Rice quality: How is it defined by consumers, industry, food scientists, and geneticists?

Mapping combined with principal component analysis identifies excellent lines with increased rice quality

Quality-related traits are some of the most important traits in rice, and screening and breeding rice lines with excellent quality are common ways for breeders to improve the quality of rice. In this study, we used 151 recombinant inbred lines (RILs) obtained by crossing the northern cultivated japonica rice variety ShenNong265 (SN265) with the southern indica rice variety LuHui99 (LH99) and simplified 18 common rice quality-related traits into 8 independent principal components (PCs) by principal component analysis (PCA). These PCs included peak and hot paste viscosity, chalky grain percentage and chalkiness degree, brown and milled rice recovery, width length rate, cooked taste score, head rice recovery, milled rice width, and cooked comprehensive score factors. Based on the weight ratio of each PC score, the RILs were classified into five types from excellent to poor, and five excellent lines were identified. Compared with SN265, these 5 lines showed better performance regarding the chalky grain percentage and chalkiness degree factor. Moreover, we performed QTL localization on the RIL population and identified 94 QTLs for quality-related traits that formed 6 QTL clusters. In future research, by combining these QTL mapping results, we will be using backcrossing to aggregate excellent traits and achieve quality improvement of SN265.

Effects of application of rapeseed cake as organic fertilizer on rice quality at high yield level

BACKGROUND

Applying organic fertilizer coupled with chemical fertilizer has been widely adopted to improve crop productivity and quality and develop sustainable agriculture. However, little information is available about the effects of organic fertilizer on the grain quality of rice (Oryza sativa L.), especially nutritional quality and starch quality. In the present study, high yielding 'super' rice cultivars were grown in the field with three cultivation practices, including zero nitrogen application (0N), local high yielding practice with chemical fertilizer (T1) and T1 treatment with additional organic fertilizer (T2).

RESULTS

Application of organic fertilizer synergistically improved rice production, nitrogen use efficiency, milling and appearance quality, and nutritional quality, including the contents of glutelin, essential amino acids and microelements, and also increased amylopectin and the ratio of the short chain of amylopectin, leading to a reduction in relative crystallinity, and decreased prolamin content. Application of organic fertilizer also increased the viscosity and breakdown values, whereas it decreased the pasting temperature and gelatinization enthalpy, resulting in better cooking and eating quality.

CONCLUSION

Overall, application of organific fertilizer could synergistically improve nitrogen use efficiency and grain quality, including the structure and physicochemical properties of starch, contents of high value protein and amino acids, contents of microelements, and cooking and eating quality. © 2021 Society of Chemical Industry.

Elementomics combined with dd-SIMCA and K-NN to identify the geographical origin of rice samples from China, India, and Vietnam

The COVID-19 pandemic has impacted the food industry and consumers, with production gaps, shipping delays, and changes in supply and demand leading to an increased risk of food fraud. Rice has a high probability for adulteration by food fraudsters, being a staple commodity for more than half the global population, making the assessment of geographical origins of rice for authenticity important in terms of protecting businesses and consumers. In this study, we describe ICP-MS elemental profiling coupled with elementomic modelling to identify the geographical indications of Indian, Chinese, and Vietnamese rice. A PLS-DA model exhibited good discrimination (R² = 0.8393, Q² = 0.7673, accuracy = 1.0). Data-driven soft independent modelling of class analogy (dd-SIMCA) and K-nearest neighbours (K-NN) models have good sensitivity (98%) and specificity (100%).

Genetic Background Negates Improvements in Rice Flour Characteristics and Food Processing Properties Caused by a Mutant Allele of the PDIL1-1 Seed Storage Protein Gene

Phenotypic differences among breeding lines that introduce the same superior gene allele can be a barrier to effective development of cultivars with desirable traits in some crop species. For example, a deficient mutation of the Protein Disulfide Isomerase Like 1-1 (PDIL1-1) gene can cause accumulation of glutelin seed storage protein precursors in rice endosperm, and improves rice flour characteristics and food processing properties. However, the gene must be expressed to be useful. A deficient mutant allele of PDIL1-1 was introduced into two rice cultivars with different genetic backgrounds (Koshihikari and Oonari). The grain components, agronomic traits, and rice flour and food processing properties of the resulting lines were evaluated. The two breeding lines had similar seed storage protein accumulation, amylose content, and low-molecular-weight metabolites. However, only the Koshihikari breeding line had high flour quality and was highly suitable for rice bread, noodles, and sponge cake, evidence of the formation of high-molecular-weight protein complexes in the endosperm. Transcriptome analysis revealed that mRNA levels of fourteen PDI, Ero1, and BiP genes were increased in the Koshihikari breeding line, whereas this change was not observed in the Oonari breeding line. We elucidated part of the molecular basis of the phenotypic differences between two breeding lines possessing the same mutant allele in different genetic backgrounds. The results suggest that certain genetic backgrounds can negate the beneficial effect of the PDIL1-1 mutant allele. Better understanding of the molecular basis for such interactions may accelerate future breeding of novel rice cultivars to meet the strong demand for gluten-free foods.

