zero-tillage-options.pdf). Crops are grown without tilling the soil, resulting in less greenhouse gas emission because of avoiding straw burning. The simplest zero tillage uses soil moisture and surface seeding without land preparation (http://www.knowledgebank.irri.org/images/docs/reduced-and-zero-tillage-options.pdf). It is preferred in non-puddled, dry direct-seeded rice (DSR) and overcomes water and labour shortage. IRRI has started DSR breeding program to address issues that limit DSR success, including weeds, nematodes, iron toxicity and mechanization.

Furthermore, parallel use of organic manures, e.g., farmyard manure (FYM) that is rich in nitrogen and other organic residues, can help to moderate the use of chemical fertilizers. Using the fallow periods for fast-growing green manures before rice transplantation also reduces nitrogen requirement by improving the soil and reducing leaching and denitrification (Sravan and Murthy 2014). Since 25% of nitrogen, 50% of phosphorus and 75% of potassium are retained in crop residues (Sravan and Murthy 2018), they are excellent for increasing soil organic content. Use of green manures also increases soil pore space. SRI combined with organic manures gives significantly higher yield compared to conventional fertilizers (Harikesh and Kumar 2018). Monitoring soil health via ‘soil health-card system’ that records various quality parameters, can better help to manage soil by replenishing only the depleted nutrients (Sravan and Murthy 2018).

Minimizing postharvest losses

Postharvest losses (PHL) account for the loss of nearly one-third of agricultural production globally (1.3 billion ton; Mopera 2016). For rice, PHL range between 15 and 25% in Southeast Asia (Gummert 2013). PHL occur all along the supply chain and include losses due to spoilage. Rice is more vulnerable to PHL in developing nations due to inadequate/inefficient technology, poor storage infrastructure and improper handling. Although grain loss occurs at harvesting, threshing, winnowing, and transportation, maximum loss happens during storage because traditional storage structures have high moisture levels inviting pests, pathogens and rodents. Fungal infection during storage leading to mycotoxin contamination, grain shattering during harvest and lack of accessible milling facilities add to PHL. Technologies such as fumigation and use of storage insecticides and pesticides can significantly reduce PHL. Synthetic insecticides, such as, methyl bromide and phosphine and plant-based chemicals, such as, leaves and oil extract of Chenopodium ambrosioides are effective in minimizing pest infestation. Lastly, airtight storage is useful in avoiding storage losses and chemical or pesticide use. Despite such importance, PHL has not received adequate attention. While food security efforts have focussed on improving rice production, mitigating PHL can significantly impact rice availability.

Downstream demand, deployment and distinction analysis

Meeting demand for nutritional rice

Rice improvement for nutritional security is a critical component of an integrated and holistic view on food security. Despite being seen as a nutritionally poor starch-rich food (largely due to generating polished white grains that are easily digestible, organoleptic grains), rice is rather rich in primary and secondary metabolites of nutritional value (Lee et al. 2019). Coloured or brown rice, partial milling, parboiling and germination-initiated rice are some routes to harness the innate and diverse nutritional attributes of different rice sub-types. To address micronutrient deficiency, especially for zinc, whose lack is critically associated with stunting in children, the mainstreaming of increased zinc in the breeding pipeline has been adopted (Swamy et al. 2016, 2018). Grain iron and zinc were increased in transgenic plants to useful levels for ameliorating micronutrient deficiency (Ludwig and Slamet-Loedin 2019). A recent report demonstrated that reduction of phytic acid content by RNAi-mediated silencing of multifunctional OsITPK5/6K-1, a major inositol triphosphate kinase (ITPK) homolog involved in phytic acid biosynthesis, is another approach for increasing iron and zinc content in the grain endosperm (Karmakar et al. 2020). The validity of increasing Vitamin A in the ‘Golden Rice’ grains is now well known and detailed characterization and safety assessment have been conducted (Swamy et al. 2019). Besides improving micronutrient and vitamin contents, there is also substantial progress in generating rice lines with low glycemic index (GI), as high GI is often considered unhealthy. Attempts have also been made to increase the lysine content of rice, as lysine is a limiting essential amino acid in rice. Expression of Lysine-Rich Protein (LRP) gene under endosperm-specific Glutelin1 (GT1) promoter increased lysine content in transgenic rice seeds by more than 30% (Liu et al. 2016). Additional quality traits of head rice recovery (HRR) during milling (Butardo and Sreenivasulu 2019), chalkiness (Santos et al. 2019), dietary fibre (Kosik et al. 2020), cooking traits (Misra et al. 2018) and secondary metabolites (Llorente et al. 2019) are also being actively addressed. CRISPR/Cas9 was used in improving the nutritional quotient of rice grains by targeting two rice starch branching enzymes SBEI and SBEIIb, with sbeII mutant showing significant increase in amylose and resistant starch content, which helps prevent diabetes (Sun et al. 2017).

