Genome-wide association study reveals marker-trait associations for major agronomic traits in proso millet (Panicum miliaceum L.).

MAIN CONCLUSION: The pilot-scale genome-wide association study in the US proso millet identified twenty marker-trait associations for five morpho-agronomic traits identifying genomic regions for future studies (e.g. molecular breeding and map-based cloning). Proso millet (Panicum miliaceum L.) is an ancient grain recognized for its excellent water-use efficiency and short growing season. It is an indispensable part of the winter wheat-based dryland cropping system in the High Plains of the USA. Its grains are endowed with high nutritional and health-promoting properties, making it increasingly popular in the global market for healthy grains. There is a dearth of genomic resources in proso millet for developing molecular tools to complement conventional breeding for developing high-yielding varieties. Genome-wide association study (GWAS) is a widely used method to dissect the genetics of complex traits. In this pilot study of the first-ever GWAS in the US proso millet, 71 globally diverse genotypes of 109 the US proso millet core collection were evaluated for five major morpho-agronomic traits at two locations in western Nebraska, and GWAS was conducted to identify single nucleotide polymorphisms (SNPs) associated with these traits. Analysis of variance showed that there was a significant difference among the genotypes, and all five traits were also found to be highly correlated with each other. Sequence reads from genotyping-by-sequencing (GBS) were used to identify 11,147 high-quality bi-allelic SNPs. Population structure analysis with those SNPs showed stratification within the core collection. The GWAS identified twenty marker-trait associations (MTAs) for the five traits. Twenty-nine putative candidate genes associated with the five traits were also identified. These genomic regions can be used to develop genetic markers for marker-assisted selection in proso millet breeding.

A comprehensive phenotypic and genotypic evaluation of Spanish groundnuts from diverse crosses to identify superior and stable donors for fresh seed dormancy.

Breeding high yielding groundnut cultivars with 2-3 weeks of fresh seed dormancy, particularly in Spanish-type cultivars, enhances the sustainability of agriculture in groundnuts. In this context, we conducted a comprehensive phenotypic and genotypic evaluation of advanced breeding lines developed in the genetic background of Spanish types. By employing multi-phenotyping and marker data, we identified PBS 15044, 16004, 16013, 16015, 16016, 16017, 16020, 16021, 16026, 16031, 16035, 16037, 16038, 16039, 16041, and 16042 with 2-3 weeks dormancy (> 90%).The various parametric and non-parametric estimates identified the stable fresh dormant genotypes with one or more superior economic trait. PBS 16021, 15044, 16038, and 16039 identified with high hundred pod weight (HPW) were also reported having high intensity of dormancy (> 90% for up to 3 weeks); PBS 15044, 16016, PBS 16038 and PBS 16039 with high hundred kernel weight (HKW) also reported with up to 3 weeks fresh seed dormancy; and PBS 16013, 16031, and 16038 with up to 3 weeks fresh seed dormancy had high shelling percentage (SP). They can be used to develop lines with the desired level of dormancy, and high yields, by designing appropriate breeding strategies.

Maternal effects, reciprocal differences and combining ability study for yield and its component traits in maize (Zea mays L.) through modified diallel analysis.

Combining ability status of the inbred lines is crucial information for hybrid breeding program. Diallel or line × tester mating designs are frequently used to evaluate the combining ability. In the current study a modified diallel model was used, wherein the Griffing's combining ability effects were further partitioned to understand the effects due to maternal and reciprocal. To do this, eight parental lines of maize were crossed in full diallel method and the generated hybrids along with parents were phenotyped. The field data on the quantitative traits was analyzed using both Griffing's and the modified model to determine how well the parents' and the F1 hybrids combined. For each of the traits, a sizable reciprocal and maternal variance was observed. The number of kernel rows per cob variable had a ratio of additive variance to dominance variance greater than one. All other traits including grain yield had a ratio close to zero, suggesting that non-additive gene action was primarily responsible for the genetic control of most of the traits. The narrow sense heritability was low to moderate for majority of the variables, except for number of kernel rows per cob. With the help of the improved model, it was possible to choose superior parents and cross-parent pairings with accuracy. Based on the modified general combining ability effects and maternal effects, the parental line P5 was recognized as a potential female parent and P7 as a good male parent for grain yield and yield-attributing characteristics. The cross combination of P8×P1 had the highest specific combining ability effect on grain yield. P5×P6 cross had the highest reciprocal effect. The correlation analysis implies that the Griffing's general combining ability effects and specific combining ability effects were found to be less efficient in predicting F1 performance as compared to the modified model.