Revisiting multi-stage models for upstream technology adoption: Evidence from rapid generation advance in rice breeding

Adoption of new plant varieties has played a significant role in eradicating global hunger. Previous research has mainly focused on farmer adoption and impact of new crop varieties, although upstream adoption of technologies in plant breeding can generate substantial multiplier effects on downstream impacts. This study moves upstream in the innovation system to generate policy advice on adoption and transfer of accelerated rice breeding technologies. More specifically, we assess the determinants of global adoption of rapid generation advance (RGA) through a sample of 158 rice breeders operating in various research institutes worldwide. Moving upstream in the innovation system has important theoretical and empirical implications due to the smaller number of decision-making units in the adoption process and the increasing role of institutional and managerial factors that may overrule individual adoption motivations. We revisit multi-stage models and devise the most robust estimation method that can be used in this situation. To generate insights on the impact of individual versus institutional adopter characteristics on upstream technology adoption, we juxtapose the response curves of the determinants of RGA adoption in rice breeding among alternative adoption stages, levels of conditionality and model specifications. Our findings confirm the importance of institutional and managerial factors and suggest that adoption and transfer of breeding technologies require breeding institutes to provide an enabling environment in which breeders are encouraged to take risks and are given sufficient freedom to experiment with and implement new technologies.

Effects of Thickness Fraction Process on Physicochemical Properties, Cooking Qualities, and Sensory Characteristics of Long-Grain Rice Samples

A process of removing thinner kernels of rough rice, i.e., thickness fraction process, has been suggested as a method for increasing milling yields in the rice industry. This study aimed at determining whether physicochemical properties, cooking qualities, and sensory characteristics of rice samples could be changed by the addition of a thickness fraction into the rice process stream. Each of four long-grain rice cultivar lots was assigned into two groups: unfractionated and thickness-fractionated. For the thickness-fractionated group, thin rice kernels (<1.9 mm) of rough rice were discarded from unfractionated rice samples. Unfractionated and thickness-fractionated rice samples were compared with respect to physicochemical properties, cooking qualities, and sensory characteristics. The results showed that the removal of such thin kernels decreased the breakage and chalkiness rates and increased head rice yields. Fractionated rice samples exhibited lower amylose contents and crude protein contents but higher gelatinization temperatures than unfractionated rice samples. While the optimum cooking duration and width–expansion ratios of thickness-fractionated rice samples were higher than those of unfractionated ones, there was a negligible impact of the thickness fraction process on sensory characteristics of long-grain rice samples. In conclusion, the thickness fraction process affects physicochemical properties and cooking qualities more than the sensory characteristics of rice samples.

RiceChain: secure and traceable rice supply chain framework using blockchain technology

The increasing number of rice product safety issues and the potential for contamination have established an enormous need for an effective strategy for the traceability of the rice supply chain. Tracing the origins of a rice product from raw materials to end customers is very complex and costly. Existing food supply chain methods (for example, rice) do not provide a scalable and cost-effective means of agricultural food supply. Besides, consumers lack the capability and resources required to check or report on the quality of agricultural goods in terms of defects or contamination. Consequently, customers are forced to decide whether to utilize or discard the goods. However, blockchain is an innovative framework capable of offering a transformative solution for the traceability of agricultural products and food supply chains. The aim of this paper is to propose a framework capable of tracking and monitoring all interactions and transactions between all stakeholders in the rice chain ecosystem through smart contracts. The model incorporates a system for customer satisfaction feedback, which enables all stakeholders to get up-to-date information on product quality, enabling them to make more informed supply chain decisions. Each transaction is documented and stored in the public ledger of the blockchain. The proposed framework provides a safe, efficient, reliable, and effective way to monitor and track rice products safety and quality especially during product purchasing. The security and performance analysis results shows that the proposed framework outperform the benchmark techniques in terms of cost-effectiveness, security and scalability with low computational overhead.

