Fertilization and Soil Ploughing Practices under Changing Physical Environment Lead to Soil Organic Carbon Dynamics under Conservation Agriculture in Rice-Wheat Cropping System: A Scoping Review

Ploughing and fertilization practices in rice-wheat system have deteriorated the soil carbon (C) pools. Conservation agriculture (CA) based management approaches have proven to enhance C sequestration and reverse the loss of soil-organic-carbon (SOC), which further enhances soil fertility. Different fractions of SOC pools react to the alterations in management practices and indicate changes in SOC dynamics as compared to total C in the soil. Higher SOC levels in soil have been observed in case of reduced/no-till (NT) practices than conventional tillage (CT). However, between CT and zero tillage/NT, total SOC stocks diminished with an increase in soil depth, which demonstrated that the benefits of SOC are more pronounced in the topsoil under NT. Soil aggregation provides physical protection to C associated with different-sized particles, thus, the improvement in soil aggregation through CA is an effective way to mitigate soil C loss. Along with less soil disturbance, residual management, suitable crop rotation, rational application of manures and fertilizers, and integrated nutrient management have been found to be effective in not only improving soil C stock but also enhancing the soil health and productivity. Thus, CA can be considered as a potential method in the build-up of SOC of soil in rice-wheat system.

Production of reactive oxygen species by freezing stress and the protective roles of antioxidant enzymes in plants

As one of the most severe environmental stresses, freezing stress can determine native flora in nature and severely reduce crop production. Many mechanisms have been proposed to explain the damage induced by freezing-thawing cycle, and oxidative stress caused by uncontrollable production of harmful reactive oxygen species (ROS) are partially contributed to causing the injury. Plants in temperate regions have evolved a unique but effective metabolism of protecting themselves called cold acclimation. Cold-acclimating plants undergo a complex but orchestrated metabolic process to increase cold hardness triggered by exposure to low temperature and shortened photoperiod and achieve the maximum freezing tolerance by a concerted regulation and expression of a number of cold responsive genes. A complicated enzymatic system have been evolved in plants to scavenge the ROS to protect themselves from oxidative stress, therefore, cold-acclimating plants are expected to increase the de novo synthesis of the genes of antioxidant genes. Indeed, many antioxidant genes increase the expression levels in response to low temperature. Furthermore, the higher expression of many antioxidant enzymes are positively correlated to inducing higher tolerance levels against freezing. All the information summarized here can be applied for developing crop and horticultural plants to have more freezing tolerance for higher production with better quality. There have been extensive studies on the activities of antioxidant enzymes and the gene regulation, however, more researches will be required in near future to elucidate the most effective antioxidant enzymes to induce highest freezing tolerance in a crop plant in a transformation process or a breeding program.

Comparison of fatty acid composition,phytochemical profile and antioxidant activity in four flax(Linum usitatissimum L.)varieties

The present study evaluates variations among flaxseed varities in terms of fatty acid composition,phytochemical profile,and antioxidant activity determined by oxygen radical absorbance capacity(ORAC),2,2-Diphenyl-1-picrylhydrazyl(DPPH)and ferrous ion reducing antioxidant power(FRAP)assays.Significant variations in fatty acid composition,phenolic acids and lignan were observed in flaxseed varieties from different countries.Among them,unsaturated fatty acids accounted over 4/5 of total fatty acid content.The highest ratio of linolenic acid of total fatty acid was observed in USPEA,whereas the lowest one was found in Yexiao.USPEA showed the highest content of total phenolics,as well as flaxseed lignan.In general,total phenolics appeared to be the main contributors of antioxidant capacity of flaxseed,which presented significant positive correlation.Our study revealed that both cultivar and origin of seed significantly affected fatty acid composition,phenolic acids,lignans and subsequent antioxidant activity of flaxseed.These results provided new aspects of breeding resources of flaxseed cultivars by presenting their quality specification and possible commercial value.