Pyramiding of triple Clubroot resistance loci conferred superior resistance without negative effects on agronomic traits in Brassica napus.

Clubroot disease caused by Plasmodiophora brassicae is becoming a serious threat to rapeseed (Brassica napus) production worldwide. Breeding resistant varieties using CR (clubroot resistance) loci is the most promising solution. Using marker-assisted selection and speed-breeding technologies, we generated Brassica napus materials in homozygous or heterozygous states using CRA3.7, CRA08.1, and CRA3.2 loci in the elite parental line of the Zhongshuang11 background. We developed three elite lines with two CR loci in different combinations and one line with three CR loci at the homozygous state. In our study, we used six different clubroot strains (Xinmin, Lincang, Yuxi, Chengdu, Chongqing, and Jixi) which are categorized into three groups based on our screening results. The newly pyramided lines with two or more CR loci displayed better disease resistance than the parental lines carrying single CR loci. There is an obvious gene dosage effect between CR loci and disease resistance levels. For example, pyramided lines with triple CR loci in the homozygous state showed superior resistance for all pathogens tested. Moreover, CR loci in the homozygous state are better on disease resistance than the heterozygous state. More importantly, no negative effect was observed on agronomic traits for the presence of multiple CR loci in the same background. Overall, these data suggest that the pyramiding of triple clubroot resistance loci conferred superior resistance with no negative effects on agronomic traits in Brassica napus.

High-dimensional multi-omics measured in controlled conditions are useful for maize platform and field trait predictions.

KEY MESSAGE: Transcriptomics and proteomics information collected on a platform can predict additive and non-additive effects for platform traits and additive effects for field traits. The effects of climate change in the form of drought, heat stress, and irregular seasonal changes threaten global crop production. The ability of multi-omics data, such as transcripts and proteins, to reflect a plant's response to such climatic factors can be capitalized in prediction models to maximize crop improvement. Implementing multi-omics characterization in field evaluations is challenging due to high costs. It is, however, possible to do it on reference genotypes in controlled conditions. Using omics measured on a platform, we tested different multi-omics-based prediction approaches, using a high dimensional linear mixed model (MegaLMM) to predict genotypes for platform traits and agronomic field traits in a panel of 244 maize hybrids. We considered two prediction scenarios: in the first one, new hybrids are predicted (CV-NH), and in the second one, partially observed hybrids are predicted (CV-POH). For both scenarios, all hybrids were characterized for omics on the platform. We observed that omics can predict both additive and non-additive genetic effects for the platform traits, resulting in much higher predictive abilities than GBLUP. It highlights their efficiency in capturing regulatory processes in relation to growth conditions. For the field traits, we observed that the additive components of omics only slightly improved predictive abilities for predicting new hybrids (CV-NH, model MegaGAO) and for predicting partially observed hybrids (CV-POH, model GAOxW-BLUP) in comparison to GBLUP. We conclude that measuring the omics in the fields would be of considerable interest in predicting productivity if the costs of omics drop significantly.

Unraveling the complexities of drought stress in cotton: a multifaceted analysis of selection criteria and breeding approaches.

Abiotic stress tolerance breeding programs present a spectrum of perspectives, yet definitive solutions remain elusive, with each approach carrying its own set of advantages and disadvantages. This study systematically evaluates extant methodologies, comparing plant performance across varied genotypes and selection traits under optimal and stress conditions. The objective is to elucidate prevailing ambiguities. Ten homozygous lines (F8 generation) were assessed using a randomized block design alongside five control varieties, with four replicates cultivated under well-watered and deficit water conditions. It is noteworthy that six of the ten homozygous lines were cultivated exclusively under well-watered conditions (F3 to F7), while four lines experienced deficit water conditions (F3 to F7). All five control varieties underwent cultivation under both conditions. These findings underscore the necessity for tailored breeding programs attuned to specific environmental exigencies, recognizing that individual traits manifest divergent responses to varying conditions. It is evident that certain traits exhibit marked disparities under well-watered conditions, while others evince heightened differentiation under water deficit conditions. Significantly, our analysis reveals a pronounced interaction between irrigation regimes and selection traits, which serves to underscore the nuanced interplay between genotype and environmental stress.

