Digital descriptors sharpen classical descriptors, for improving genebank accession management: A case study on Arachis spp. and Phaseolus spp.

High-throughput phenotyping brings new opportunities for detailed genebank accessions characterization based on image-processing techniques and data analysis using machine learning algorithms. Our work proposes to improve the characterization processes of bean and peanut accessions in the CIAT genebank through the identification of phenomic descriptors comparable to classical descriptors including methodology integration into the genebank workflow. To cope with these goals morphometrics and colorimetry traits of 14 bean and 16 forage peanut accessions were determined and compared to the classical International Board for Plant Genetic Resources (IBPGR) descriptors. Descriptors discriminating most accessions were identified using a random forest algorithm. The most-valuable classification descriptors for peanuts were 100-seed weight and days to flowering, and for beans, days to flowering and primary seed color. The combination of phenomic and classical descriptors increased the accuracy of the classification of Phaseolus and Arachis accessions. Functional diversity indices are recommended to genebank curators to evaluate phenotypic variability to identify accessions with unique traits or identify accessions that represent the greatest phenotypic variation of the species (functional agrobiodiversity collections). The artificial intelligence algorithms are capable of characterizing accessions which reduces costs generated by additional phenotyping. Even though deep analysis of data requires new skills, associating genetic, morphological and ecogeographic diversity is giving us an opportunity to establish unique functional agrobiodiversity collections with new potential traits.

LysipheN: a gravimetric IoT device for near real-time high-frequency crop phenotyping: a case study on common beans.

Climate instability directly affects agro-environments. Water scarcity, high air temperature, and changes in soil biota are some factors caused by environmental changes. Verified and precise phenotypic traits are required for assessing the impact of various stress factors on crop performance while keeping phenotyping costs at a reasonable level. Experiments which use a lysimeter method to measure transpiration efficiency are often expensive and require complex infrastructures. This study presents the development and testing process of an automated, reliable, small, and low-cost prototype system using IoT with high-frequency potential in near-real time. Because of its waterproofness, our device-LysipheN-assesses each plant individually and can be deployed for experiments in different environmental conditions (farm, field, greenhouse, etc.). LysipheN integrates multiple sensors, automatic irrigation according to desired drought scenarios, and a remote, wireless connection to monitor each plant and device performance via a data platform. During testing, LysipheN proved to be sensitive enough to detect and measure plant transpiration, from early to ultimate plant developmental stages. Even though the results were generated on common beans, the LysipheN can be scaled up/adapted to other crops. This tool serves to screen transpiration, transpiration efficiency, and transpiration-related physiological traits. Because of its price, endurance, and waterproof design, LysipheN will be useful in screening populations in a realistic ecological and breeding context. It operates by phenotyping the most suitable parental lines, characterizing genebank accessions, and allowing breeders to make a target-specific selection using functional traits (related to the place where LysipheN units are located) in line with a realistic agronomic background.

Using phenomics to identify and integrate traits of interest for better-performing common beans: A validation study on an interspecific hybrid and its Acutifolii parents.

Introduction: Evaluations of interspecific hybrids are limited, as classical genebank accession descriptors are semi-subjective, have qualitative traits and show complications when evaluating intermediate accessions. However, descriptors can be quantified using recognized phenomic traits. This digitalization can identify phenomic traits which correspond to the percentage of parental descriptors remaining expressed/visible/measurable in the particular interspecific hybrid. In this study, a line of P. vulgaris, P. acutifolius and P. parvifolius accessions and their crosses were sown in the mesh house according to CIAT seed regeneration procedures. Methodology: Three accessions and one derived breeding line originating from their interspecific crosses were characterized and classified by selected phenomic descriptors using multivariate and machine learning techniques. The phenomic proportions of the interspecific hybrid (line INB 47) with respect to its three parent accessions were determined using a random forest and a respective confusion matrix. Results: The seed and pod morphometric traits, physiological behavior and yield performance were evaluated. In the classification of the accession, the phenomic descriptors with highest prediction force were Fm', Fo', Fs', LTD, Chl, seed area, seed height, seed Major, seed MinFeret, seed Minor, pod AR, pod Feret, pod round, pod solidity, pod area, pod major, pod seed weight and pod weight. Physiological traits measured in the interspecific hybrid present 2.2% similarity with the P. acutifolius and 1% with the P. parvifolius accessions. In addition, in seed morphometric characteristics, the hybrid showed 4.5% similarity with the P. acutifolius accession. Conclusions: Here we were able to determine the phenomic proportions of individual parents in their interspecific hybrid accession. After some careful generalization the methodology can be used to: i) verify trait-of-interest transfer from P. acutifolius and P. parvifolius accessions into their hybrids; ii) confirm selected traits as "phenomic markers" which would allow conserving desired physiological traits of exotic parental accessions, without losing key seed characteristics from elite common bean accessions; and iii) propose a quantitative tool that helps genebank curators and breeders to make better-informed decisions based on quantitative analysis.

In pursuit of a better world: crop improvement and the CGIAR.

The CGIAR crop improvement (CI) programs, unlike commercial CI programs, which are mainly geared to profit though meeting farmers' needs, are charged with meeting multiple objectives with target populations that include both farmers and the community at large. We compiled the opinions from >30 experts in the private and public sector on key strategies, methodologies, and activities that could the help CGIAR meet the challenges of providing farmers with improved varieties while simultaneously meeting the goals of: (i) nutrition, health, and food security; (ii) poverty reduction, livelihoods, and jobs; (iii) gender equality, youth, and inclusion; (iv) climate adaptation and mitigation; and (v) environmental health and biodiversity. We review the crop improvement processes starting with crop choice, moving through to breeding objectives, production of potential new varieties, selection, and finally adoption by farmers. The importance of multidisciplinary teams working towards common objectives is stressed as a key factor to success. The role of the distinct disciplines, actors, and their interactions throughout the process from crop choice through to adoption by farmers is discussed and illustrated.

