Research article

Profile of the grain physical traits and physicochemical properties of selected Malaysian rice landraces for future use in a breeding program

  • Malaysia is currently experiencing the same scenario as other countries, as the majority of consumers have shifted their preferences from locally produced rice to imported rice. This has resulted in a significant influx of imported rice into the domestic markets. Food security in the long term cannot be achieved by depending on imported food. Therefore, countries must make an effort to develop high-quality rice to meet the demand of customers. The study aimed to evaluate the grain physical traits and physicochemical properties of 30 Malaysian rice landraces to optimize the use of rice landraces in breeding programs. The grain physical traits were evaluated according to grain size, grain shape, and kernel elongation. Meanwhile, the physicochemical properties were determined by amylose content, alkali spreading value, and gel consistency. The grain length ranged from 4.14 to 8.16 mm and the grain width varied between 1.76 and 2.81 mm. The grain shapes were categorized into three types: medium, long and slender, and bold. Most of the rice landraces exhibited a low amylose content ranging from 16.07 to 19.83, while intermediate amylose content ranged from 20.00 to 23.80. The alkali spreading value showed that most of the rice landraces require an intermediate cooking time. The gel consistency exhibited a wide range, varying from soft to hard. The gel consistency exhibited the highest phenotypic and genotypic coefficient of variance, with values of 42.44% and 41.88%, respectively. Most of the studied traits except for kernel elongation were identified as having high heritability and high genetic advance as a percentage of the mean. A dendrogram effectively revealed the genetic relationships among Malaysian rice landraces by generating three distinct clusters. Cluster Ⅰ was primarily composed of glutinous rice landraces with a low to very low amylose content and exhibited the highest mean values for gel consistency and kernel elongation. Cluster Ⅱ consisted of 13 rice landraces that had the highest mean value for milled grain length and grain shape. Cluster Ⅲ was composed of rice landraces and control rice cultivars, and they exhibited the highest mean values for alkali spreading value, amylose content, and milled grain width. Bokilong, Kolomintuhon, Silou, Tutumoh, and Bidor in Cluster Ⅲ exhibited comparable physicochemical properties and cooking quality traits as the control rice cultivars. The findings of this study are important for identifying potential donors for breeding programs focused on developing high-quality or specialty rice cultivars.

    Citation: Site Noorzuraini Abd Rahman, Rosimah Nulit, Faridah Qamaruz Zaman, Khairun Hisam Nasir, Mohd Hafiz Ibrahim, Mohd Ramdzan Othman, Nur Idayu Abd Rahim, Nor Sufiah Sebaweh. Profile of the grain physical traits and physicochemical properties of selected Malaysian rice landraces for future use in a breeding program[J]. AIMS Agriculture and Food, 2024, 9(4): 934-958. doi: 10.3934/agrfood.2024051

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  • Malaysia is currently experiencing the same scenario as other countries, as the majority of consumers have shifted their preferences from locally produced rice to imported rice. This has resulted in a significant influx of imported rice into the domestic markets. Food security in the long term cannot be achieved by depending on imported food. Therefore, countries must make an effort to develop high-quality rice to meet the demand of customers. The study aimed to evaluate the grain physical traits and physicochemical properties of 30 Malaysian rice landraces to optimize the use of rice landraces in breeding programs. The grain physical traits were evaluated according to grain size, grain shape, and kernel elongation. Meanwhile, the physicochemical properties were determined by amylose content, alkali spreading value, and gel consistency. The grain length ranged from 4.14 to 8.16 mm and the grain width varied between 1.76 and 2.81 mm. The grain shapes were categorized into three types: medium, long and slender, and bold. Most of the rice landraces exhibited a low amylose content ranging from 16.07 to 19.83, while intermediate amylose content ranged from 20.00 to 23.80. The alkali spreading value showed that most of the rice landraces require an intermediate cooking time. The gel consistency exhibited a wide range, varying from soft to hard. The gel consistency exhibited the highest phenotypic and genotypic coefficient of variance, with values of 42.44% and 41.88%, respectively. Most of the studied traits except for kernel elongation were identified as having high heritability and high genetic advance as a percentage of the mean. A dendrogram effectively revealed the genetic relationships among Malaysian rice landraces by generating three distinct clusters. Cluster Ⅰ was primarily composed of glutinous rice landraces with a low to very low amylose content and exhibited the highest mean values for gel consistency and kernel elongation. Cluster Ⅱ consisted of 13 rice landraces that had the highest mean value for milled grain length and grain shape. Cluster Ⅲ was composed of rice landraces and control rice cultivars, and they exhibited the highest mean values for alkali spreading value, amylose content, and milled grain width. Bokilong, Kolomintuhon, Silou, Tutumoh, and Bidor in Cluster Ⅲ exhibited comparable physicochemical properties and cooking quality traits as the control rice cultivars. The findings of this study are important for identifying potential donors for breeding programs focused on developing high-quality or specialty rice cultivars.



    Let Fq be the finite field of q elements with characteristic p, where q=pr, p is a prime number. Let Fq=Fq{0} and Z+ denote the set of positive integers. Let sZ+ and bFq. Let f(x1,,xs) be a diagonal polynomial over Fq of the following form

    f(x1,,xs)=a1xm11+a2xm22++asxmss,

    where aiFq, miZ+, i=1,,s. Denote by Nq(f=b) the number of Fq-rational points on the affine hypersurface f=b, namely,

    Nq(f=b)=#{(x1,,xs)As(Fq)f(x1,,xs)=b}.