Evaluation of Expression Stability of Candidate References Genes among Green and Yellow Pea Cultivars (<i>Pisum sativum</i>L.) Subjected to Abiotic and Biotic Stress

Dry pea (Pisum sativum L.) is grown as human and animal feed throughout the world. Large yield losses in pea due to biotic and abiotic stresses compel an improved understanding of mechanisms of stress tolerance and genetic determinants conditioning these tolerances. The availability of stably expressed reference genes is a prerequisite for examining differential gene expression. The objective of this study was to examine the expression profile of several candidate reference genes across a broad range of commercial pea cultivars. Expression profiles of five candidate reference genes;18s rRNA, actin, TIF, β tubulin-2 and β tubulin-3 were examined. Relative quantifications of candidate reference genes were estimated from control plants, plants after 48 h of cold treatment, and plants 24 and 48 h after inoculation with Sclerotinia sclerotiorum, the causal agent of white mold disease of pea. RT-qPCR was performed on cDNA synthesized from three food grade spring peas, Ariel, Aragorn, and Sterling, and two spring yellow peas, Delta and Universal, which are used as animal feed. Analysis of variance (ANOVA) of CT values demonstrated significant variation between varieties and treatments under cold and disease conditions. The most abundant transcripts among tested reference genes were for 18s rRNA. Stability analysis indicated that TIF and β tubulin-3 genes were the most stably expressed candidate genes under both cold and disease stress and could serve as reference genes across a wide range of pea cultivars.

Pedigree and SSR Data Analysis Reveal Dominant Prevalence of Few Parents in Pedigrees of Pakistani Wheat Varieties

The international recognition of the importance of genetic diversity demands continuous estimation of genetic diversity of in hand population as test of its buffering capacity against all putative threats. Randomly selected Pakistani wheat varieties developed during 1965-1999 and 2000-2011 were evaluated on the basis of pedigree and SSR data. At 2nd and 3rd levels of pedigree, average occurrence of a parent per variety was 2.1 times. The dominating parents included BLUEBIRD, KALYANSONA and SIETE-CERROS-66, which were present in the pedigrees of 71.42%, 64.28%, and 58.57% varieties, respectively. The varieties INQLAB-91 and KIRAN-95 had the same pedigree and were genetically identical as revealed by SSR data. Similarly, varieties PAVON-76 and SOGHAT-90 also had the same parents in their pedigrees. This genetic similarity was also confirmed by SSR based cluster. The SSR based PC1 and PC2 showed narrow genetic diversity confirming the presence of few dominating parents. The results emphasize the inclusion of novel and genetically diverse parents in Pakistani wheat breeding programs to maintain broader genetic base of varieties/cultivars for buffering the effects of ever changing virulent pathogens and crop growth environments.

Evolutionary genomics of climatic adaptation and resilience to climate change in alfalfa

Given the escalating impact of climate change on agriculture and food security,gaining insights into the evolutionary dynamics of climatic adaptation and uncovering climate-adapted variation can empower the breeding of climate-resilient crops to face future climate change.Alfalfa(Medicago sativa subsp.sativa),the queen of forages,shows remarkable adaptability across diverse global environments,making it an excellent model for investigating species responses to climate change.In this study,we performed population genomic analyses using genome resequencing data from 702 accessions of 24 Medicago species to unravel alfalfa’s climatic adaptation and genetic susceptibility to future climate change.We found that interspecific genetic exchange has contributed to the gene pool of alfalfa,particularly enriching defense and stress-response genes.Intersubspecific introgression between M.sativa subsp.falcata(subsp.falcata)and alfalfa not only aids alfalfa’s climatic adaptation but also introduces genetic burden.A total of 1671 genes were associated with climatic adaptation,and 5.7%of them were introgressions from subsp.falcata.By integrating climate-associated variants and climate data,we identified populations that are vulnerable to future climate change,particularly in higher latitudes of the Northern Hemisphere.These findings serve as a clarion call for targeted conservation initiatives and breeding efforts.We also identified preadaptive populations that demonstrate heightened resilience to climate fluctuations,illuminating a pathway for future breeding strategies.Collectively,this study enhances our understanding about the local adaptation mechanisms of alfalfa and facilitates the breeding of climate-resilient alfalfa cultivars,contributing to effective agricultural strategies for facing future climate change.

