Speed Breeding to Accelerate Crop Improvement

Speed breeding through controlled environments as a new technique on the block offers advantages over conventional field-based generation advancement methods. Physiological parameters, especially light, is altered to induce early flowering to reduce generation time. Germinating immature seeds will reduce the generation time further. Several experiments were conducted in the past and are being conducted to develop speed breeding protocols for many crops. Speed breeding protocols were standardized for some crops, for example, chickpea, that allow six to seven generations per year as opposed to two to three earlier. Besides being faster, speed breeding enables savings on resources as advancing generations is cheaper through speed breeding as compared to field experiments. Rapid generation advancement through speed breeding integrated with the advanced techniques of genomic tools, gene editing, early- and high-throughput phenotyping, rapid population development, etc. would boost the genetic analysis and increase the rate of genetic gain in the cultivar development of the crop plants. In the backdrop of increasing food and nutrition demands, gains in crop improvement need to be increased. Speed breeding offers one of the feasible ways to achieve this. The costs involved may pose an obstacle to many enthusiasts, but cheaper alternatives can be explored. Integrating artificial intelligence with speed breeding makes it more valuable in crop improvement programs

Linking of Genebank to Breeding and Food Security

Genebanks have the responsibility of collecting, maintaining, characterizing, evaluating, documenting and distributing plant genetic resources for research, education and breeding purposes globally. About 7.4 million germplasm accessions are conserved ex situ in the genebanks globally. Efficient use of germplasm in crop improvement is depending on the availability of accession-level information on the traits of interest. For the majority of accessions, only basic passport and characterization data are available, while data on unique traits is generally lacking that limits their utilization in crop improvement. Development of germplasm diversity and trait-specific subsets enhanced availability of accessions-level information. Researchers can search in the global plant genetic resources database called Genesys PGR which contains passport data, characterization and evaluation data sets and trait-specific subsets developed on various crops (https://www.genesys-pgr.org/). The impact of germplasm for contributing to increased yield, adaptation, nutrition and improved health and sustainable agriculture has been demonstrated in many crops. There are many instances where a single plant genetic resource has proved to have large commercial value by conferring a specific trait. With the availability of new technologies such as high-throughput large-scale phenotypic assessment for key traits and use of multi-omic tools could accelerate rapid identification of traits and genes for breeding improved cultivars. This chapter details about ex situ germplasm conservation, discovering climate resilient germplasm following different approaches such as diversity and trait-specific subsets, focused germplasm identification strategy, molecular characterization of germplasm and trait discovery, access to germplasm and the impact of genebank contributing to the global agriculture sustainability

Large-Scale Mapping of Soil Quality Index in Different Land Uses Using Airborne Hyperspectral Data

Large-scale mapping of soil quality index (SQI) is a challenging task because of the cost and time involved in measuring required soil parameters through conventional wet chemistry-based methods. Hyperspectral remote sensing (HRS) may be used to overcome such a challenge. We hypothesize that soil quality at a specific location may be estimated from remotely sensed reflectance spectra because both these attributes are composite parameters. We used the HRS data collected with the Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) sensor to estimate SQIs in an agricultural catchment. SQIs were developed from 16 different soil properties measured at 101 locations coinciding AVIRIS-NG flight. Chemometric models were used to estimate SQIs from spectral reflectance data collected under laboratory conditions and those processed from AVIRIS-NG data before and after linear and nonlinear unmixing. Except for the linearly unmixed AVIRIS-NG data, three other spectral data sources yielded coefficient of determination ( R2 ) values exceeding 0.7. Specifically, the R2 values for the mixed and nonlinearly unmixed spectra were 0.71 and 0.72, respectively, suggesting that HRS approach may directly be used for estimating SQIs. With high validation statistics, we converted the AVIRIS-NG imagery to SQI map for the entire catchment. Such high spatial resolution maps allowed us to examine the effects of land use/cover on soil quality. Strong linear dependencies between SQI and land uses and terrain structures suggested that HRS-derived SQI maps may be used to prioritize soil management efforts for sustainable development