Integrated Nutrient Management Improves the Growth and Yield of Rice and Greengram in a Rice-Greengram Cropping System under the Coastal Plain Agro-Climatic Condition

Continuous mono-cropping of rice has resulted in decline or stagnation of yield output due to the occurrence of multiple nutrient deficiencies and worsening of soil physicochemical properties accompanying increased pressure of insect pests and diseases. The basic concept of integrated nutrient management (INM) is maintenance or adjustment of soil fertility and supply of plant nutrients to an optimum level for sustaining the desired crop productivity through optimisation of benefits from all possible sources of plant nutrients in an integrated way. Augmenting a rice-based cropping system with pulses is a prevalent and indigenous cropping system under rainfed conditions. Considering the above facts, experiments were conducted to evaluate the impacts of integrated nutrient management on productivity of aromatic rice-greengram cropping system and nutrient balance of the post-harvest soil for agricultural sustainability under rainfed conditions in two consecutive years (2017-2018 and 2018-2019) with six main plots and three subplots. The experimental findings revealed that the treatment comprised of 50% recommended dose of fertiliser (RDF) through chemicals + 50% recommended dose of nitrogen (RDN) through farmyard manure (FYM) increased the plant height, tillers, dry matter accumulation, leaf area and leaf area duration, and yield parameters in short grain aromatic rice. Similarly, preceding application of 50% RDF + 50% RDN through FYM to rice and further application 75% RDF + Rhizobium+ phosphate solubilizing bacteria (PSB) to greengram increased the growth characteristics and yield parameters-such as pods/plant, seeds/pod, grain yield, stover yield, and harvest index-in greengram. It was concluded that the treatment consisting of 50% RDF (chemical fertiliser) + 50% RDN (FYM) to rice and 75% RDF + Rhizobium + PSB to greengram increased the productivity of the rice-greengram cropping system. Furthermore, the adoption of INM has positively impacted post-harvest soil nutrient balance.

Rice quality and its impacts on food security and sustainability in Bangladesh

Rice market efficiency is important for food security in countries where rice is a staple. We assess the impact of rice quality on rice prices, food security, and environmental sustainability in Bangladesh. We find that while price varies as expected for most quality attributes, it is unaffected by a broken percentage below 24.9 percent. This reveals a potential inefficiency, considering the average 5 percent broken rate observed in the market. An increase in the broken rate of milled rice within the limits supported by our findings can, ceteris paribus, increase rice rations by 4.66 million a year, or conversely, yield the current number of rice rations using 170.79 thousand fewer hectares and cutting emissions by 1.48 million metric tons of CO2 equivalent. Thus, producing rice based on quality assessment can improve food security and its sustainability.

The Physicochemical Properties of Starch Are Affected by Wxlv in Indica Rice

Amylose largely determines rice grain quality profiles. The process of rice amylose biosynthesis is mainly driven by the waxy (Wx) gene, which also affects the diversity of amylose content. The present study assessed the grain quality profiles, starch fine structure, and crystallinity characteristics of the near-isogenic lines Q11(Wx^lv), NIL(Wx^a), and NIL(Wx^b) in the indica rice Q11 background containing different Wx alleles. Q11(Wx^lv) rice contained a relatively higher amylose level but very soft gel consistency and low starch viscosity, compared with rice lines carrying Wx^a and Wx^b. In addition, starch fine structure analysis revealed a remarkable decrease in the relative area ratio of the short amylopectin fraction but an increased amylose fraction in Q11(Wx^lv) rice. Chain length distribution analysis showed that Q11(Wx^lv) rice contained less amylopectin short chains but more intermediate chains, which decreased the crystallinity and lamellar peak intensity, compared with those of NIL(Wx^a) and NIL(Wx^b) rice. Additionally, the starches in developing grains showed different accumulation profiles among the three rice lines. Moreover, significant differences in starch gelatinization and retrogradation characteristics were observed between near-isogenic lines, which were caused by variation in starch fine structure. These findings revealed the effects of Wx^lv on rice grain quality and the fine structure of starch in indica rice.

US Consumers' Perceptions of Raw and Cooked Broken Rice

Rice supplies about 20% of the calories to the world’s consumers. Milling removes the outer husk and bran, breaking about 20% of the rice kernels during the milling process that equates to almost 100,000,000 tons of rice annually. Broken rice is discounted in price by almost half or relegated to non-human consumption. This study seeks to understand why this large percentage of rice production is discounted for human consumption. Consumers who routinely consume rice evaluated raw and cooked rice with 5%, 10%, 20%, 30% and 40% levels of brokens. Sensory analysis indicated the appearance of raw rice with high levels of brokens affected the price consumers were willing to pay. Panelists were not able to discern sensory differences amongst cooked rice samples with different brokens percentages despite an eight-fold difference in brokens (p < 0.01). From this, we concluded that the price discounts imposed on broken rice are not because of perceived differences in the eating quality of cooked rice. Overall impression and overall texture were the two most significant determinants in willingness to purchase rice. The five cooked-rice samples with different levels of broken rice inclusion did not differ in terms of willingness to purchase.