Cover Crop and Irrigation Effects on Soil Microbial Communities and Enzymes in Semiarid Agroecosystems of the Central Great Plains of North America

Cover crops can have beneficial effects on soil microbiology by increasing carbon （C） supply, but these beneficial effects can be modulated by precipitation conditions. The objective of this study was to compare a fallow-winter wheat （Triticum aestivum L.） rotation to several cover crop-winter wheat rotations under rainfed and irrigated conditions in the semiarid US High Plains. Experiments were carried out at two sites, Sidney in Nebraska, and Akron in Colorado, USA, with three times of soil sampling in 2012--2013 at cover crop termination, wheat planting, and wheat maturity. The experiments included four single-species cover crops, a 10-species mixture, and a fallow treatment. The variables measured were soil C and nitrogen （N）, soil community structure by fatty acid methyl ester （FAME） profiles, and soil β-glucosidase,β-glucosaminidase, and phosphodiesterase activities. The fallow treatment, devoid of living plants, reduced the concentrations of most FAMEs at cover crop termination. The total FAME concentration was correlated with cover crop biomass （R = 0.62 at Sidney and 0.44 at Akron）. By the time of wheat planting, there was a beneficial effect of irrigation, which caused an increase in myeorrhizal and protozoan markers. At wheat maturity, the cover crop and irrigation effects on soil FAMEs had subsided, but irrigation had a positive effect on the β-glucosidase and phosphodiesterase activities at Akron, which was the drier of the two sites. Cover crops and irrigation were slow to impact soil C concentration. Our results show that cover crops had a short-lived effect on soil microbial communities in semiarid wheat-based rotations and irrigation could enhance soil enzyme activity. In the semiarid environment, longer time spans may have been needed to see beneficial effects of cover crops on soil microbial community structure, soil enzyme activities, and soil C sequestration.

Potential Breeding for High Nitrogen Fixation in <i>Pisum sativum</i>L.: Germplasm Phenotypic Characterization and Genetic Investigation

Nitrogen (N) is the most yield-limiting crop nutrient worldwide. Industrially produced N has increased in cost over the past years, and is unavailable in many regions around the globe. Biological N fixation by rhizobial bacteria is a great underutilized resource that this project aims to maximize. Grain legumes fix approximately 20 to 100 kg·N·ha-1·yr-1. The amount of N supplied by fixation is affected by genes and traits of both the bacterial and plant partners. The objectives of this study are to identify Pisum sativum varieties with high nitrogen fixation efficiency. This is achieved by germplasm screening and phenotypic evaluation of nodule formation, total plant nitrogen, and residual nitrogen in soil. Significant differences in plant total nitrogen among the various cultivated genotypes were found, with heritability of 0.57. These pea varieties left in the soil a residual N that varies between 11.21 to 65.018 kg.N.ha-1. Our findings reveal a unique opportunity for improving N fixation through genetic crossing and selection.

A community resource for exploring and utilizing genetic diversity in the USDA pea single plant plus collection

Globally,pea(Pisum sativum L.)is an important temperate legume crop for food,feed and fodder,and many breeding programs develop cultivars adapted to these end-uses.In order to assist pea development efforts,we assembled the USDA Pea Single Plant Plus Collection(PSPPC),which contains 431 P.sativum accessions with morphological,geographic and taxonomic diversity.The collection was characterized genetically in order to maximize its value for trait mapping and genomics-assisted breeding.To that end,we used genotyping-by-sequencing—a cost-effective method for de novo single-nucleotide polymorphism(SNP)marker discovery—to generate 66591 high-quality SNPs.These data facilitated the identification of accessions divergent from mainstream breeding germplasm that could serve as sources of novel,favorable alleles.In particular,a group of accessions from Central Asia appear nearly as diverse as a sister species,P.fulvum,and subspecies,P.sativum subsp.elatius.PSPPC genotypes can be paired with new and existing phenotype data for trait mapping;as proof-of-concept,we localized Mendel’s A gene controlling flower color to its known position.We also used SNP data to define a smaller core collection of 108 accessions with similar levels of genetic diversity as the entire PSPPC,resulting in a smaller germplasm set for research screening and evaluation under limited resources.Taken together,the results presented in this study along with the release of a publicly available SNP data set comprise a valuable resource for supporting worldwide pea genetic improvement efforts.