    In 1949, Hua and Vandiver [1] and Weil [2] independently obtained the formula of Nq(f=b) in terms of character sum as follows

    Nq(f=b)=qs1+ψ1(a11)ψs(ass)J0q(ψ1,,ψs), (1.1)

    where the sum is taken over all s multiplicative characters of Fq that satisfy ψmii=ε, ψiε, i=1,,s and ψ1ψs=ε. Here ε is the trivial multiplicative character of Fq, and J0q(ψ1,,ψs) is the Jacobi sum over Fq defined by

    J0q(ψ1,,ψs)=c1++cs=0,ciFqψ1(c1)ψs(cs).

    Though the explicit formula for Nq(f=b) are difficult to obtain in general, it has been studied extensively because of their theoretical importance as well as their applications in cryptology and coding theory; see[3,4,5,6,7,8,9]. In this paper, we use the Jacobi sums, Gauss sums and the results of quadratic form to deduce the formula of the number of Fq2-rational points on a class of hypersurfaces over Fq2 under certain conditions. The main result of this paper can be stated as

    Theorem 1.1. Let q=2r with rZ+ and Fq2 be the finite field of q2 elements. Let f(X)=a1xm11+a2xm22++asxmss, g(Y)=y1y2+y3y4++yn1yn+y2n2t1+ +y2n3+y2n1+bty2n2t++b1y2n2+b0y2n, and l(X,Y)=f(X)+g(Y), where ai,bjFq2, mi1, (mi,mk)=1, ik, mi|(q+1), miZ+, 2|n, n>2, 0tn22, TrFq2/F2(bj)=1 for i,k=1,,s and j=0,1,,t. For hFq2, we have

    (1) If h=0, then

    Nq2(l(X,Y)=0)=q2(s+n1)+γFq2(si=1((γai)mimi1)(qs+2n3+(1)tqs+n3)).

    (2) If hFq2, then

    Nq2(l(X,Y)=h)=q2(s+n1)+(qs+2n3+(1)t+1(q21)qs+n3)si=1((hai)mimi1)+γFq2{h}[si=1((γai)mimi1)(q2n+s3+(1)tqn+s3)].

    Here,

    (γai)mi={1,ifγaiisaresidueofordermi,0,otherwise.

    To prove Theorem 1.1, we need the lemmas and theorems below which are related to the Jacobi sums and Gauss sums.

    Definition 2.1. Let χ be an additive character and ψ a multiplicative character of Fq. The Gauss sum Gq(ψ,χ) in Fq is defined by

    Gq(ψ,χ)=xFqψ(x)χ(x).

    In particular, if χ is the canonical additive character, i.e., χ(x)=e2πiTrFq/Fp(x)/p where TrFq/Fp(y)=y+yp++ypr1 is the absolute trace of y from Fq to Fp, we simply write Gq(ψ):=Gq(ψ,χ).

    Let ψ be a multiplicative character of Fq which is defined for all nonzero elements of Fq. We extend the definition of ψ by setting ψ(0)=0 if ψε and ε(0)=1.

    Definition 2.2. Let ψ1,,ψs be s multiplicative characters of Fq. Then, Jq(ψ1,,ψs) is the Jacobi sum over Fq defined by

    Jq(ψ1,,ψs)=c1++cs=1,ciFqψ1(c1)ψs(cs).

    The Jacobi sums Jq(ψ1,,ψs) as well as the sums J0q(ψ1,,ψs) can be evaluated easily in case some of the multiplicative characters ψi are trivial.

    Lemma 2.3. ([10,Theorem 5.19,p. 206]) If the multiplicative characters ψ1,,ψs of Fq are trivial, then

    Jq(ψ1,,ψs)=J0q(ψ1,,ψs)=qs1.

    If some, but not all, of the ψi are trivial, then

    Jq(ψ1,,ψs)=J0q(ψ1,,ψs)=0.

    Lemma 2.4. ([10,Theorem 5.20,p. 206]) If ψ1,,ψs are multiplicative characters of Fq with ψs nontrivial, then

    J0q(ψ1,,ψs)=0

    if ψ1ψs is nontrivial and

    J0q(ψ1,,ψs)=ψs(1)(q1)Jq(ψ1,,ψs1)

    if ψ1ψs is trivial.

    If all ψi are nontrivial, there exists an important connection between Jacobi sums and Gauss sums.

    Lemma 2.5. ([10,Theorem 5.21,p. 207]) If ψ1,,ψs are nontrivial multiplicative characters of Fq and χ is a nontrivial additive character of Fq, then

    Jq(ψ1,,ψs)=Gq(ψ1,χ)Gq(ψs,χ)Gq(ψ1ψs,χ)

    if ψ1ψs is nontrivial and

    Jq(ψ1,,ψs)=ψs(1)Jq(ψ1,,ψs1)=1qGq(ψ1,χ)Gq(ψs,χ)

    if ψ1ψs is trivial.

    We turn to another special formula for Gauss sums which applies to a wider range of multiplicative characters but needs a restriction on the underlying field.

    Lemma 2.6. ([10,Theorem 5.16,p. 202]) Let q be a prime power, let ψ be a nontrivial multiplicative character of Fq2 of order m dividing q+1. Then

    Gq2(ψ)={q,ifmoddorq+1meven,q,ifmevenandq+1modd.

    For hFq2, define v(h)=1 if hFq2 and v(0)=q21. The property of the function v(h) will be used in the later proofs.

