Abiotic stresses adversely affect rice yield and productivity, especially under the changing climatic scenario. Exposure to multiple abiotic stresses acting together aggravates these effects. The projected increase in global temperatures, rainfall variability, and salinity will increase the frequency and intensity of multiple abiotic stresses. These abiotic stresses affect paddy physiology and deteriorate grain quality, especially milling quality and cooking characteristics. Understanding the molecular and physiological mechanisms behind grain quality reduction under multiple abiotic stresses is needed to breed cultivars that can tolerate multiple abiotic stresses. This review summarizes the combined effect of various stresses on rice physiology, focusing on grain quality parameters and yield traits, and discusses strategies for improving grain quality parameters using high-throughput phenotyping with omics approaches.
Phosphorus (P) flow in agricultural land depends on the P taken off from harvested product, its losses through runoff and fertilizer applied to balance the removed P. Phytic acid (PA), the major storage form of phosphorus (P) in cereal grains is a key anti‐nutrient for human and non‐ruminants leads to eutrophication of waterways. As the natural non‐renewable P reserves are limited, enhancing P use efficiency is needed for field crops. SULTR‐like phosphorus distribution transporter (SPDT) is a novel rice transporter transfer P to the grain. Any alteration in transporter gene reduce grain P with concomitant rise in the leaves. A low PA (3.0 g/kg) rice Khira was identified where a single nucleotide mutation in LOC_Os06g05160 gene encoding SPDT showed low P transportation to grain. An amino acid change was detected as Valine‐330 to Alanine at the 3′ end of fifth exon. Highest expression of SPDT was observed in node I of rice as compared to low PA genotype. The mutation in SPDT could significantly affect P and PA accumulation in the grains with increased mineral bioavailability.
Practical applications
Excessive P application in crop leads to higher production cost as well as rapid depletion of limited rock phosphate. Alteration of P transporter function in the rice lower PA and total P accumulation in the grains with increased mineral bioavailability. The re‐distributed P in the straw can be applied as manure to the rice field. Thus, less P will be removed from the field, result in the decreased requirement for P fertilizer.
Quantitative trait loci (QTL) for rice grain weight identified using bi-parental populations in various environments were found inconsistent and have a modest role in marker assisted breeding and map-based cloning programs. Thus, the identification of a consistent consensus QTL region across populations is critical to deploy in marker aided breeding programs. Using the QTL meta-analysis technique, we collated rice grain weight QTL information from numerous studies done across populations and in diverse environments to find constitutive QTL for grain weight. Using information from 114 original QTL in meta-analysis, we discovered three significant Meta-QTL (MQTL) for grain weight on chromosome 3. According to gene ontology, these three MQTL have 179 genes, 25 of which have roles in developmental functions. Amino acid sequence BLAST of these genes indicated their orthologue conservation among core cereals with similar functions. MQTL3.1 includes the OsAPX1, PDIL, SAUR, and OsASN1 genes, which are involved in grain development and have been discovered to play a key role in asparagine biosynthesis and metabolism, which is crucial for source-sink regulation. Five potential candidate genes were identified and their expression analysis indicated a significant role in early grain development. The gene sequence information retrieved from the 3 K rice genome project revealed the deletion of six bases coding for serine and alanine in the last exon of OsASN1 led to an interruption in the synthesis of α-helix of the protein, which negatively affected the asparagine biosynthesis pathway in the low grain weight genotypes. Further, the MQTL3.1 was validated using linked marker RM7197 on a set of genotypes with extreme phenotypes. MQTL that have been identified and validated in our study have significant scope in MAS breeding and map-based cloning programs for improving rice grain weight.
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