Research on Plant Genomics and Breeding 2.0.

Plant genomics and breeding is one among the several highly regarded disciplines in today's field of biological sciences [...].

Genetic and Biotechnological Approaches to Improve Fruit Bioactive Content: A Focus on Eggplant and Tomato Anthocyanins.

Anthocyanins are a large group of water-soluble flavonoid pigments. These specialized metabolites are ubiquitous in the plant kingdom and play an essential role not only in plant reproduction and dispersal but also in responses to biotic and abiotic stresses. Anthocyanins are recognized as important health-promoting and chronic-disease-preventing components in the human diet. Therefore, interest in developing food crops with improved levels and compositions of these important nutraceuticals is growing. This review focuses on work conducted to elucidate the genetic control of the anthocyanin pathway and modulate anthocyanin content in eggplant (Solanum melongena L.) and tomato (Solanum lycopersicum L.), two solanaceous fruit vegetables of worldwide relevance. While anthocyanin levels in eggplant fruit have always been an important quality trait, anthocyanin-based, purple-fruited tomato cultivars are currently a novelty. As detailed in this review, this difference in the anthocyanin content of the cultivated germplasm has largely influenced genetic studies as well as breeding and transgenic approaches to improve the anthocyanin content/profile of these two important solanaceous crops. The information provided should be of help to researchers and breeders in devising strategies to address the increasing consumer demand for nutraceutical foods.

RNAi-mediated downregulation of AcCENH3 can induce in vivo haploids in onion (Allium cepa L.).

Haploid induction (HI) holds great promise in expediting the breeding process in onion, a biennial cross-pollinated crop. We used the CENH3-based genome elimination technique in producing a HI line in onion. Here, we downregulated AcCENH3 using the RNAi approach without complementation in five independent lines. Out of five events, only three could produce seeds upon selfing. The progenies showed poor seed set and segregation distortion, and we were unable to recover homozygous knockdown lines. The knockdown lines showed a decrease in accumulation of AcCENH3 transcript and protein in leaf tissue. The decrease in protein content in transgenic plants was correlated with poor seed set. When the heterozygous knockdown lines were crossed with wild-type plants, progenies showed HI by genome elimination of the parental chromosomes from AcCENH3 knockdown lines. The HI efficiency observed was between 0 and 4.63% in the three events, and it was the highest (4.63%) when E1 line was crossed with wildtype. Given the importance of doubled haploids in breeding programmes, the findings from our study are poised to significantly impact onion breeding.

New Frontiers in Potato Breeding: Tinkering with Reproductive Genes and Apomixis.

Potato is the most important non-cereal crop worldwide, and, yet, genetic gains in potato have been traditionally delayed by the crop's biology, mostly the genetic heterozygosity of autotetraploid cultivars and the intricacies of the reproductive system. Novel site-directed genetic modification techniques provide opportunities for designing climate-smart cultivars, but they also pose new possibilities (and challenges) for breeding potato. As potato species show a remarkable reproductive diversity, and their ovules have a propensity to develop apomixis-like phenotypes, tinkering with reproductive genes in potato is opening new frontiers in potato breeding. Developing diploid varieties instead of tetraploid ones has been proposed as an alternative way to fill the gap in genetic gain, that is being achieved by using gene-edited self-compatible genotypes and inbred lines to exploit hybrid seed technology. In a similar way, modulating the formation of unreduced gametes and synthesizing apomixis in diploid or tetraploid potatoes may help to reinforce the transition to a diploid hybrid crop or enhance introgression schemes and fix highly heterozygous genotypes in tetraploid varieties. In any case, the induction of apomixis-like phenotypes will shorten the time and costs of developing new varieties by allowing the multi-generational propagation through true seeds. In this review, we summarize the current knowledge on potato reproductive phenotypes and underlying genes, discuss the advantages and disadvantages of using potato's natural variability to modulate reproductive steps during seed formation, and consider strategies to synthesize apomixis. However, before we can fully modulate the reproductive phenotypes, we need to understand the genetic basis of such diversity. Finally, we visualize an active, central role for genebanks in this endeavor by phenotyping properly genotyped genebank accessions and new introductions to provide scientists and breeders with reliable data and resources for developing innovations to exploit market opportunities.