    Lemma 2.7. ([10,Lemma 6.23,p. 281]) For any finite field Fq, we have

    cFqv(c)=0,

    for any bFq,

    c1++cm=bv(c1)v(ck)={0,1k<m,v(b)qm1,k=m,

    where the sum is over all c1,,cmFq with c1++cm=b.

    The quadratic forms have been studied intensively. A quadratic form f in n indeterminates is called nondegenerate if f is not equivalent to a quadratic form in fewer than n indeterminates. For any finite field Fq, two quadratic forms f and g over Fq are called equivalent if f can be transformed into g by means of a nonsingular linear substitution of indeterminates.

    Lemma 2.8. ([10,Theorem 6.30,p. 287]) Let fFq[x1,,xn], q even, be a nondegenerate quadratic form. If n is even, then f is either equivalent to

    x1x2+x3x4++xn1xn

    or to a quadratic form of the type

    x1x2+x3x4++xn1xn+x2n1+ax2n,

    where aFq satisfies TrFq/Fp(a)=1.

    Lemma 2.9. ([10,Corollary 3.79,p. 127]) Let aFq and let p be the characteristic of Fq, the trinomial xpxa is irreducible in Fq if and only if TrFq/Fp(a)0.

    Lemma 2.10. ([10,Lemma 6.31,p. 288]) For even q, let aFq with TrFq/Fp(a)=1 and bFq. Then

    Nq(x21+x1x2+ax22=b)=qv(b).

    Lemma 2.11. ([10,Theorem 6.32,p. 288]) Let Fq be a finite field with q even and let bFq. Then for even n, the number of solutions of the equation

    x1x2+x3x4++xn1xn=b

    in Fnq is qn1+v(b)q(n2)/2. For even n and aFq with TrFq/Fp(a)=1, the number of solutions of the equation

    x1x2+x3x4++xn1xn+x2n1+ax2n=b

    in Fnq is qn1v(b)q(n2)/2.

    Lemma 2.12. Let q=2r and hFq2. Let g(Y)Fq2[y1,y2,,yn] be a polynomial of the form

    g(Y)=y1y2+y3y4++yn1yn+y2n2t1++y2n3+y2n1+bty2n2t++b1y2n2+b0y2n,

    where bjFq2, 2|n, n>2, 0tn22, TrFq2/F2(bj)=1, j=0,1,,t. Then

    Nq2(g(Y)=h)=q2(n1)+(1)t+1qn2v(h). (2.1)

    Proof. We provide two proofs here. The first proof is as follows. Let q1=q2. Then by Lemmas 2.7 and 2.10, the number of solutions of g(Y)=h in Fq2 can be deduced as

    Nq2(g(Y)=h)=c1+c2++ct+2=hNq2(y1y2+y3y4++yn2t3yn2t2=c1)Nq2(yn2t1yn2t+y2n2t1+bty2n2t=c2)Nq2(yn1yn+y2n1+b0y2n=ct+2)=c1+c2++ct+2=h(qn2t31+v(c1)q(n2t4)/21)(q1v(c2))(q1v(ct+2))=c1+c2++ct+2=h(qn2t21+v(c1)q(n2t2)/21v(c2)qn2t31v(c1)v(c2)q(n2t4)/21)(q1v(c3))(q1v(ct+2))=c1+c2++ct+2=h(qnt21+v(c1)q(n2)/21v(c2)qnt31++(1)t+1v(c1)v(c2)v(ct+2)q(n2t4)/21)=qn11+q(n2)/21c1Fq2v(c1)++(1)t+1c1+c2++ct+2=hv(c1)v(c2)v(ct+2)q(n2t4)/21. (2.2)

    By Lamma 2.7 and (2.2), we have

    Nq2(g(Y)=h)=qn11+(1)t+1v(h)q(n2)/21=q2(n1)+(1)t+1v(h)qn2.

    Next we give the second proof. Note that if f and g are equivalent, then for any bFq2 the equation f(x1,,xn)=b and g(x1,,xn)=b have the same number of solutions in Fq2. So we can get the number of solutions of g(Y)=h for hFq2 by means of a nonsingular linear substitution of indeterminates.

    Let k(X)Fq2[x1,x2,x3,x4] and k(X)=x1x2+x21+Ax22+x3x4+x23+Bx24, where TrFq2/F2(A)=TrFq2/F2(B)=1. We first show that k(x) is equivalent to x1x2+x3x4.

    Let x3=y1+y3 and xi=yi for i3, then k(X) is equivalent to y1y2+y1y4+y3y4+Ay22+y23+By24.

    Let y2=z2+z4 and yi=zi for i2, then k(X) is equivalent to z1z2+z3z4+Az22+z23+Az24+Bz24.

    Let z1=α1+Aα2 and zi=αi for i1, then k(X) is equivalent to α1α2+α23+α3α4+(A+B)α24.

    Since TrFq2/F2(A+B)=0, we have α23+α3α4+(A+B)α24 is reducible by Lemma 2.9. Then k(X) is equivalent to x1x2+x3x4. It follows that if t is odd, then g(Y) is equivalent to x1x2+x3x4++xn1xn, and if t is even, then g(Y) is equivalent to x1x2+x3x4++xn1xn+x2n1+ax2n with TrFq2/F2(a)=1. By Lemma 2.11, we get the desired result.