High-density bin-based genetic map reveals a 530-kb chromosome segment derived from wild peanut contributing to late leaf spot resistance

Late leaf spot (LLS) is one of the major foliar diseases of peanut, causing serious yield loss and affecting the quality of kernel and forage. Some wild Arachis species possess higher resistance to LLS as compared with cultivated peanut; however, ploidy level differences restrict utilization of wild species. In this study, a synthetic amphidiploid (Ipadur) of wild peanuts with high LLS resistance was used to cross with Tifrunner to construct TI population. In total, 200 recombinant inbred lines were collected for whole-genome resequencing. A high-density bin-based genetic linkage map was constructed, which includes 4,809 bin markers with an average inter-bin distance of 0.43 cM. The recombination across cultivated and wild species was unevenly distributed, providing a novel recombination landscape for cultivated-wild Arachis species. Using phenotyping data collected across three environments, 28 QTLs for LLS disease resistance were identified, explaining 4.35–20.42% of phenotypic variation. The major QTL located on chromosome 14, qLLS14.1, could be consistently detected in 2021 Jiyang and 2022 Henan with 20.42% and 12.12% PVE, respectively. A favorable 530-kb chromosome segment derived from Ipadur was identified in the region of qLLS14.1, in which 23 disease resistance proteins were located and six of them showed significant sequence variations between Tifrunner and Ipadur. Allelic variation analysis indicating the 530-kb segment of wild species might contribute to the disease resistance of LLS. These associate genomic regions and candidate resistance genes are of great significance for peanut breeding programs for bringing durable resistance through pyramiding such multiple LLS resistance loci into peanut cultivars

Applications of UAVs: Image-Based Plant Phenotyping

Plant phenotyping plays an important role in the qualitative and quantitative assessment of plant growth in its growth environment. Traditional data-collection process used in plant breeding applications is mostly manual, time-consuming, labor-intensive, and highly subjective. Recent advancements in imaging sensors and platforms have significantly enhanced the speed and precision of image-based automated high-throughput plant phenotyping (HTPP). Current automated HTPP is mostly done in controlled environment where the plants are moved to phenotyping platforms. Such technologies are not feasible for open-field phenotyping. Satellite-based remote sensing has been used from decades but is not much effective in small-scale field phenotyping. Nowadays, satellite imagery with good resolution of up to few centimeters (~10–50 cm) is available, but due to fixed revisit time its temporal resolution is still limited. For crops’ trait estimation, high spatial, spectral, and temporal resolutions are mandatory. On the other hand, unmanned aerial vehicle (UAV)-drone-assisted image-based HTPP is current state-of-the-art for open-field phenotyping, and is known for providing data with high spatiotemporal resolution, with wide coverage in shorter duration. UAV (drone)-assisted HTPP is used in quantitative phenotyping for traits like plant height, biomass, and leaf area index, and qualitative phenotyping for traits like leaf nitrogen content; it is also used in biotic and abiotic stress quantification in plants. As of now the UAVs (drones) are popular for scouting and pesticide spraying in open field. The use of UAVs (drones) for phenotyping is a newer research area that is not matured enough till date. The main objective of this chapter is to explore the use of UAVs (drones) with different types of sensors mounted on it, for lean field phenotyping so that it will be used to assist the breeders in speeding up the selective breeding process using image-based HTPP with high precision and accuracy

Genetic Identification and Characterisation of Crop Agronomic Traits and Stress Resistance