Research on the Effects of the Relationship between Agronomic Traits and Dwarfing Genes on Yield in Colored Wheat.

This research focuses on 72 approved varieties of colored wheat from different provinces in China. Utilizing coefficients of variation, structural equation models, and correlation analyses, six agronomic traits of colored wheat were comprehensively evaluated, followed by further research on different dwarfing genes in colored wheat. Using the entropy method revealed that among the 72 colored wheat varieties, 10 were suitable for cultivation. Variety 70 was the top-performing variety, with a comprehensive index of 87.15%. In the final established structural equation model, each agronomic trait exhibited a positive direct effect on yield. Notably, plant height, spike length, and flag leaf width had significant impacts on yield, with path coefficients of 0.55, 0.40, and 0.27. Transcriptome analysis and real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) validation were used to identify three dwarfing genes controlling plant height: Rht1, Rht-D1, and Rht8. Subsequent RT-qPCR validation clustering heatmap results indicated that Rht-D1 gene expression increased with the growth of per-acre yield. Rht8 belongs to the semi-dwarf gene category and has a significant positive effect on grain yield. However, the impact of Rht1, as a dwarfing gene, on agronomic traits varies. These research findings provide crucial references for the breeding of new varieties.

Assessing myBaits Target Capture Sequencing Methodology Using Short-Read Sequencing for Variant Detection in Oat Genomics and Breeding.

The integration of target capture systems with next-generation sequencing has emerged as an efficient tool for exploring specific genetic regions with a high resolution and facilitating the rapid discovery of novel alleles. Despite these advancements, the application of targeted sequencing methodologies, such as the myBaits technology, in polyploid oat species remains relatively unexplored. In this study, we utilized the myBaits target capture method offered by Daicel Arbor Biosciences to detect variants and assess their reliability for variant detection in oat genomics and breeding. Ten oat genotypes were carefully chosen for targeted sequencing, focusing on specific regions on chromosome 2A to detect variants. The selected region harbors 98 genes. Precisely designed baits targeting the genes within these regions were employed for the target capture sequencing. We employed various mappers and variant callers to identify variants. After the identification of variants, we focused on the variants identified via all variants callers to assess the applicability of the myBaits sequencing methodology in oat breeding. In our efforts to validate the identified variants, we focused on two SNPs, one deletion and one insertion identified via all variant callers in the genotypes KF-318 and NOS 819111-70 but absent in the remaining eight genotypes. The Sanger sequencing of targeted SNPs failed to reproduce target capture data obtained through the myBaits technology. Similarly, the validation of deletion and insertion variants via high-resolution melting (HRM) curve analysis also failed to reproduce target capture data, again suggesting limitations in the reliability of the myBaits target capture sequencing using short-read sequencing for variant detection in the oat genome. This study shed light on the importance of exercising caution when employing the myBaits target capture strategy for variant detection in oats. This study provides valuable insights for breeders seeking to advance oat breeding efforts and marker development using myBaits target capture sequencing, emphasizing the significance of methodological sequencing considerations in oat genomics research.

Dual-Model GWAS Analysis and Genomic Selection of Maize Flowering Time-Related Traits.

An appropriate flowering period is an important selection criterion in maize breeding. It plays a crucial role in the ecological adaptability of maize varieties. To explore the genetic basis of flowering time, GWAS and GS analyses were conducted using an associating panel consisting of 379 multi-parent DH lines. The DH population was phenotyped for days to tasseling (DTT), days to pollen-shedding (DTP), and days to silking (DTS) in different environments. The heritability was 82.75%, 86.09%, and 85.26% for DTT, DTP, and DTS, respectively. The GWAS analysis with the FarmCPU model identified 10 single-nucleotide polymorphisms (SNPs) distributed on chromosomes 3, 8, 9, and 10 that were significantly associated with flowering time-related traits. The GWAS analysis with the BLINK model identified seven SNPs distributed on chromosomes 1, 3, 8, 9, and 10 that were significantly associated with flowering time-related traits. Three SNPs 3_198946071, 9_146646966, and 9_152140631 showed a pleiotropic effect, indicating a significant genetic correlation between DTT, DTP, and DTS. A total of 24 candidate genes were detected. A relatively high prediction accuracy was achieved with 100 significantly associated SNPs detected from GWAS, and the optimal training population size was 70%. This study provides a better understanding of the genetic architecture of flowering time-related traits and provides an optimal strategy for GS.