    From (1.1), we know that the formula for the number of solutions of f(X)=0 over Fq2 is

    Nq2(f(X)=0)=q2(s1)+d11j1=1ds1js=1¯ψj11(a1)¯ψjss(as)J0q2(ψj11,,ψjss),

    where di=(mi,q21) and ψi is a multiplicative character of Fq2 of order di. Since mi|q+1, we have di=mi. Let H={(j1,,js)1ji<mi, 1is}. It follows that ψj11ψjss is nontrivial for any (j1,,js)H as (mi,mj)=1. By Lemma 2, we have J0q2(ψj11,,ψjss)=0 and hence Nq2(f(X)=0)=q2(s1).

    Let Nq2(f(X)=c) denote the number of solutions of the equation f(X)=c over Fq2 with cFq2. Let V={(j1,,js)|0ji<mi,1is}. Then

    Nq2(f(X)=c)=γ1++γs=cNq2(a1xm11=γ1)Nq2(asxmss=γs)=γ1++γs=cm11j1=0ψj11(γ1a1)ms1js=0ψjss(γsas).

    Since ψi is a multiplicative character of Fq2 of order mi, we have

    Nq2(f(X)=c)=γ1c++γsc=1(j1,,js)Vψj11(γ1c)ψj11(ca1)ψjss(γsc)ψjss(cas)=(j1,,js)Vψj11(ca1)ψjss(cas)γ1c++γsc=1ψj11(γ1c)ψjss(γsc)=(j1,,js)Vψj11(ca1)ψjss(cas)Jq2(ψj11,,ψjss).

    By Lemma 2.3,

    Nq2(f(X)=c)=q2(s1)+(j1,,js)Hψj11(ca1)ψjss(cas)Jq2(ψj11,,ψjss).

    By Lemma 2.5,

    Jq2(ψj11,,ψjss)=Gq2(ψj11)Gq2(ψjss)Gq2(ψj11ψjss).

    Since mi|q+1 and 2mi, by Lemma 2.6, we have

    Gq2(ψj11)==Gq2(ψjss)=Gq2(ψj11ψjss)=q.

    Then

    Nq2(f(X)=c)=q2(s1)+qs1m11j1=1ψj11(ca1)ms1js=1ψjss(cas)=q2(s1)+qs1(m11j1=0ψj11(ca1)1)(ms1js=0ψjss(cas)1).

    It follows that

    Nq2(f(X)=c)=q2(s1)+qs1si=1((cai)mimi1), (3.1)

    where

    (cai)mi={1,ifcai is a residue of ordermi,0,otherwise.

    For a given hFq2. We discuss the two cases according to whether h is zero or not.

    Case 1: h=0. If f(X)=0, then g(Y)=0; if f(X)0, then g(Y)0. Then

    Nq2(l(X,Y)=0)=c1+c2=0Nq2(f(X)=c1)Nq2(g(Y)=c2)=q2(s1)(q2(n1)+(1)t+1(q21)qn2)+c1+c2=0c1,c2Fq2Nq2(f(X)=c1)Nq2(g(Y)=c2). (3.2)

    By Lemma 2.12, (3.1) and (3.2), we have

    Nq2(l(X,Y)=0)=q2(s+n2)+(1)t+1q2(s1)+hn(1)t+1q2(s2)+n+c1Fq2[q2(s+n2)(1)t+1q2(s2)+n+si=1((c1ai)mimi1)(q2n+s3(1)t+1qn+s3)]=q2(s+n2)+(1)t+1q2(s1)+n(1)t+1q2(s2)+n+q2(s+n1)(1)t+1q2(s1)+nq2(s+n2)+(1)t+1q2(s2)+n+c1Fq2[si=1((c1ai)mimi1)(q2n+s3(1)t+1qn+s3)]=q2(s+n1)+c1Fq2[si=1((c1ai)mimi1)(q2n+s3(1)t+1qn+s3)]. (3.3)

    Case 2: hFq2. If f(X)=h, then g(Y)=0; if f(X)=0, then g(Y)=h; if f(X){0,h}, then g(Y){0,h}. So we have

    Nq2(l(X,Y))=h)=c1+c2=hNq2(f(X)=c1)Nq2(g(Y)=c2)=Nq2(f(X)=0)Nq2(g(Y)=h)+Nq2(f(X)=h)Nq2(g(Y)=0)+c1+c2=hc1,c2Fq2{h}Nq2(f(X)=c1)Nq2(g(Y)=c2). (3.4)

    By Lemma 2.12, (3.1) and (3.4),

    Nq2(l(X,Y)=h)=2q2(s+n2)+(1)t+1q2s+n2(1)t+12q2s+n4+(qs+2n3+(1)t+1(q21)qs+n3)si=1((hai)mimi1)+c1Fq2{h}[q2(s+n2)(1)t+1q2s+n4+si=1((c1ai)mimi1)(q2n+s3(1)t+1qn+s3)].

    It follows that

    Nq2(l(X,Y)=h)=2q2(s+n2)+(1)t+1q2s+n2(1)t+12q2s+n4+(qs+2n3+(1)t+1(q21)qs+n3)si=1((hai)mimi1)+c1Fq2{h}[q2(s+n2)(1)t+1q2s+n4+si=1((c1ai)mimi1)(q2n+s3(1)t+1qn+s3)]=q2(s+n1)+(qs+2n3+(1)t+1(q21)qs+n3)si=1((hai)mimi1)+c1Fq2{h}[si=1((c1ai)mimi1)(q2n+s3+(1)tqn+s3)]. (3.5)

    By (3.3) and (3.5), we get the desired result. The proof of Theorem 1.1 is complete.

