Plant breeding is a multidisciplinary applied science that is crucial for enhancing food, fodder, fuel, and fiber production globally. Using detailed surveys in three Organisation for Economic Co-operation and Development countries, this study investigated the current state of the plant breeding sector across tertiary, government, and industry levels. The findings highlight increasing concerns about the shortage of trained plant breeders, especially in the private sector, impacting food security and the economy. The need for a coordinated approach between the public and private sectors is emphasized. Suggestions for improvements include the establishment of dedicated training facilities, national funds for graduate fellowships, and increased private sector involvement in plant breeding education. The importance of adapting plant breeding courses to emerging scientific and technological advancements is highlighted, along with industry-relevant training and improved promotion of the sector. The study raises awareness of the global shortage of trained plant breeders and provides valuable insights for decision makers toward strategic planning to address global food and fiber production challenges.

Background Cotton accounts for 80% of the global natural fibre production. Its leaf hairiness affects insect resistance, fibre yield, and economic value. However, this phenotype is still qualitatively assessed by visually attributing a Genotype Hairiness Score (GHS) to a leaf/plant, or by using the HairNet deep-learning model which also outputs a GHS. Here, we introduce HairNet2, a quantitative deep-learning model which detects leaf hairs (trichomes) from images and outputs a segmentation mask and a Leaf Trichome Score (LTS). Results Trichomes of 1250 images were annotated (AnnCoT) and a combination of six Feature Extractor modules and five Segmentation modules were tested alongside a range of loss functions and data augmentation techniques. HairNet2 was further validated on the dataset used to build HairNet (CotLeaf-1), a similar dataset collected in two subsequent seasons (CotLeaf-2), and a dataset collected on two genetically diverse populations (CotLeaf-X). The main findings of this study are that (1) leaf number, environment and image position did not significantly affect results, (2) although GHS and LTS mostly correlated for individual GHS classes, results at the genotype level revealed a strong LTS heterogeneity within a given GHS class, (3) LTS correlated strongly with expert scoring of individual images. Conclusions HairNet2 is the first quantitative and scalable deep-learning model able to measure leaf hairiness. Results obtained with HairNet2 concur with the qualitative values used by breeders at both extremes of the scale (GHS 1-2, and 5-5+), but interestingly suggest a reordering of genotypes with intermediate values (GHS 3-4+). Finely ranking mild phenotypes is a difficult task for humans. In addition to providing assistance with this task, HairNet2 opens the door to selecting plants with specific leaf hairiness characteristics which may be associated with other beneficial traits to deliver better varieties.

Cotton is a key global fiber crop. However, yield potential is limited by the presence of endemic and introduced pests and diseases. The introduction of host plant resistance (HPR), defined as the purposeful use of resistant crop cultivars to reduce the impact of pests and diseases, has been a key breeding target for the Commonwealth Scientific and Industrial Research Organisation (CSIRO) cotton breeding program. The program has seen success in releasing cultivars resistant to Bacterial blight, Verticillium wilt, Fusarium wilt, and Cotton bunchy top. However, emerging biotic threats such as Black root rot and secondary pests, are becoming more frequent in Australian cotton production systems. The uptake of tools and breeding methods, such as genomic selection, high throughput phenomics, gene editing, and landscape genomics, paired with the continued utilization of sources of resistance from Gossypium germplasm, will be critical for the future of cotton breeding. This review celebrates the success of HPR breeding activities in the CSIRO cotton breeding program and maps a pathway for the future in developing resistant cultivars.

Global plant breeding activities are reliant on the available genetic variation held in extant varieties and germplasm collections. Throughout the mid- to late 1900s, germplasm collecting efforts were prioritized for breeding programs to archive precious material before it disappeared and led to the development of the numerous large germplasm resources now available in different countries. In recent decades, however, the maintenance and particularly the expansion of these germplasm resources have come under threat, and there has been a significant decline in investment in further collecting expeditions, an increase in global biosecurity restrictions, and restrictions placed on the open exchange of some commercial germplasm between breeders. The large size of most genebank collections, as well as constraints surrounding the availability and reliability of accurate germplasm passport data and physical or genetic characterization of the accessions in collections, limits germplasm utilization by plant breeders. To overcome these constraints, core collections, defined as a representative subset of the total germplasm collection, have gained popularity. Core collections aim to increase germplasm utilization by containing highly characterized germplasm that attempts to capture the majority of the variation in a whole collection. With the recent availability of many new genetic tools, the potential to unlock the value of these resources can now be realized. The Commonwealth Scientific and Industrial Research Organisation (CSIRO) cotton breeding program supplies 100% of the cotton cultivars grown in Australia. The program is reliant on the use of plant genetic resources for the development of improved cotton varieties to address emerging challenges in pest and disease resistance as well as the global changes occurring in the climate. Currently, the CSIRO germplasm collection is actively maintained but underutilized by plant breeders. This review presents an overview of the Australian cotton germplasm resources and discusses the appropriateness of a core collection for cotton breeding programs.