Assessing Falling Number Stability Increases the Genomic Prediction Ability of Pre-Harvest Sprouting Resistance in Common Winter Wheat.

Pre-harvest sprouting (PHS) resistance is a complex trait, and many genes influencing the germination process of winter wheat have already been described. In the light of interannual climate variation, breeding for PHS resistance will remain mandatory for wheat breeders. Several tests and traits are used to assess PHS resistance, i.e., sprouting scores, germination index, and falling number (FN), but the variation of these traits is highly dependent on the weather conditions during field trials. Here, we present a method to assess falling number stability (FNS) employing an after-ripening period and the wetting of the kernels to improve trait variation and thus trait heritability. Different genome-based prediction scenarios within and across two subsequent seasons based on overall 400 breeding lines were applied to assess the predictive abilities of the different traits. Based on FNS, the genome-based prediction of the breeding values of wheat breeding material showed higher correlations across seasons (r=0.505-0.548) compared to those obtained for other traits for PHS assessment (r=0.216-0.501). By weighting PHS-associated quantitative trait loci (QTL) in the prediction model, the average predictive abilities for FNS increased from 0.585 to 0.648 within the season 2014/2015 and from 0.649 to 0.714 within the season 2015/2016. We found that markers in the Phs-A1 region on chromosome 4A had the highest effect on the predictive abilities for FNS, confirming the influence of this QTL in wheat breeding material, whereas the dwarfing genes Rht-B1 and Rht-D1 and the wheat-rye translocated chromosome T1RS.1BL exhibited effects, which are well-known, on FN per se exclusively.

Inheritance of Resistance to Chickpea Fusarium Wilt Disease (Fusarium oxysporum f. sp. ciceris Race 2) in a Wide-Cross Cicer arietinum × Cicer reticulatum Mapping Family.

Chickpea (Cicer arietinum) is a major food legume providing high quality nutrition, especially in developing regions. Chickpea wilt (Fusarium oxysporum f. sp. ciceris) causes significant annual losses. Integrated disease management of Fusarium wilt is supported by resistant varieties. Relatively few resistance genes are known so there is value in exploring genetic resources in chickpea wild relatives. This study investigates the inheritance of Fusarium wilt resistance (race 2) in recombinant inbred lines (RILs) from a cross between a cultivated susceptible chickpea variety (Gokce) and a wild resistant Cicer reticulatum line (Kayat-077). RILs, parents, resistant and susceptible tester lines were twice grown in the greenhouse with inoculation and disease symptoms scored. DNA was extracted from dried leaves and individuals were single nucleotide polymorphism (SNP) genotyped. SNPs were placed on the reference chickpea genome and quantitative trait locus (QTL) mapping was performed. Significant QTL regions were examined using PulseDB to identify candidate genes. The results showed the segregation of Fusarium wilt resistance conforming to a single gene inheritance. One significant QTL was found at the start of chromosome 8, containing 138 genes, three of which were disease-resistance candidates for chickpea breeding.

Molecular Markers for Marker-Assisted Breeding for Biotic and Abiotic Stress in Melon (Cucumis melo L.): A Review.

Melon (Cucumis melo L.) is a globally grown crop renowned for its juice and flavor. Despite growth in production, the melon industry faces several challenges owing to a wide range of biotic and abiotic stresses throughout the growth and development of melon. The aim of the review article is to consolidate current knowledge on the genetic mechanism of both biotic and abiotic stress in melon, facilitating the development of robust, disease-resistant melon varieties. A comprehensive literature review was performed, focusing on recent genetic and molecular advancements related to biotic and abiotic stress responses in melons. The review emphasizes the identification and analysis of quantitative trait loci (QTLs), functional genes, and molecular markers in two sections. The initial section provides a comprehensive summary of the QTLs and major and minor functional genes, and the establishment of molecular markers associated with biotic (viral, bacterial, and fungal pathogens, and nematodes) and abiotic stress (cold/chilling, drought, salt, and toxic compounds). The latter section briefly outlines the molecular markers employed to facilitate marker-assisted backcrossing (MABC) and identify cultivars resistant to biotic and abiotic stressors, emphasizing their relevance in strategic marker-assisted melon breeding. These insights could guide the incorporation of specific traits, culminating in developing novel varieties, equipped to withstand diseases and environmental stresses by targeted breeding, that meet both consumer preferences and the needs of melon breeders.