Systems-based rice improvement approaches for sustainable food and nutritional security

An integrated research approach to ensure sustainable rice yield increase of a crop grown by 25% of the world's farmers in 10% of cropland is essential for global food security. Rice, being a global staple crop, feeds about 56% of the world population and sustains 40% of the world's poor. At ~ $200 billion, it also accounts for 13% of the annual crop value. With hunger and malnutrition rampant among the poor, rice research for development is unique in global food and nutrition security. A systems-based, sustainable increase in rice quantity and quality is imperative for environmental and biodiversity benefits. Upstream 'discovery' through biotechnology, midstream 'development' through breeding and agronomy, downstream 'dissemination and deployment' must be 'demand-driven' for 'distinct socio-economic transformational impacts'. Local agro-ecology and livelihood nexus must drive the research agenda for targeted benefits. This necessitates sustained long-term investments by government, non-government and private sectors to secure the future food, nutrition, environment, prosperity and equity status.

Genetic and phenotypic characterization of rice grain quality traits to define research strategies for improving rice milling, appearance, and cooking qualities in Latin America and the Caribbean

Rice (Oryza sativa L.)grain quality is a set of complex interrelated traits that include grain milling, appearance, cooking, and edible properties. As consumer preferences in Latin America and the Caribbean evolve, determining what traits best capture regional grain quality preferences is fundamental for breeding and cultivar release. In this study, a genome-wide association study (GWAS), marker-assisted selection (MAS), and genomic selection (GS) were evaluated to help guide the development of new breeding strategies for rice grain quality improvement. For this purpose, 284 rice lines representing over 20 yr of breeding in Latin America and the Caribbean were genotyped and phenotyped for 10 different traits including grain milling, appearance, cooking, and edible quality traits. Genetic correlations among the 10 traits ranged from -0.83 to 0.85. A GWAS identified 19 significant marker/trait combinations associated with eight grain quality traits. Four functional markers, three located in the Waxy and one in the starch synthase IIa genes, were significantly associated with six grain-quality traits. These markers individually explained 51-75% of the phenotypic variance depending on the trait, clearly indicating their potential utility for MAS. Cross-validation studies to evaluate predictive abilities of four different GS models for each of the 10 quality traits were conducted and predictive abilities ranged from 0.3 to 0.72. Overall, the machine learning model random forest had the highest predictive abilities and was especially effective for traits where large effect quantitative trait loci were identified. This study provides the foundation for deploying effective molecular breeding strategies for grain quality in Latin American rice breeding programs.

Research advance in gas detection of volatile organic compounds released in rice quality deterioration process

Rice quality deterioration will cause grievous waste of stored grain and various food safety problems. Gas detection of volatile organic compounds (VOCs) produced by deterioration is a nondestructive detection method to judge rice quality and alleviate rice spoilage. This review discussed the research advance of VOCs detection in terms of nondestructive detection methods of rice quality deterioration, applications of VOCs in grain detection, inspection of characteristic gas produced during rice spoilage, rice deterioration prevention and control, and detection of VOCs released by rice mildew and insect attack. According to the main causes of rice quality deterioration and major sources of VOCs with off-odor generated during rice storage, deterioration can be divided into mold and insect infection. The results of literature manifested that researches mainly focused on the infection of Aspergillus in the mildew process and the attack of certain pests in recent years, thus the research scope was limited. In this paper, the gas detection methods combined with the chemometrics to qualitatively analyze the VOCs, as well as the correlation with the number of colonies and insects were further studied based on the common dominant strains during rice mildew, that is, Aspergillus and Penicillium fungi, and the common pests during storage, that is, Sitophilus oryzae and Rhyzopertha dominica. Furthermore, this paper pointed out that the quantitative determination of characteristic VOCs, the numeration relationship between VOCs and the degree of mildew and insect infestation, the further expansion of detection range, and the application of degraded rice should be the spotlight of future research.