The yield of a pasture is directly proportional to the amount of light plants intercept and allocate to different organs. When plants are carbon (C) limited, due to defoliation, they allocate more C preferentially to shoots to restore leaf area. In contrast, water and nitrogen (N) limitations lead to a greater allocation of C to roots. Changes in the root:shoot ratio therefore reflect changes in C and N partitioning and indicate their relative priority. A major factor that influences plant responses to stress is their ability to store and remobilise reserves to restore leaf area. Species with tap roots, like lucerne, have a large potential C and N storage capacity that is utilised seasonally for storage and remobilisation. This has been used to develop seasonally based grazing management rules. Similarly, recommendations to graze perennial ryegrass at the 2- or 3-leaf stage are based on the balance between maximizing growth rates and the need to replenish water-soluble carbohydrate reserves. However, perennial ryegrass has lower levels of perennial reserves than other grass species. This reduces its resilience to concurrent water deficits or N deficiency. Under these conditions maintaining the recommended 3-leaf grazing intervals and/or leaving higher post-grazing pasture masses are recommended to assist canopy recovery. Other grass species, such as cocksfoot and tall fescue, provide more resilience, particularly in response to water deficits.

Trifolium is the most used pastoral legume genus in temperate grassland systems, and a common feature in meadows and open space areas in cities and parks. Breeding of Trifolium spp. for pastoral production has been going on for over a century. However, the breeding targets have changed over the decades in response to different environmental and production pressures. Relatively small gains have been made in Trifolium breeding progress. Trifolium breeding programmes aim to maintain a broad genetic base to maximise variation. New Zealand is a global hub in Trifolium breeding, utilising exotic germplasm imported by the Margot Forde Germplasm Centre. This article describes the history of Trifolium breeding in New Zealand as well as the role and past successes of utilising genebanks in forage breeding. The impact of germplasm characterisation and evaluation in breeding programmes is also discussed. The history and challenges of Trifolium breeding and its effect on genetic gain can be used to inform future pre-breeding decisions in this genus, as well as being a model for other forage legumes.

Determining the performance of white clover cultivars under drought conditions is critical in dry climates. However, comparing the differences in cultivar performance requires equivalent soil water content for all plants, to reduce the water deficit threshold eliciting stomatal closure. In this study, the objective was to compare the rate of stomatal closure in eighty white clover cultivars in response to soil drying. Two glasshouse experiments were conducted, and the daily transpiration rate was measured by weighing each pot. The transpiration rate of the drought-stressed plants were normalized against the control plants to minimize effects from transpiration fluctuations and was recorded as the normalized transpiration rate (NTR). The daily soil water content was expressed as the fraction of transpirable soil water (FTSW). The FTSW threshold (FTSWc) was estimated after which the NTR decreases linearly. The FTSWc marks the critical point where the stomata start to close, and transpiration decreases linearly. The significant difference (p < 0.05) between the 10 cultivars with the highest and lowest FTSWc demonstrates the cultivars would perform better in short- or long-term droughts.

Pedigree maps are useful for germplasm exploration and identification of genetic bottlenecks. The primary objective of this study was to construct pedigree maps for red clover ( Trifolium pratense L.) accessions held in the Margot Forde Germplasm Centre (MFGC) in Palmerston North, New Zealand. Pedigree data from accessions introduced into the MFGC between 1934 and 2016 were used. Data were filtered for accessions with breeding activity. A total of 30 founding accessions was identified, of which 25 were categorized as “New Zealand Broad,” two as “English Broad,” another two as “English Giant Hybrid,” and one as “Cotswold Broad.” The first synthetic form was identified from parents derived from English Broad and English Giant Hybrid. Influencing founder accessions were also identified. A relationship between introductions, relatedness, and geographic origin was found. The inbreeding and kinship coefficients were estimated across the population. The largest number of traced generations was eight. A total of 1742 accessions was used in the estimation of relatedness coefficients, with mean relatedness of 0.005. Overall mean inbreeding was 0.56%. Among the accessions with nonzero inbreeding coefficients, inbreeding was 10.68%. A sharp increase in inbreeding was found in the 1990s. Although inbreeding remained stable in the last three decades, a relationship between inbreeding and new introductions into the collection was found ( r = 0.62). We conclude red clover diversity has been successfully maintained at MFGC during the past 80 yr. However, risk in loss of diversity is present unless germplasm exploration techniques, such as pedigree analysis, and novel breeding patterns are undertaken.