Deployment of improved production systems

Demography and climate change call for improved production systems. Innovations to cope with climate change are clubbed under climate-smart agriculture (CSA). Three principles define CSA: (1) increasing agricultural productivity to support increased incomes, food security and development; (2) increasing adaptive capacity and resilience to climate variability at multiple levels (from farm to nation); (3) decreasing greenhouse gas emissions where possible and appropriate (Douthwaite et al. 2017). A sustainable increase in crop yield will spare the natural resources, including land, from agriculture (Phalan et al. 2016), allowing more biodiversity and affiliated land use that restore natural surroundings. Improved crop resilience can also lead to yield gains even with low investment by farmers with smaller land holdings, thereby resulting in increased incomes and social and economic security. Decreasing greenhouse gas emissions, particularly methane from inundated paddy fields will also have a significant impact on natural ecosystems. Globally, rice production fields emit about the same amount of greenhouse gases as Germany. Simple practices, such as, AWD, DSR and rice straw management can lower methane emissions by up to 70%. The challenges calling for CSA are extremely complex and they can be best addressed through trans-disciplinary professionals involving researchers, extension workers and policy specialists (Hellin et al. 2020b). Therefore, agricultural research must be integrated into a systems approach involving agronomists, environmental scientists and socio-economists along with plant breeders, geneticists and agricultural extension efforts. Figure 2 captures the major research areas that illustrate trans-disciplinarity. A new global consortium the “Sustainable Rice Landscapes Initiative” (https://www.unenvironment.org/news-and-stories/press-release/new-consortium-reduce-environmental-footprint-rice-production) will bring experts from research institutions, international organizations and influential business groups on a common platform to reduce the environmental footprint of rice production. The consortium aims to facilitate policy support from governments along with technical training.

Fig. 2
figure 2

The components of a multi-disciplinary systems approach required for improving rice yield and quality and increasing its influence on policies and markets. Introduction of gender-based products and scaling of innovative technologies can further extend the boundaries

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Concluding remarks and future directions

Despite being extensively studied in the last few decades, rice still has tremendous research scope. This is because it is eco-geographically most spread out and hence, the findings from one eco-geography may not hold in another. Hence, increased research investment in rice will address the socio-economic as well as the wide ranging eco-geographic diversities. A significant amount of resource allocation right at the upstream level will facilitate innovation at the core of the delivery pipeline. Moreover, the availability of vast amounts of genetic and genomic information, coupled with the rapid upsurge in the development of omics technologies at various levels, such as, genomes, epigenomes, transcriptomes, epitranscriptomes and proteomes will also contribute to the development of newer strategies for crop variety development. This ensures that the daunting task of maintaining food supply in the face of climate change can be accomplished. However, this would also entail institutional-level support by formulation of policies for fast-tracking delivery processes. For example, “seeds without borders” (https://www.irri.org/news-and-events/news/agreement-multi-country-seed-sharing-reached) espouses the cause that seeds of new varieties tested in a particular eco-geography should be available to countries with similar eco-geographies without the political blocks and time spent in re-testing within country boundaries.

It is imperative that innovation at all levels must be assessed for scientific as well as socio-economic relevance through the stage-gating progress. This would enable only the most impacting undertakings to proceed through the different stages of delivery. Thus, a circular research model (Fig. 3) that considers the monitoring, evaluation and learning to analyze if the demand has been met and it has made a socio-economic difference, should become an essential part of ‘research for development’. It is clear that sustained research efforts are needed to future-proof food security. The examples cited here are mainly for rice, but the approaches are also applicable to other cereal crops.

Fig. 3
figure 3

The ‘5D’ Cycle showing that a circular model consisting of demand, discovery, development, dissemination and distinction is essential to ensure that research efforts facilitate developmental goals

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