Challenges and opportunities in productivity and sustainability of rice cultivation system: a critical review in Indian perspective

Abstract

Rice-wheat cropping system, intensively followed in Indo-Gangetic plains (IGP), played a prominent role in fulfilling the food grains demand of the increasing population of South Asia. In northern Indian plains, some practices such as intensive rice cultivation with traditional method for long-term have been associated with severe deterioration of natural resources, declining factor productivity, multiple nutrients deficiencies, depleting groundwater, labour scarcity and higher cost of cultivation, putting the agricultural sustainability in question. Varietal development, soil and water management, and adoption of resource conservation technologies in rice cultivation are the key interventions areas to address these challenges. The cultivation of lesser water requiring crops, replacing rice in light-textured soil and rainfed condition, should be encouraged through policy interventions. Direct seeding of short duration, high-yielding and stress tolerant rice varieties with water conservation technologies can be a successful approach to improve the input use efficiency in rice cultivation under medium-heavy-textured soils. Moreover, integrated approach of suitable cultivars for conservation agriculture, mechanized transplanting on zero-tilled/unpuddled field and need-based application of water, fertilizer and chemicals might be a successful approach for sustainable rice production system in the current scenario. In this review study, various challenges in productivity and sustainability of rice cultivation system and possible alternatives and solutions to overcome such challenges are discussed in details.

Graphic abstract

Computer Vision and Machine Learning Analysis of Commercial Rice Grains: A Potential Digital Approach for Consumer Perception Studies

Rice quality assessment is essential for meeting high-quality standards and consumer demands. However, challenges remain in developing cost-effective and rapid techniques to assess commercial rice grain quality traits. This paper presents the application of computer vision (CV) and machine learning (ML) to classify commercial rice samples based on dimensionless morphometric parameters and color parameters extracted using CV algorithms from digital images obtained from a smartphone camera. The artificial neural network (ANN) model was developed using nine morpho-colorimetric parameters to classify rice samples into 15 commercial rice types. Furthermore, the ANN models were deployed and evaluated on a different imaging system to simulate their practical applications under different conditions. Results showed that the best classification accuracy was obtained using the Bayesian Regularization (BR) algorithm of the ANN with ten hidden neurons at 91.6% (MSE = <0.01) and 88.5% (MSE = 0.01) for the training and testing stages, respectively, with an overall accuracy of 90.7% (Model 2). Deployment also showed high accuracy (93.9%) in the classification of the rice samples. The adoption by the industry of rapid, reliable, and accurate methods, such as those presented here, may allow the incorporation of different morpho-colorimetric traits in rice with consumer perception studies.

Tailoring rice varieties to consumer preferences induced by cultural and colonial heritage: Lessons from New Rice for Africa (NERICA) in The Gambia

Rice breeding priorities in Africa often focus on agronomic gains. However, being a net importer of rice, the continent's varietal replacement success also crucially hinges on new varieties' market competitiveness vis-à-vis imports. Markets have been profoundly shaped by cultural and colonial heritage. Indigenous preferences for African rice can be traced back to ancient rice domestication and have been subsequently influenced by Asian rice import standards as a result of colonial import substitution policies. New Rice for Africa (NERICA) crosses between African and Asian rice species have the potential to reconcile these dual indigenous/import preferences, but little is known about their market competitiveness. We use auction market data to assess the intrinsic and extrinsic consumer value of NERICA in The Gambia relative to two market standards: branded, Asian rice imports and the most popular locally grown Asian rice variety. We categorize rice consumers into four market segments, based on their heritage as evidenced by their preferences and genealogical lineages. NERICA outperforms both Asian rice standards in terms of market competitiveness, and its value is further reinforced by colonial heritage and labeling, but somewhat weakened by cultural heritage. Consumers were found to pay price premiums for NERICA in the range of 5% to 22% relative to Asian rice imports, with the highest premiums offered by consumers with colonial heritage, representing 86% of the sample. Maintaining and expanding this market will require breeders to incorporate trait mixes that reconcile agronomic gains and consumer preferences induced by cultural and colonial heritage.

Effects of cultivars and fertilization levels on the quality of rice milling: A diagnosis using near-infrared spectroscopy, X-ray diffraction, and scanning electron microscopy