    There is a direct corollary of Theorem 1.1 and we omit its proof.

    Corollary 4.1. Under the conditions of Theorem 1.1, if a1==as=hFq2, then we have

    Nq2(l(X,Y)=h)=q2(s+n1)+(qs+2n3+(1)t+1(q21)qs+n3)si=1(mi1)+γFq2{h}[si=1((γh)mimi1)(q2n+s3+(1)tqn+s3)],

    where

    (γh)mi={1,ifγhisaresidueofordermi,0,otherwise.

    Finally, we give two examples to conclude the paper.

    Example 4.2. Let F210=α=F2[x]/(x10+x3+1) where α is a root of x10+x3+1. Suppose l(X,Y)=α33x31+x112+y23+α10y24+y1y2+y3y4. Clearly, TrF210/F2(α10)=1, m1=3, m2=11, s=2, n=4, t=0, a2=1. By Theorem 1.1, we have

    N210(l(X,Y)=0)=10245+(327+323)×20=1126587102265344.

    Example 4.3. Let F212=β=F2[x]/(x12+x6+x4+x+1) where β is a root of x12+x6+x4+x+1. Suppose l(X,Y)=x51+x132+y23+β10y24+y1y2+y3y4. Clearly, TrF212/F2(β10)=1, m1=5, m2=13, s=2, n=4, t=0, a1=a2=1. By Corollary 1, we have

    N212(l(X,Y)=1)=25×12+(647643×4095)×48=1153132559312355328.

    This work was jointly supported by the Natural Science Foundation of Fujian Province, China under Grant No. 2022J02046, Fujian Key Laboratory of Granular Computing and Applications (Minnan Normal University), Institute of Meteorological Big Data-Digital Fujian and Fujian Key Laboratory of Data Science and Statistics.

    The authors declare there is no conflicts of interest.