Proteomic and physiological approach reveals drought-induced changes in rapeseeds: Water-saver and water-spender strategy.

The cultivar-dependent differences in Brassica napus L. seed yield are significantly affected by drought stress. Here, the response of leaf proteome to long-term drought (28days) was studied in cultivars (cvs): Californium (C), Cadeli (D), Navajo (N), and Viking (V). Analysis of twenty-four 2-D DIGE gels revealed 134 spots quantitatively changed at least 2-fold; from these, 79 proteins were significantly identified by MALDI-TOF/TOF. According to the differences in water use, the cultivars may be assigned to two categories: water-savers or water-spenders. In the water-savers group (cvs C+D), proteins related to nitrogen assimilation, ATP and redox homeostasis were increased under stress, while in the water-spenders category (cvs N+V), carbohydrate/energy, photosynthesis, stress related and rRNA processing proteins were increased upon stress. Taking all data together, we indicated cv C as a drought-adaptable water-saver, cv D as a medium-adaptable water-saver, cv N as a drought-adaptable water-spender, and cv V as a low-adaptable drought sensitive water-spender rapeseed. Proteomic data help to evaluate the impact of drought and the extent of genotype-based adaptability and contribute to the understanding of their plasticity. These results provide new insights into the provenience-based drought acclimation/adaptation strategy of contrasting winter rapeseeds and link data at gasometric, biochemical, and proteome level. SIGNIFICANCE: Soil moisture deficit is a real problem for every crop. The data in this study demonstrates for the first time that in stem-prolongation phase cultivars respond to progressive drought in different ways and at different levels. Analysis of physiological and proteomic data showed two different water regime-related strategies: water-savers and spenders. However, not only water uptake rate itself, but also individual protein abundances, gasometric and biochemical parameters together with final biomass accumulation after stress explained genotype-based responses. Interestingly, under a mixed climate profile, both water-use patterns (savers or spenders) can be appropriate for drought adaptation. These data suggest, than complete "acclimation image" of rapeseeds in stem-prolongation phase under drought could be reached only if these characteristics are taken, explained and understood together.

Biological Networks Underlying Abiotic Stress Tolerance in Temperate Crops--A Proteomic Perspective.

Abiotic stress factors, especially low temperatures, drought, and salinity, represent the major constraints limiting agricultural production in temperate climate. Under the conditions of global climate change, the risk of damaging effects of abiotic stresses on crop production increases. Plant stress response represents an active process aimed at an establishment of novel homeostasis under altered environmental conditions. Proteins play a crucial role in plant stress response since they are directly involved in shaping the final phenotype. In the review, results of proteomic studies focused on stress response of major crops grown in temperate climate including cereals: common wheat (Triticum aestivum), durum wheat (Triticum durum), barley (Hordeum vulgare), maize (Zea mays); leguminous plants: alfalfa (Medicago sativa), soybean (Glycine max), common bean (Phaseolus vulgaris), pea (Pisum sativum); oilseed rape (Brassica napus); potato (Solanum tuberosum); tobacco (Nicotiana tabaccum); tomato (Lycopersicon esculentum); and others, to a wide range of abiotic stresses (cold, drought, salinity, heat, imbalances in mineral nutrition and heavy metals) are summarized. The dynamics of changes in various protein functional groups including signaling and regulatory proteins, transcription factors, proteins involved in protein metabolism, amino acid metabolism, metabolism of several stress-related compounds, proteins with chaperone and protective functions as well as structural proteins (cell wall components, cytoskeleton) are briefly overviewed. Attention is paid to the differences found between differentially tolerant genotypes. In addition, proteomic studies aimed at proteomic investigation of multiple stress factors are discussed. In conclusion, contribution of proteomic studies to understanding the complexity of crop response to abiotic stresses as well as possibilities to identify and utilize protein markers in crop breeding processes are discussed.

Significant relationships among frost tolerance and net photosynthetic rate, water use efficiency and dehydrin accumulation in cold-treated winter oilseed rapes.

Five winter oilseed rape cultivars (Benefit, Californium, Cortes, Ladoga, Navajo) were subjected to 30 days of cold treatment (4 °C) to examine the effect of cold on acquired frost tolerance (FT), dehydrin (DHN) content, and photosynthesis-related parameters. The main aim of this study was to determine whether there are relationships between FT (expressed as LT50 values) and the other parameters measured in the cultivars. While the cultivar Benefit accumulated two types of DHNs (D45 and D35), the other cultivars accumulated three additional DHNs (D97, D47, and D37). The similar-sized DHNs (D45 and D47) were the most abundant; the others exhibited significantly lower accumulations. The highest correlations were detected between LT50 and DHN accumulation (r=-0.815), intrinsic water use efficiency (WUEi; r=-0.643), net photosynthetic rate (r=-0.628), stomatal conductance (r=0.511), and intracellular/intercellular CO2 concentration (r=0.505). Those cultivars that exhibited higher Pn rate in cold (and further a significant increase in WUEi) had higher levels of DHNs and also higher FT. No significant correlation was observed between LT50 and E, PRI, or NDVI. Overall, we have shown the selected physiological parameters to be able to distinguish different FT cultivars of winter oilseed rape.