Using Surface Response Models to Evaluate the Effects of Kinetin on Dioscorea alata Propagated in Wtro

Kinetin is an important growth hormone used for in vitro propagation, but its dynamic and temporal effects on Dioscoreaalata have not been thoroughly evaluated. In this study, surface response models were developed to better elucidate the effects ofkinetin on D. alata propagated in vitro. Nodal segments were obtained from Akaaba, an important D. alata cultivar in Ghana, andpropagated in vitro under five kinetin rates （0, 2.5, 5, 7.5 and 10 μM）. The models were developed using segmented multipleregression with time and kinetin as the predictors. The effects on plant height, the number of leaves, shoots and roots were assessedwith three-dimensional figures for better observation of temporal trends. The model fit was very good with normalized root meansquared error （NRMSE） = 0.1, R-squared = 0.83 and adjusted R-squared = 0.82, averaged across the different growth parameters.Different kinetin levels elicited the maximum shoot, leaf and root formation, as well as the growth rates over time. Moderate kinetinlevels （2-4 μM） provided better growth at early culturing period. Higher kinetin levels （5-10 μM） suppressed the growth of theplantlets at early stages, but the plantlets recovered from the stress and resumed normal growth thereafter. After 4-5 weeks, thegrowth rates of the moderate kinetin levels （2-4 μM） declined much faster and were lower compared to the higher kinetin levels,except plant height and the number of roots which were still higher at the moderate kinetin level even after eight weeks of culturing.Thus, kinetin requirements vary depending on the growth parameters of interest.

Fruit cracking and firmness DNA test development and evaluation in sweet cherry

One application of DNA-informed breeding,which has potential to increase the effectiveness of traditional breeding methods,is the use of DNAbased diagnostic tests to estimate genetic potential of breeding individuals.In sweet cherry(Prunus avium L.),cracked or soft fruit are major industry challenges.Recent research detected two quantitative trait loci(QTLs)for fruit cracking and firmness differing in trait levels associated with QTL haplotypic variation.Also,a DNA test for cracking(Pav-G5Crack-SSR),using two simple sequence repeat(SSR)markers,was previously developed but not yet validated on breeding germplasm.In addition to SSR markers,single nucleotide polymorphism(SNP)markers can be used for developing locus-specific DNA tests and run as simple assays such as high-resolution melting(HRM).The objective of this research was to develop and evaluate the predictiveness of DNA tests for fruit cracking and firmness in sweet cherry.Unselected seedlings from pedigreeconnected families were screened with the Pav-G5Crack-SSR DNA test.DNA tests were also created from four SNP markers with HRM assays,using two years of cracking and firmness data for evaluation.Pav-G5Crack-SSR explained 12–15%of the cracking phenotypic variance,while Pav-G1Crack-SNP and Pav-G5Crack-SNP(which targeted the same QTL as Pav-G5Crack-SSR)together explained 16%–30%of the cracking phenotypic variance.Pav-G1Firm-SNP and Pav-G3Firm-SNP together explained 22%–28%of the firmness phenotypic variance.All three DNA tests can be implemented in breeding programs to enhance effectiveness in breeding for decreased cracking incidence and increased fruit firmness in sweet cherry.

Genome Assembly of Alfalfa Cultivar Zhongmu-4 and Identification of SNPs Associated with Agronomic Traits

Alfalfa(Medicago sativa L.)is the most important legume forage crop worldwide with high nutritional value and yield.For a long time,the breeding of alfalfa was hampered by lacking reliable information on the autotetraploid genome and molecular markers linked to important agronomic traits.We herein reported the de novo assembly of the allele-aware chromosome-level genome of Zhongmu-4,a cultivar widely cultivated in China,and a comprehensive database of genomic variations based on resequencing of 220 germplasms.Approximate 2.74 Gb contigs(N50 of 2.06 Mb),accounting for 88.39%of the estimated genome,were assembled,and 2.56 Gb contigs were anchored to 32 pseudo-chromosomes.A total of 34,922 allelic genes were identified from the allele-aware genome.We observed the expansion of gene families,especially those related to the nitrogen metabolism,and the increase of repetitive elements including transposable elements,which probably resulted in the increase of Zhongmu-4 genome compared with Medicago truncatula.Population structure analysis revealed that the accessions from Asia and South America had relatively lower genetic diversity than those from Europe,suggesting that geography may influence alfalfa genetic divergence during local adaption.Genome-wide association studies identified 101 single nucleotide polymorphisms(SNPs)associated with 27 agronomic traits.Two candidate genes were predicted to be correlated with fall dormancy and salt response.We believe that the alleleaware chromosome-level genome sequence of Zhongmu-4 combined with the resequencing data of the diverse alfalfa germplasms will facilitate genetic research and genomics-assisted breeding in variety improvement of alfalfa.