Cultivars and fertilization levels influence rice productivity and can be associated with grain quality. Thus, it is possible to make decisions regarding the choice of cultivars and application of fertilizer levels based on the type of milling, a necessary post-harvest process that may minimize the nutrient load in the grains and result in loss in quality. This study relates the physicochemical composition and morphological quality of brown and polished milled rice grains, cultivar types, and different levels of soil fertilization using near-infrared spectroscopy analysis, X-ray diffraction and scanning electron microscopy. Statistical tools were used to test the various treatments and identify the relationship between factors and variables. A high fertilization level is related to increasing crude protein composition and starch for cultivar IRGA 431 CL associated with polished rice. However, the combination of cultivar IRGA 424 RI and brown rice demonstrated a higher grain resistance, and different percentages of whole, chalky, and damaged rice. The correlation between ash × crude protein and starch × crude fiber was found to be positive for brown rice and negative for the polished rice. Further, an increase in starch content was inversely proportional to the ash content, whereas an increase in crude protein was inversely proportional to the low-fat content in milled rice. The crystalline characteristics of rice starch were preserved at high fertilization levels associated with polished grains that demonstrated high starch content. Polished grains, however, showed more pores and cavities, and consequently greater permeabilities in the surface. It is recommended that batches of grains produced from cultivar IRGA 431 CL with high levels of fertilization be subjected to polished rice milling to achieve high protein and starch quality. However, grains from cultivar IRGA 424 RI with high levels of fertilization are recommended for brown rice milling owing to the high percentage of physical defects observed.

Functional Analysis of the Differences in the Dimensions of Two Types of Boiled and Steamed Rice Grains

The study tested how the cooking process can change the dimensions of rice grains. The impact of set times of cooking or steaming process on the characteristics such as length, width, and height of two varieties of rice, namely, long-grain white and parboiled, was investigated. The measurements of the dimension characteristics obtained at different times of the cooking process were converted to functional data. Different methods of multivariate functional data analysis, namely, functional multivariate analysis of variance, functional discriminant coordinates, and cluster analysis, were applied to discover the differences between the two varieties and the two heat treatment methods.

Dissecting the meteorological and genetic factors affecting rice grain quality in Northeast China

Background

The Northeast Plain of China, which is an important region for the production of high grain quality rice in China. However, the grain quality of the rice produced varies across this region, even for the same cultivar.

Objective

In order to explore the meteorological factors that have the greatest influence on quality and the transcriptional level differences between different cultivars and different locations at grain filling stage.

Methods

We grew eight rice cultivars in three locations in Northeast China during two growing seasons (2017 and 2018). We recorded meteorological conditions, including air temperature, air temperature range, and photosynthetically active radiation (PAR) during the grain-filling stage of each cultivar, and analyzed the grain quality of those eight cultivars.

Results

Across all eight cultivars, meteorological factors had a stronger effect on eating quality than genotype, while genotype had a stronger effect on milling quality. Of the three environmental factors assessed, PAR was significantly correlated with the most grain quality traits. Using RNA-sequencing analysis, we identified 573 environment-specific DEGs (Differentially Expressed Genes), and 119 genotype-specific DEGs; 11 DEGs were responsive to genotype × environment interactions. These DEGs were involved in many key metabolic processes.

Conclusion

Our results indicated that interactions among environmental factors, especially PAR, affected rice quality in Northeast China. Further analyses of the DEGs identified herein may provide useful information for future breeding programs aiming to develop high grain quality rice varieties suitable for cultivation across Northeast China.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13258-021-01121-z.

Raman Molecular Fingerprints of Rice Nutritional Quality and the Concept of Raman Barcode

The nutritional quality of rice is contingent on a wide spectrum of biochemical characteristics, which essentially depend on rice genome, but are also greatly affected by growing/environmental conditions and aging during storage. The genetic basis and related identification of genes have widely been studied and rationally linked to accumulation of micronutrients in grains. However, genetic classifications cannot catch quality fluctuations arising from interannual, environmental, and storage conditions. Here, we propose a quantitative spectroscopic approach to analyze rice nutritional quality based on Raman spectroscopy, and disclose analytical algorithms for the determination of: (i) amylopectin and amylose concentrations, (ii) aromatic amino acids, (iii) protein content and structure, and (iv) chemical residues. The proposed Raman algorithms directly link to the molecular composition of grains and allow fast/non-destructive determination of key nutritional parameters with minimal sample preparation. Building upon spectroscopic information at the molecular level, we newly propose to represent the nutritional quality of labeled rice products with a barcode specially tailored on the Raman spectrum. The Raman barcode, which can be stored in databases promptly consultable with barcode scanners, could be linked to diet applications (apps) to enable a rapid, factual, and unequivocal product identification based on direct molecular screening.