Enhancing crops’ agronomic traits and resilience to stress is crucial for promoting food security and sustainable agriculture, particularly during climate change and for the growing global population. Genetic identification and characterisation are pivotal for comprehending the mechanisms underlying these traits and crops’ responses to stress. Various genetic tools and methodologies, such as quantitative trait locus (QTL) mapping, genomewide association studies (GWAS), marker-assisted selection (MAS), genomic selection (GS), and functional genomics techniques, like transcriptomics, proteomics, and metabolomics, have facilitated the recognition of crucial genomic regions associated with significant agronomic traits, like yield, quality, and resistance to both biotic and abiotic stresses. Hence, identifying leads for new genetic gains for crop breeding programs includes developing improved cultivars with heightened yield potential, enhanced nutritional quality, and resilience to stresses from pests and environmental factors. Leveraging genetic diversity through germplasm resources and molecular breeding strategies may be used to address these challenges

Identification and expression profile of dhurrin biosynthesis pathway genes in sorghum vegetative tissues

Sorghum is considered a fifth major cereal, widely used as a multipurpose crop worldwide. The use of sorghum as a major forage crop is limited due to cyanogenic glycoside dhurrin in the vegetative shoot tissues. This cyanogenic glycoside is harmful to livestock when fed as fodder. The present study selected three sorghum genotypes for estimating hydrogen cyanide potential (HCNp) in vegetative tissues under well-watered (WW) conditions. The HCNp concentration varied from genotype to genotype and ranged from 364 to 512 ppm. The HCNp estimation was observed more in ICSR 14001 with 511 ppm, followed by ICSV 93046 (443 ppm) and CSH 24 MF (364 ppm). A significant difference was noticed between the genotypes. Sequence information of dhurrin biosynthesis pathway genes was retrieved and characterized using different bioinformatic tools. The gene expression analysis of dhurrin biosynthesis pathway genes showed different expression patterns, with the highest in ICSV 93046 and less in ICSR 14001 and CSH 24 MF. Genes CYP79A1, CYP71E1 and UGT85B1 showed a 2.5- to 4 fold increase in ICSV 93046 and no significant expression in ICSR 14001 and CSH 24 MF. The genotype CSH 24 MF observed a 1.5-fold increase in CYP79A1 gene expression, and the other genes observed no significant increase. This study assisted in identifying the contrasting genotypes inducing HCNp and the key genes of the dhurrin pathway producing hydrogen cyanide (HCN) under WW conditions, which can be used as potential candidates for gene editing, providing safe feed for the livestock

On-farm evidence on breaking yield barriers through optimizing wheat cropping system in Indo Gangetic Plain

The wheat production in the food basket of South Asia has plateaued with threats of environmental sustainability and posing a serious challenge to future food security. For sustainable wheat production in conventional rice-wheat (CTRW) systems under changing climatic scenario, atwo-year on-farm study was conducted. We evaluated system optimization practices (SOP) of legume inclusion with CTR-zero-tillage (ZT) wheat-mungbean (CTR-ZTWMb) and direct seeded rice-ZT wheat-mungbean (DSR-ZTWMb) and triple ZT (raised bed) based futuristic systems of maize-wheat-mungbean (ZTMWMb) and soybean-wheat-mungbean (ZTSWMb). The global warming potential (GWP) of wheat production was significantly reduced by 811 kg CO2 eq/ha (783−861) in the SOP compared to CTRW. Moreover, the water usein wheat reduced by 85.9 and 85.2 ha-mm/ha in CTR-ZTWMb and DSR-ZTWMb with higher reduction in ZTMWMb and ZTSWMb by128.7 and 118.0 ha-mm/ha, respectively over CTRW. Similarly, the total weed density was reduced at 60 (39 and 52 %) and 90 (38 and 49 %) days after sowing with CTR-ZTWMb and DSR-ZTWMb over CTRW. However, the weed density reduction was lesser with ZTSWMb and ZTMWMb at 60 (3.0 and 23.6 %), and 90 (9.8 and 31.0 %) days after sowingcompared to the CTRW.The partial factor productivity (PFP) of NPK applied was 8.5–19.0 % higher under SOP over the CTRW. The use of non-renewable energy in wheat cultivation was reduced by 24.4–28.9 % with SOP over CTRW. The enhancement in wheat grain yield (7.4–11.8 %) and net returns (98–169 US$/ha) was also recorded with CTR-ZTWMb and DSR-ZTWMb and this gain in futuristic systems (ZTMWMb and ZTSWMb) was much higher in grain yield (17.2–21.0$/ha) over CTRW. The adoption of these SOPs on 1 million ha could produce 0.37–1.05 million t additional wheat over CTRW. The on-farm study evidenced thatwheat production with system optimization practices of legume inclusion and zero tillage are better alternatives to achieve higher productivity and profitability with a lesserenvironmental footprint in Indo-Gangetic Plains and similar agroecological regions