Multi-trait index: selection and recommendation of superior black bean genotypes as new improved varieties.

Common bean provides diet rich in vitamins, fiber, minerals, and protein, which could contribute into food security of needy populations in many countries. Developing genotypes that associate favorable agronomic and grain quality traits in the common bean crop could increase the chances of adopting new cultivars black bean. In this context, the present study aimed at selection of superior black bean lines using multi-variate indexes, Smith-Hazel-index, and genotype by yield*trait biplot analysis. These trials were conducted in Campos dos Goytacazes - RJ, in 2020 and 2021. The experimental design used was randomized blocks, with 28 treatments and three replications. The experimental unit consisted of four rows 4.0 m long, spaced at 0.50 m apart, with a sowing density of 15 seeds per meter. The two central rows were used for the evaluations. The selection of superior genotypes was conducted using the multiple trait stability index (MTSI), multi-trait genotype-ideotype distance index (MGIDI), multi-trait index based on factor analysis and genotype-ideotype distance (FAI-BLUP), Smith-Hazel index, and Genotype by Yield*Trait Biplot (GYT). The multivariate indexes efficiently selected the best black bean genotypes, presenting desirable selection gains for most traits. The use of multivariate indexes and GYT enable the selection of early genotypes with higher grain yields. These lines G9, G13, G17, G23, and G27 were selected based on their performance for multiple traits closest to the ideotype and could be recommended as new varieties.

High-yield hybrid breeding of Camellia oleifolia based on ISSR molecular markers.

BACKGROUND: C. Oleifera is among the world's largest four woody plants known for their edible oil production, yet the contribution rate of improved varieties is less than 20%. The species traditional breeding is lengthy cycle (20-30 years), occupation of land resources, high labor cost, and low accuracy and efficiency, which can be enhanced by molecular marker-assisted selection. However, the lack of high-quality molecular markers hinders the species genetic analysis and molecular breeding. RESULTS: Through quantitative traits characterization, genetic diversity assessment, and association studies, we generated a selection population with wide genetic diversity, and identified five excellent high-yield parental combinations associated with four reliable high-yield ISSR markers. Early selection criteria were determined based on kernel fresh weight and cultivated 1-year seedling height, aided by the identification of these 4 ISSR markers. Specific assignment of selected individuals as paternal and maternal parents was made to capitalize on their unique attributes. CONCLUSIONS: Our results indicated that molecular markers-assisted breeding can effectively shorten, enhance selection accuracy and efficiency and facilitate the development of a new breeding system for C. oleifera.

A 3D printed plant model for accurate and reliable 3D plant phenotyping.

BACKGROUND: This study addresses the importance of precise referencing in 3-dimensional (3D) plant phenotyping, which is crucial for advancing plant breeding and improving crop production. Traditionally, reference data in plant phenotyping rely on invasive methods. Recent advancements in 3D sensing technologies offer the possibility to collect parameters that cannot be referenced by manual measurements. This work focuses on evaluating a 3D printed sugar beet plant model as a referencing tool. RESULTS: Fused deposition modeling has turned out to be a suitable 3D printing technique for creating reference objects in 3D plant phenotyping. Production deviations of the created reference model were in a low and acceptable range. We were able to achieve deviations ranging from -10 mm to +5 mm. In parallel, we demonstrated a high-dimensional stability of the reference model, reaching only ±4 mm deformation over the course of 1 year. Detailed print files, assembly descriptions, and benchmark parameters are provided, facilitating replication and benefiting the research community. CONCLUSION: Consumer-grade 3D printing was utilized to create a stable and reproducible 3D reference model of a sugar beet plant, addressing challenges in referencing morphological parameters in 3D plant phenotyping. The reference model is applicable in 3 demonstrated use cases: evaluating and comparing 3D sensor systems, investigating the potential accuracy of parameter extraction algorithms, and continuously monitoring these algorithms in practical experiments in greenhouse and field experiments. Using this approach, it is possible to monitor the extraction of a nonverifiable parameter and create reference data. The process serves as a model for developing reference models for other agricultural crops.