Developing new lines of Japonica rice for higher quality and yield under arid conditions

Rice is the world's largest food crop, and its production needs to be doubled by 2050 to cope with population growth and associated demand. In addition to the value of improving yields, quality is also important for breeders and consumers, but it pays less attention in arid regions. During two successive summer growing seasons, the experimental material focused on 34 genotypes developed from different crosses on Fn generation after fixation as well as six of the most recent commercial cultivars used for comparisons. The results showed that a high yield of grain followed by high milling and grain quality characteristics were observed among the 34 genotypes used in this analysis. Highly important and positive correlations between the percentage of hulling and the percentage of milling (0.424) and the yield ability could be accomplished by choosing the number of panicles per plant and the weight of the panicles. Selection criteria for good quality should be met by the percentage of head rice and many mineral elements, particularly zinc and iron. As a consequence, the genotypes M.J 5460S/SK105-1, M.J 5460S/GZ7768-1, M.J 5460S/G177-1, M.J 5460S/SK105-3 and M.J 5460S/SK106-4 had desirable high yield and quality characteristics and could be used as promising accessions to the rice breeding program in arid regions. In addition to commercial genotypes, improved Japonica rice genotypes could be produced in arid conditions for higher yield and quality, leading to an increase in total production, supporting food security and nutrition.

A rare Waxy allele coordinately improves rice eating and cooking quality and grain transparency

In rice (Oryza sativa), amylose content (AC) is the major factor that determines eating and cooking quality (ECQ). The diversity in AC is largely attributed to natural allelic variation at the Waxy (Wx) locus. Here we identified a rare Wx allele, Wx^mw , which combines a favorable AC, improved ECQ and grain transparency. Based on a phylogenetic analysis of Wx genomic sequences from 370 rice accessions, we speculated that Wx^mw may have derived from recombination between two important natural Wx alleles, Wxⁱⁿ and Wx^b . We validated the effects of Wx^mw on rice grain quality using both transgenic lines and near-isogenic lines (NILs). When introgressed into the japonica Nipponbare (NIP) background, Wx^mw resulted in a moderate AC that was intermediate between that of NILs carrying the Wx^b allele and NILs with the Wx^mp allele. Notably, mature grains of NILs fixed for Wx^mw had an improved transparent endosperm relative to soft rice. Further, we introduced Wx^mw into a high-yielding japonica cultivar via molecular marker-assisted selection: the introgressed lines exhibited clear improvements in ECQ and endosperm transparency. Our results suggest that Wx^mw is a promising allele to improve grain quality, especially ECQ and grain transparency of high-yielding japonica cultivars, in rice breeding programs.

Green Labelled Rice Shows a Higher Nutritional and Physiochemical Quality Than Conventional Rice in China

In China, green food refers to a wide array of certified agricultural and processed edible commodities that are produced strictly following defined standard protocols and labelled with a specified “Green Food” logo. The demand for green labelled rice is rapidly growing due to its higher quality and adherence to safety standards compared to conventional rice. Therefore, the physicochemical and nutritional quality of green rice needs to be further investigated for consumers’ benefits. Using Daohuaxiang 2, one of the most famous types of green rice, we found that green rice was significantly superior to conventional rice in terms of thousand kernel weight, chalkiness, amylose content, and rheological properties. Green rice contained lower levels of heavy metals than conventional rice due to a dramatic reduction in chemical inputs during its cultivation. The concentrations of Cr, As, Cd, Pb in green rice decreased, respectively, from 98.7 to 180.1 μg/kg, 49.8 to 62.3 μg/kg, 7.8 to 9.1 μg/kg, and 29.0 to 42.8 μg/kg on average. Gas chromatography coupled with mass spectrometry (GC–MS)-based metabolomics, in combination with multivariate analysis, revealed that 15 metabolites differentially accumulated when comparing green and conventional rice. Among these, 12 metabolites showed a high accumulation in green rice, including seven amino acids, two sugars, and three fatty acids. Overall, our results suggest the superior quality of a type of green rice that is popular in China, which may boost green rice consumption and facilitate the further expansion of green rice production in China.

Unraveling heterogeneity of consumers' food choice: Implications for nutrition interventions in eastern India

Understanding heterogeneity of consumers' food choice is critical in formulating tailored nutrition interventions. To illustrate this, we survey urban and rural consumers from low- and middle-income households in eastern India to unravel five sources of heterogeneity (5 Ws) in gastronomic systems that affect diets: (i) socioeconomic characteristics of the target population (who); (ii) food environments (where); (iii) eating occasions (when); (iv) consumed dishes (what); and (v) ingredient attributes and consumer attitudes towards food (why). Diets in eastern India are predominantly starch-based featuring infrequent intake of fruits and vegetables. Accounting for heterogeneity in gastronomic systems can help policy makers and nutritionists develop more targeted nutrition interventions, which can aid in the development of planetary health diets in various contexts around the world.