Genetics-inspired data-driven approaches explain and predict crop performance fluctuations attributed to changing climatic conditions

Dear Editor,Genetics-focused approaches have been widely used to uncover major genetic variants associated with performance variation.Selecting,manipulating,and editing genetic variants significantly improve crop performance.Meanwhile,the genetic component explains a portion of performance variation,and the environ-mental component contributes to the remaining,often large,portion(Laidig et al.,2017;Bonecke et al.,2020;Li et al.,2021).To ensure superior and robust performance,elite varieties are extensively tested across multiple years and locations.These extensive performance records,coupled with climatic profiles,could be leveraged to understand climate's impact on agriculture through approaches parallel to quantitative genetics approaches(Figure 1A).

A Comprehensive Review of High Throughput Phenotyping and Machine Learning for Plant Stress Phenotyping

During the last decade,there has been rapid adoption of ground and aerial platforms with multiple sensors for phenotyping various biotic and abiotic stresses throughout the developmental stages of the crop plant.High throughput phenotyping(HTP)involves the application of these tools to phenotype the plants and can vary from ground-based imaging to aerial phenotyping to remote sensing.Adoption of these HTP tools has tried to reduce the phenotyping bottleneck in breeding programs and help to increase the pace of genetic gain.More specifically,several root phenotyping tools are discussed to study the plant’s hidden half and an area long neglected.However,the use of these HTP technologies produces big data sets that impede the inference from those datasets.Machine learning and deep learning provide an alternative opportunity for the extraction of useful information for making conclusions.These are interdisciplinary approaches for data analysis using probability,statistics,classification,regression,decision theory,data visualization,and neural networks to relate information extracted with the phenotypes obtained.These techniques use feature extraction,identification,classification,and prediction criteria to identify pertinent data for use in plant breeding and pathology activities.This review focuses on the recent findings where machine learning and deep learning approaches have been used for plant stress phenotyping with data being collected using various HTP platforms.We have provided a comprehensive overview of different machine learning and deep learning tools available with their potential advantages and pitfalls.Overall,this review provides an avenue for studying various HTP platforms with particular emphasis on using the machine learning and deep learning tools for drawing legitimate conclusions.Finally,we propose the conceptual challenges being faced and provide insights on future perspectives for managing those issues.

Effects of arbuscular mycorrhizal fungi,biochar,selenium,silica gel,and sulfur on arsenic uptake and biomass growth in Pisum sativum L.

Arsenic(As)is carcinogenic and highly toxic to plants.Crops accumulate As when grown in field soils irrigated with As-contaminated groundwater.The accumulation of As in roots,shoots,and grains of pea varieties can negatively affect human health via the food chain.This research is focused on the biomass growth and alleviation of As accumulation in roots,shoots,and grains of pea varieties in high As soil amended with arbuscular mycorrhizal fungi(AMF),biochar(BC),selenium(Se),silica gel(Si-gel),and sulfur(S).Root,shoot,and grain masses were found higher in pea grown in As soil amended with AMF,Se,Si-gel,and S.Amendments with rice husk and sawdust BC was found less effective to increase growth parameters in Bangladesh Agricultural Research Institute(BARI)Motor 2.Arsenic in grains was reduced by 77%,71%,and 69%by AMF,Se,and Si-gel,respectively.It is recommended that soil amendments with AMF,S,and Se have great potential for improving biomass production of pea grown in As-contaminated soil,as well as reducing As transfer to humans through the food chains.

Streamline unsupervised machine learning to survey and graph indel-based haplotypes from pan-genomes

Dear Editor,Pan-genomes with high quality de novo assemblies are shifting the paradigm of biology research in genome evolution,speciation,and function annotation(Shi et al.,2023).An all-vs.-all comparison across assemblies potentially overcomes the limitation of mapping short reads to a single assembly in cataloging polymorphisms,especially large insertions and deletions(indels)contributing to phenotypic variations through altering gene structure or expression(Chen et al.,2021).