Screening pearl millet genotypes for resistance to Striga hermonthica and compatibility to Fusarium oxysporum f.sp. strigae

Pearl millet (Pennisetum glaucum [L.] R. Br., 2n = 2x = 14) is a nutritionally rich and climate-resilient food crop cultivated globally. It is a crucial staple crop in Burkina Faso and the dry Sahel region, encompassing Niger, Mali, and Senegal. However, the yield of pearl millet is relatively low in the region (<0.85 tons ha−1) due to Striga hermonthica (Sh) infestation, bird damage, insect pests, diseases, and low-yielding open-pollinated landrace varieties. The study aimed to screen genetically diverse pearl millet accessions for Sh resistance and compatibility to a Striga bio-control agent, Fusarium oxysporum f. sp. Strigae (FOS), to select contrasting and promising parents for resistance breeding and production. One hundred and fifty genotypes were evaluated in Sh hotspot fields in the rain-fed and greenhouse conditions using an alpha lattice design and two replications in Burkina Faso. Significant differences were recorded among the tested pearl millet genotypes for the assessed agro-morphological and Striga resistance. Days to flowering was significantly delayed in the assessed genotypes due to Sh infestation. Applying FOS on pearl millet seed significantly reduced the mean Striga number in Sh-infested conditions. The following genotypes: IP-3098, IP-6112, IP-9242, IP-10579, and IP-11358 were identified as exhibiting Sh resistance and were compatible to FOS. The pearl millet genotypes supported few to none Sh emerged plants with comparatively low values under the Striga number progress curve. The selected genotypes are useful parents to breed for Striga resistance and integrated management in Burkina Faso and related agroecologies

Nutritional status of Zombi pea (Vigna vexillata) as influenced by plant density and deblossoming

Feeding billions, a healthy and nutritious diet in the era of climate change is a major challenge before plant breeders, geneticists and agronomist. In this context, the continuous search for adaptive and nutritious crops could be a better alternative to combat the problems of hunger and malnutrition. The zombi pea, a nutritious and underutilized leguminous vegetable, is one of such better alternatives to feed billions a nutritious food besides being a potential gene source for breeding abiotic stress resistant varieties. To evaluate its potential as a wonder crop in the tropical and subtropical regions of India, the nutritional status of tubers, pods and pericarp were investigated under different treatments of plant spacings and deblossoming. The experiment was conducted in split plot design with three replications and eight treatments during 2021–2022 in the coastal regions of India. The nutrient profiling in tubers and pericarp of pods in zombi pea revealed higher accumulation of nutrients viz. potassium (K), magnesium (Mg), iron (Fe), manganese (Mn) and zinc (Zn) with blossom retention. The zombi pea tubers reflected significantly high protein accumulation with the increase in plant spacing. The results pertaining to nutrient profiling in the pods of zombi pea indicated that the plant spacing has no significant effect on the accumulation of majority of nutrients under study. The above-mentioned findings are conspicuously novel and valuable. The present study would pave the way for understanding nutritional importance and breeding potential of this orphan crop. The blossom retention renders higher nutrient accumulation in tubers, pods and pericarp of zombi pea. Deblossoming has no significant influence on nutritional profile of this wonder crop but, wider spacing is effective in producing tubers with high protein content