    [1] van Dam RM (2020) A global perspective on white rice consumption and risk of type 2 diabetes. Diabetes Care 43: 2625–2627. https://doi.org/10.2337/dci20-0042 doi: 10.2337/dci20-0042
    [2] Mustafa S (2022) Rice: Market Summaries. FAO. Available from: https://openknowledge.fao.org/server/api/core/bitstreams/7116b9f0-896c-4dac-b4ca-8f3a51212efa/content.
    [3] Socheata V (2024) Kingdom remains tenth-largest rice producing nation. The Phnom Penh Post. Available from: https://www.phnompenhpost.com/national/kingdom-remains-tenth-largest-rice-producing-nation#: ~: text = Indonesia leads Southeast Asia and, year and ranking 10th globally.
    [4] Ab Samat NH, Saili AR, Yusop Z, et al. (2022) Factors affecting selection of rice among the consumer in Shah Alam, Selangor. IOP Conf Ser Earth Environ Sci 1059: 1–8. https://doi.org/10.1088/1755-1315/1059/1/012005 doi: 10.1088/1755-1315/1059/1/012005
    [5] Piao SY, Li ZR, Sun YC, et al. (2020) Analysis of the factors influencing consumers' preferences for rice: locally produced versus the imported in the Ga East Municipality of the Greater Accra Region of Ghana. J Agric Life Environ Sci 32: 177–192. https://doi.org/10.22698/jales.20200016 doi: 10.22698/jales.20200016
    [6] Abubakar Y, Rezai G, Shamsudin MN et al. (2015) Malaysian consumers' demand for quality attributes of imported rice. Aust J Basic Appl Sci 9: 317–322.
    [7] Peterson-Wilhelm B, Nalley LL, Durand-Morat A, et al. (2022) Does rice quality matter? Understanding consumer preferences for rice in Nigeria. J Agric Appl Econ 54: 769–791. https://doi.org/10.1017/aae.2022.38 doi: 10.1017/aae.2022.38
    [8] Qiu X, Yang J, Zhang F, et al. (2021) Genetic dissection of rice appearance quality and cooked rice elongation by genome-wide association study. Crop J 9: 1470–1480. https://doi.org/10.1016/j.cj.2020.12.010 doi: 10.1016/j.cj.2020.12.010
    [9] Mottaleb KA, Mishra AK (2016) Rice consumption and grain-type preference by household: A Bangladesh case. J Agric Appl Econ 48: 298–319. https://doi.org/10.1017/aae.2016.18 doi: 10.1017/aae.2016.18
    [10] Zainol Abidin AZ and Abu Dardak R (2023) Sociological issues and challenges of rice production in Malaysia. Food and Fertilizer Technology Centre for the Asian and Pacific Region (FFTC), Agricultural Policy Platform (FFTC-AP). Available from: https://ap.fftc.org.tw/article/3473
    [11] Antriyandarti E, Agustono, Ani SW, et al. (2023) Consumers' willingness to pay for local rice: Empirical evidence from Central Java, Indonesia. J Agric Food Res 14: 1–7. https://doi.org/10.1016/j.jafr.2023.100851 doi: 10.1016/j.jafr.2023.100851
    [12] Laroche DC, Postolle A (2013) Food sovereignty and agricultural trade policy commitments: How much leeway do West African nations have? Food Policy 38: 115–125. https://doi.org/10.1016/j.foodpol.2012.11.005 doi: 10.1016/j.foodpol.2012.11.005
    [13] Fiamohe R, Nakelse T, Diagne A, et al. (2015) Assessing the effect of consumer purchasing criteria for types of rice in Togo: A choice modeling approach. Agribusiness 31: 433–452. https://doi.org/10.1002/agr.21406 doi: 10.1002/agr.21406
    [14] Stryker JD (2013) Developing competitive rice value chains. In: Wopereis MCS, Johnson D, Horie T, Tollens E, et al. (Eds.), Realizing Africa's rice promise, Wallingford, UK: CABI Publishing, 1–6. https://doi.org/10.1079/9781845938123.0324
    [15] Demont M (2013) Reversing urban bias in African rice markets: A review of 19 national rice development strategies. Glob Food Sec 2: 172–181. https://doi.org/10.1016/j.gfs.2013.07.001 doi: 10.1016/j.gfs.2013.07.001
    [16] Jamora N, Ramaiah V (2022) Global demand for rice genetic resources. CABI Agric Biosci 3: 1–15. https://org.doi/10.1186/s43170-022-00095-6 doi: 10.1186/s43170-022-00095-6
    [17] Yan AO, Yong XU, Xiao-fen CUI, et al. (2016). A genetic diversity assessment of starch quality traits in rice landraces from the Taihu basin, China. J Integr Agric 15: 493–501. https://doi.org/10.1016/S2095-3119(15)61050-4 doi: 10.1016/S2095-3119(15)61050-4
    [18] Rajendran PA, Devi JN, Prabhakaran SV (2021) Breeding for grain quality improvement in rice, In: Ibrokhim Y, Abdurakhmonov (Eds.), Plant Breeding—Current and Future Views, IntechOpen, 1–11. https://doi.org/10.5772/intechopen.95001
    [19] Kim MS, Yang JY, Yu JK, et al. (2021) Breeding of high cooking and eating quality in rice by marker-assisted backcrossing (MABc) using KASP markers. Plants 10: 804. https://doi.org/10.3390/plants10040804 doi: 10.3390/plants10040804
    [20] Zafar S and Jianlong X (2023). Recent advances to enhance nutritional quality of rice. Rice Sci 30: 523–536. https://doi.org/10.1016/j.rsci.2023.05.004 doi: 10.1016/j.rsci.2023.05.004
    [21] Ab Razak S, Nor Azman NHE, Kamaruzaman R, et al. (2020) Genetic diversity of released Malaysian rice varieties based on single nucleotide polymorphism markers. Czech J Genet Plant Breed 56: 62–70. https://doi.org/10.17221/58/2019-CJGPB doi: 10.17221/58/2019-CJGPB
    [22] Sidhu JS, Gill MS, and Bains GS (1975) Milling of paddy in relation to yield and quality of rice of different Indian varieties. J Agric Food Chem 23: 1183–1185. https://doi.org/10.1021/jf60202a035 doi: 10.1021/jf60202a035
    [23] Longvah T, Bhargavi I, Sharma P, et al. (2022) Nutrient variability and food potential of indigenous rice landraces (Oryza sativa L.) from Northeast India. J Food Compos Anal 114: 104838. https://doi.org/10.1016/j.jfca.2022.104838 doi: 10.1016/j.jfca.2022.104838
    [24] Lum MS (2017) Physicochemical characteristics of different rice varieties found in Sabah, Malaysia. Trans Sci Technol 4: 68–75.