GAPIT Version 3: Boosting Power and Accuracy for Genomic Association and Prediction

Genome-wide association study(GWAS)and genomic prediction/selection(GP/GS)are the two essential enterprises in genomic research.Due to the great magnitude and complexity of genomic and phenotypic data,analytical methods and their associated software packages are frequently advanced.GAPIT is a widely-used genomic association and prediction integrated tool as an R package.The first version was released to the public in 2012 with the implementation of the general linear model(GLM),mixed linear model(MLM),compressed MLM(CMLM),and genomic best linear unbiased prediction(g BLUP).The second version was released in 2016 with several new implementations,including enriched CMLM(ECMLM)and settlement of MLMs under progressively exclusive relationship(SUPER).All the GWAS methods are based on the single-locus test.For the first time,in the current release of GAPIT,version 3 implemented three multi-locus test methods,including multiple loci mixed model(MLMM),fixed and random model circulating probability unification(Farm CPU),and Bayesian-information and linkage-disequilibrium iteratively nested keyway(BLINK).Additionally,two GP/GS methods were implemented based on CMLM(named compressed BLUP;c BLUP)and SUPER(named SUPER BLUP;s BLUP).These new implementations not only boost statistical power for GWAS and prediction accuracy for GP/GS,but also improve computing speed and increase the capacity to analyze big genomic data.Here,we document the current upgrade of GAPIT by describing the selection of the recently developed methods,their implementations,and potential impact.All documents,including source code,user manual,demo data,and tutorials,are freely available at the GAPIT website(http://zzlab.net/GAPIT).

rMVP: A Memory-efficient, Visualization-enhanced, and Parallel-accelerated Tool for Genome-wide Association Study

Along with the develoipment of high-throughput sequencing technologies,both sample size and SNP number are increasing rapidly in genome-wide association studies(GWAS),and the associated computation is more challenging than ever.Here,we present a memory-efficient,visualization-enhanced,and parallel-accelerated R package called“r MVP”to address the need for improved GWAS computation.r MVP can 1)effectively process large GWAS data,2)rapidly evaluate population structure,3)efficiently estimate variance components by Efficient Mixed-Model Association e Xpedited(EMMAX),Factored Spectrally Transformed Linear Mixed Models(Fa ST-LMM),and Haseman-Elston(HE)regression algorithms,4)implement parallel-accelerated association tests of markers using general linear model(GLM),mixed linear model(MLM),and fixed and random model circulating probability unification(Farm CPU)methods,5)compute fast with a globally efficient design in the GWAS processes,and 6)generate various visualizations of GWASrelated information.Accelerated by block matrix multiplication strategy and multiple threads,the association test methods embedded in r MVP are significantly faster than PLINK,GEMMA,and Farm CPU_pkg.r MVP is freely available at https://github.com/xiaolei-lab/r MVP.

HP30-2, a mitochondrial PRAT protein for import of signal sequence-less precursor proteins in Arabidopsis thaliana

Chloroplasts and mitochondria contain a family of putative preprotein and amino acid transporters designated PRAT. Here, we analyzed the role of two previously characterized PRAT protein family members, encoded by At3g49560 （HP30） and At5g24650 （HP30-2）, in planta using a combination of genetic, cell biological and biochemical approaches. Expression studies and green fluorescent protein tagging identified HP30-2 both in chloroplasts and mitochondria, whereas HP30 was located exclusively in chloroplasts. Biochemical evidence was obtained for an association of mitochondrial HP30-2 with two distinct protein complexes, one containing the inner membrane translocase TIM22 and the other containing an alternative NAD（P）H dehydrogenase subunit （NDCI） implicated in a respiratory complex 1-1ike electron trans- port chain. Through its association with TIM22, HP30-2 is involved in the uptake of carrier proteins and other, hydrophobic membrane proteins lacking cleavable N H2-terminal presequences, whereas HP30-2＇s interaction with NDC1 may permit controlling mitochondrial biogenesis and activity.