Deploying viscosity and starch polymer properties to predict cooking and eating quality models: A novel breeding tool to predict texture

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Multivariate analysis was used to develop twelve cooking and eating quality classes.

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Two-layered random forest model was used to predict rice classification.

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High classification accuracy of cooking and eating quality ideotypes were obtained.

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Mismatches from IRRI-released and consumer-preferred lines was capture by the model.

Acceptance of new rice genotypes demanded by rice value chain depends on premium value of varieties that match consumer demands of regional preferences. High throughput prediction tools are not available to breeders to classify cooking and eating quality (CEQ) ideotypes and to capture texture of varieties. The pasting properties in combination with starch properties were used to develop two layered models in order to classify the rice varieties into twelve distinct CEQ ideotypes with unique sensory profiles. Classification models developed using random forest method depicted the overall accuracy of 96 %. These CEQ models were found to be robust to predict ideotypes in both Indica and Japonica diversity panels grown under dry and wet seasons and across the years. We conducted random forest modeling using 1.8 million high density SNPs and identified top 1000 SNP features which explained CEQ model classification with the accuracy of 0.81. Furthermore these CEQ models were found to be valuable to predict textural preferences of IRRI breeding lines released during 1960–2013 and mega varieties preferred in South and South East Asia.

Correlation of taste values with chemical compositions and Rapid Visco Analyser profiles of 36 indica rice (Oryza sativa L.) varieties

Yield, taste quality, and cultivar utilisation improvements are important research topics in indica rice breeding. Herein, we compared the relative effectiveness and relationship of three taste evaluation methods, namely, chemical composition, Rapid Visco Analyser (RVA), and taste analyser. We assessed associations among these methods using 36 indica varieties commonly grown in Yunnan, Sichuan, and Guizhou, China. Temperature and sunlight duration during grain filling influenced rice cooking quality. Varieties with high taste quality had low amylose and protein contents; high peak viscosities and breakdowns; and low hold viscosities, setbacks, and final viscosities. Protein and combined protein and amylose explained 38.6% and 62.1% of the variation in taste value, respectively. The RVA profile was affected by protein, amylose, and amylopectin contents and explained 60.5% of the taste-value variation. This study lays the foundation for taste evaluation of high-quality rice varieties early in the breeding process, which can improve cultivation and marketing potential.

Understanding Filipino Rice Farmer Preference Heterogeneity for Varietal Trait Improvements: A Latent Class Analysis

Using an experimental methodology based on investment games, we examine whether smallholder rice farmers from Nueva Ecija, Philippines have heterogeneous preferences for improvements in 10 rice varietal traits. We use a latent class cluster approach to identify different segments of rice producing households and their distinct preferences for trait improvements. These clusters were characterised post hoc using household, farm, and marketing characteristics. On average, farmers invested the most in rice varietal trait improvements that offered opportunities to reduce losses caused by lodging, insects and diseases. We found four classes of farmers with distinct preferences for improvements in variety traits. The clusters were significantly different in terms of household and farm characteristics. These findings can guide breeding research in the development of varieties that have the traits farmers identified for improvement, and that will address the unique needs of distinct farmer segments.

Preserving cultural heritage through the valorization of Cordillera heirloom rice in the Philippines

For centuries, heirloom rice varieties have been grown on the terraces of the Cordillera Mountains of Luzon, Philippines, terroirs known for their significant historical, cultural, and aesthetic values. However, heritage heirloom rice farming is gradually being abandoned, mainly because of its lower productivity and the struggle of the sector to create a sustainable niche market for heirloom rice by branding its cultural, social, and nutritional values. We propose several demand-side intervention strategies for the valorization of heirloom rice. To support the development of a segmented marketing strategy for heritage farming, we provide evidence on urban consumers' willingness to purchase heirloom rice. We interviewed 500 urban consumers from Metro Manila in July-August 2015, who placed a purchasing bid on a kilogram of heirloom rice. Consumers' bids averaged PHP 72.61 kg^-1 (USD 1.60 kg^-1), which is less than half its current market price. This explains why heirloom rice struggles to gain market share in urban markets in the Philippines. Given this bid price, we estimate a potential market size of PHP 20.3 billion (USD 443 million) that could be created for heirloom rice and tapped into by heritage farmers. Findings further indicate that women, business owners, and consumers who buy packaged rice and eat pigmented rice are willing to pay more for heirloom rice. Finally, our evidence suggests that proper information framing will be necessary to create demand and support the valorization of heirloom rice to preserve cultural heritage and in situ biodiversity of rice landraces in the Philippines.