    [25] Mohd Sarif H, Rafii MY, Ramli A, et al. (2020) Genetic diversity and variability among pigmented rice germplasm using molecular marker and morphological traits. Biotechnol Biotechnol Equip 34: 747–762. https://doi.org/10.1080/13102818.2020.1804451 doi: 10.1080/13102818.2020.1804451
    [26] Ronie ME, Abdul Aziz AH, Mohd Noor NQI, et al. (2022) Characterisation of Bario rice flour varieties: Nutritional compositions and physicochemical properties. Appl Sci 12: 9064. https://doi.org.10.3390/app12189064 doi: 10.3390/app12189064
    [27] Kew Board of Trustees of the Royal Botanic Gardens (2022) Seed bank design: Seed drying rooms (Technical Information Sheet 11). Available from: https://brahmsonline.kew.org/Content/Projects/msbp/resources/Training/11-Seed-drying-room-design.pdf.
    [28] IRRI (2013) Standard Evaluation System for Rice, 5th ed. International Rice Research Institute (IRRI), Manila, Philippines. 1–55.
    [29] Juliano BO (1971) A simplified assay for milled-rice amylose. Cereal Sci Today 16: 334–360.
    [30] Ekanayake SB, Navaratne EWMDS, Wickramasinghe I, et al. (2018) Determination of changes in amylose and amylopectin percentages of cowpea and green gram during storage. Nutr Food Sci Int J 6: 1–5. https://doi.org/10.19080/nfsij.2018.06.555690 doi: 10.19080/nfsij.2018.06.555690
    [31] Bhattacharya KR, Sowbhagya CM (1972) An improved alkali reaction test for rice quality. Int J Food Sci Technol 7: 323–331. https://doi.org/10.1111/J.1365-2621.1972.TB01667.X doi: 10.1111/J.1365-2621.1972.TB01667.X
    [32] Bioversity International, IRRI, and WARDA (2007) Descriptor for wild and cultivated rice (Oryza spp.). Bioversity International, Rome, Italy, 1–72.
    [33] Cagampang GB, Perez CM, Juliano BO (1973) A gel consistency test for eating quality of rice. J Sci Food Agric 24: 1589–1594. https://doi.org/10.1002/jsfa.2740241214 doi: 10.1002/jsfa.2740241214
    [34] Sivasubramanian S, Menon M (1973) Heterosis and inbreeding depression in rice. Madras Agric J 60: 1139–1144.
    [35] Falconer DS, Mackay TFC (1996) Introduction to Quantitative Genetics, 4th ed, London: Longman Group Ltd.
    [36] Robinson HF, Comstock RE, Harvey PH (1949) Estimates of heritability and the degree of dominance in corn. Agron J 41: 353–359. https://doi.org/10.2134/agronj1949.00021962004100080005x doi: 10.2134/agronj1949.00021962004100080005x
    [37] Mazid MS, Rafii MY, Hanafi MM, et al. (2013) Agro-morphological characterization and assessment of variability, heritability, genetic advance and divergence in bacterial blight resistant rice genotypes. South African J Bot 86: 15–22. https://doi.org/10.1016/j.sajb.2013.01.004 doi: 10.1016/j.sajb.2013.01.004
    [38] Johnson HW, Robinson HF, Comstock RE (1955). Estimates of genetic and environmental variability in soybeans. Agron J 47: 314–318. https://doi.org/10.2134/agronj1955.00021962004700070009x doi: 10.2134/agronj1955.00021962004700070009x
    [39] Sokal RR, Michener CD (1958) A atatistical methods for evaluating relationships. Univ Kansas Sci Bull 38: 1409–1448.
    [40] Botta-Dukát Z (2023) Quartile coefficient of variation is more robust than CV for traits calculated as a ratio. Sci Rep 13: 4671. https://doi.org/10.1038/s41598-023-31711-8 doi: 10.1038/s41598-023-31711-8
    [41] Prasad T, Banumathy S, Sassikumar D, et al. (2021) Study on physicochemical properties of rice landraces for amylose, gel consistency and gelatinization temperature. Electron J Plant Breed 12: 723–731. https://doi.org/10.37992/2021.1203.101 doi: 10.37992/2021.1203.101
    [42] Debsharma SK, Syed MA, Ali MH, et al. (2023) Harnessing on genetic variability and diversity of rice (Oryza sativa L.) genotypes based on quantitative and qualitative traits for desirable crossing materials. Genes 14: 1–21. https://doi.org/10.3390/genes14010010 doi: 10.3390/genes14010010
    [43] Bollinedi H, Vinod KK, Bisht K, et al. (2020) Characterising the diversity of grain nutritional and physico-chemical quality in Indian rice landraces by multivariate genetic analyses. Indian J Genet Plant Breed 80: 26–38. https://doi.org/10.31742/IJGPB.80.1.4 doi: 10.31742/IJGPB.80.1.4
    [44] Tuhina-Khatun M, Hanafi MM, Yusop MR, et al. (2015) Genetic variation, heritability, and diversity analysis of upland rice (Oryza sativa L.) genotypes based on quantitative traits. Biomed Res Int 2015: 290861. https://doi.org/10.1155/2015/290861 doi: 10.1155/2015/290861
    [45] Terfa GN, Gurmu GN (2020) Genetic variability, heritability and genetic advance in linseed (Linum usitatissimum L) genotypes for seed yield and other agronomic traits. Oil Crop Sci 5: 156–160. https://doi.org/10.1016/j.ocsci.2020.08.002 doi: 10.1016/j.ocsci.2020.08.002
    [46] Patel RRS, Sharma D, Das BK, et al. (2021) Study of coefficient of variation (GCV & PCV), heritability and genetic advance in advanced generation mutant line of rice (Oryza sativa L.). Pharma Innov J 10: 784–787.
    [47] Zhao D, Zhang C, Li Q, et al. (2022) Genetic control of grain appearance quality in rice. Biotechnol Adv 60: 108014. https://doi.org/10.1016/j.biotechadv.2022.108014 doi: 10.1016/j.biotechadv.2022.108014
    [48] Ajimilah AH (1984) Quality parameters for Malaysian rice varieties. MARDI Res Bull 12: 320–332.
    [49] Lahkar L, Tanti B (2017) Study of morphological diversity of traditional aromatic rice landraces (Oryza sativa L.) collected from Assam, India. Ann Plant Sci 6: 1855–1861. https://doi.org/10.21746/aps.2017.6.12.9 doi: 10.21746/aps.2017.6.12.9
    [50] Azuka CE, Nkama I, Asoiro FU (2021) Physical properties of parboiled milled local rice varieties marketed in South-East Nigeria. J Food Sci Technol 58: 1788–1796. https://doi.org/10.1007/s13197-020-04690-1 doi: 10.1007/s13197-020-04690-1
    [51] Custodio MC, Demont M, Laborte A et al. (2016) Improving food security in Asia through consumer-focused rice breeding. Glob Food Sec 9: 19–28. https://doi.org/10.1016/j.gfs.2016.05.005 doi: 10.1016/j.gfs.2016.05.005
    [52] Arikit S, Wanchana S, Khanthong S, et al. (2019) QTL-seq identifies cooked grain elongation QTLs near soluble starch synthase and starch branching enzymes in rice (Oryza sativa L.). Sci Rep 9: 1–10. https://doi.org/10.1038/s41598-019-44856-2 doi: 10.1038/s41598-019-44856-2
    [53] Mahadik SM, Sawant AA, Kalse SB (2022) Evaluation of cooking characteristics of different brown rice varieties grown in the Konkan region. Pharma Innov J 11: 546–549.
    [54] Mahmood A, Mei LY, Md Noh MF, et al. (2018) Rice-based traditional Malaysian kuih. Malaysian Appl Biol J 47: 71–77.
    [55] Srinang P, Khotasena S, Sanitchon J, et al. (2023) New source of rice with a low amylose content and slow in vitro digestion for improved health benefits. Agronomy 13: 2622. https://doi.org/10.3390/agronomy13102622 doi: 10.3390/agronomy13102622
    [56] Sultana S, Faruque M, Islam MR (2022) Rice grain quality parameters and determination tools: A review on the current developments and future prospects. Int J Food Prop 25: 1063–1078. https://doi.org/10.1080/10942912.2022.2071295 doi: 10.1080/10942912.2022.2071295
    [57] Calingacion M, Laborte A, Nelson A, et al. (2014) Diversity of global rice markets and the science required for consumer-targeted rice breeding. PLoS One 9(1):1–12. https://doi.org/10.1371/journal.pone.0085106 doi: 10.1371/journal.pone.0085106
    [58] Rebeira SP, Wickramasinghe HAM, Samarasinghe WLG, et al. (2014) Diversity of grain quality characteristics of traditional rice (Oryza sativa L.) varieties in Sri Lanka. Trop Agric Res 25: 470–478. https://doi.org/10.4038/tar.v25i4.8062 doi: 10.4038/tar.v25i4.8062
    [59] Juliano BO, Bechtel DB (1985) The grain and its gross composition. In: Rice: Chemistry and Technology. Cereals and Grains Association. Northwood Circle, USA, 17–57. https://doi.org/10.1094/1891127349.004
    [60] Zhang X, Suzuki H (1991) Comparative study on amylose content, alkali spreading and gel consistency of rice. J Japanese Soc Starch Sci 38: 257–262. https://doi.org/10.5458/jag1972.38.257 doi: 10.5458/jag1972.38.257
    [61] Pushpa R, Suresh R, Iyyanar K, et al. (2018) Study on the gelatinization properties and amylose content in rice germplasm. J Pharmacogn Phytochem SP1: 2934–2942. Available from: https://www.phytojournal.com/special-issue/2018.v7.i1S.3918/study-on-the-gelatinization-properties-and-amylose-content-in-rice-germplasm.
    [62] Kamalaja T, Maheswari KU, Devi KU, et al. (2018) Assessment of grain quality characteristics in the selected newly released rice varieties of central Telenagana zone. Int J Chem Stud 6: 2615–2619.
    [63] Bocevska M, Aldabas I, Andreevska D, et al. (2009) Gelatinization behavior of grains and flour in relation to physico-chemical properties of milled rice (Oryza sativa L.). J Food Qual 32: 108–124. https://doi.org/10.1111/j.1745-4557.2008.00239.x doi: 10.1111/j.1745-4557.2008.00239.x
    [64] Cruz ND, Khush GS (2000) Rice grain quality evaluation procedures. In: Singh RK, Singh US, Khush GS (Eds.), Aromatic rices, New Delhi, India: Oxford & IBH Publishing Co. Pvt. Ltd., 15–28.
    [65] Köten M, Ünsal AS, Kahraman S (2020) Physicochemical, nutritional, and cooking properties of local Karacadag rice (Oryza sativa L.)-Turkey. Int Food Res J 27: 435–444.
    [66] Indrasari SD, Purwaningsih, Jumali, et al. (2019) The volatile components and rice quality of three Indonesian aromatics local paddy. IOP Conf Ser Earth Environ Sci 309: 1–9. https://doi.org/10.1088/1755-1315/309/1/012016 doi: 10.1088/1755-1315/309/1/012016
    [67] Nguyen HTH, Chen ZQ, Fries A, et al. (2022) Effect of additive, dominant and epistatic variances on breeding and deployment strategy in Norway spruce. Forestry 95: 416–427. https://doi.org/10.1093/forestry/cpab052 doi: 10.1093/forestry/cpab052
    [68] Nihad SAI, Manidas AC, Hasan K, et al. (2021) Genetic variability, heritability, genetic advance and phylogenetic relationship between rice tungro virus resistant and susceptible genotypes revealed by morphological traits and SSR markers. Curr Plant Biol 25: 1–9. https://doi.org/10.1016/j.cpb.2020.100194 doi: 10.1016/j.cpb.2020.100194
    [69] Myint MM, Soe ANY, Thandar S (2023) Evaluation of physicochemical characteristics and genetic diversity of widely consumed rice varieties in Kyaukse area, Myanmar. Plant Sci Today 1–12. https://doi.org/10.14719/pst.2264 doi: 10.14719/pst.2264
    [70] Wickramasinghe HAM, Noda T (2008) Physicochemical properties of starches from Sri Lankan rice varieties. Food Sci Technol Res 14: 49–54. https://doi.org/10.3136/fstr.14.49 doi: 10.3136/fstr.14.49
    [71] Chen F, Lu Y, Pan L, et al. (2022). The underlying physicochemical properties and starch structures of Indica rice grains with translucent endosperms under low-moisture conditions. Foods 11: 1378. https://doi.org/10.3390/foods11101378 doi: 10.3390/foods11101378
    [72] Anugrahati NA, Pranoto Y, Marsono Y, et al. (2017) Physicochemical properties of rice (Oryza sativa L.) flour and starch of two Indonesian rice varieties differing in amylose content. Int Food Res J 24: 108–113.
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