Quality of cowpea seeds: A food security strategy in the tropical environment.

What is the relation between seed quality and food security? Here we built a summary diagram that links the development stages of the seeds with their potential of providing grain yield. This idea was tested using cowpea as a model crop, grown in a tropical environment. Initially, seed quality attributes such as water content, dry weight, germination, vigor, and longevity were characterized during seed development. With this, we were able to elucidate at which point the late maturation phase and the acquisition of seed with superior physiological quality starts. From these data, the proposed summary diagram highlighted the seed quality as a technological basis for generating a more productive plant community. It also showed that only seeds with a high-quality profile have a better chance to establishment in an increasingly challenging agricultural environment. Overall, we bring the concept that cowpea seeds with superior quality besides being the essential input for tropical agriculture is also a strategy that can contribute food security.

A Reliable Method to Recognize Soybean Seed Maturation Stages Based on Autofluorescence-Spectral Imaging Combined With Machine Learning Algorithms.

In recent years, technological innovations have allowed significant advances in the diagnosis of seed quality. Seeds with superior physiological quality are those with the highest level of physiological maturity and the integration of rapid and precise methods to separate them contributes to better performance in the field. Autofluorescence-spectral imaging is an innovative technique based on fluorescence signals from fluorophores present in seed tissues, which have biological implications for seed quality. Thus, through this technique, it would be possible to classify seeds in different maturation stages. To test this, we produced plants of a commercial cultivar (MG/BR 46 "Conquista") and collected the seeds at five reproductive (R) stages: R7.1 (beginning of maturity), R7.2 (mass maturity), R7.3 (seed disconnected from the mother plant), R8 (harvest point), and R9 (final maturity). Autofluorescence signals were extracted from images captured at different excitation/emission combinations. In parallel, we investigated physical parameters, germination, vigor and the dynamics of pigments in seeds from different maturation stages. To verify the accuracy in predicting the seed maturation stages based on autofluorescence-spectral imaging, we created machine learning models based on three algorithms: (i) random forest, (ii) neural network, and (iii) support vector machine. Here, we reported the unprecedented use of the autofluorescence-spectral technique to classify the maturation stages of soybean seeds, especially using the excitation/emission combination of chlorophyll a (660/700 nm) and b (405/600 nm). Taken together, the machine learning algorithms showed high performance segmenting the different stages of seed maturation. In summary, our results demonstrated that the maturation stages of soybean seeds have their autofluorescence-spectral identity in the wavelengths of chlorophylls, which allows the use of this technique as a marker of seed maturity and superior physiological quality.

Transcripts Expressed during Germination Sensu Stricto Are Associated with Vigor in Soybean Seeds.

The rapid and uniform establishment of crop plants in the field underpins food security through uniform mechanical crop harvesting. In order to achieve this, seeds with greater vigor should be used. Vigor is a component of physiological quality related to seed resilience. Despite this importance, there is little knowledge of the association between events at the molecular level and seed vigor. In this study, we investigated the relationship between gene expression during germination and seed vigor in soybean. The expression level of twenty genes related to growth at the beginning of the germination process was correlated with vigor. In this paper, vigor was evaluated by different tests. Then we reported the identification of the genes Expansin-like A1, Xyloglucan endotransglucosylase/hydrolase 22, 65-kDa microtubule-associated protein, Xyloglucan endotransglucosylase/hydrolase 2, N-glycosylase/DNA lyase OGG1 and Cellulose synthase A catalytic subunit 2, which are expressed during germination, that correlated with several vigor tests commonly used in routine analysis of soybean seed quality. The identification of these transcripts provides tools to study vigor in soybean seeds at the molecular level.

Liming enhances longevity of wheat seeds produced in acid soils.

The environment where plants grow, such as acidic soils, interferes with the nutrient concentration and physiological quality of seeds. This hypothesis was tested using wheat seeds as a model crop, grown in a tropical soil with and without lime application for twelve years. Here we show that lime provides remarkable enhancements in soil chemistry and seed composition, without altering the seed's germination and vigor. Also, it favors the production of seeds with additional molecular mechanisms that extend their longevity. Our results indicate that the application of lime mitigates acidity in tropical soils and ensures the production of seeds with enhanced chemical composition and longer life span.

An Approach Using Emerging Optical Technologies and Artificial Intelligence Brings New Markers to Evaluate Peanut Seed Quality.

Seeds of high physiological quality are defined by their superior germination capacity and uniform seedling establishment. Here, it was investigated whether multispectral images combined with machine learning models can efficiently categorize the quality of peanut seedlots. The seed quality from seven lots was assessed traditionally (seed weight, water content, germination, and vigor) and by multispectral images (area, length, width, brightness, chlorophyll fluorescence, anthocyanin, and reflectance: 365 to 970 nm). Seedlings from the seeds of each lot were evaluated for their photosynthetic capacity (fluorescence and chlorophyll index, F0, Fm, and Fv/Fm) and stress indices (anthocyanin and NDVI). Artificial intelligence features (QDA method) applied to the data extracted from the seed images categorized lots with high and low quality. Higher levels of anthocyanin were found in the leaves of seedlings from low quality seeds. Therefore, this information is promising since the initial behavior of the seedlings reflected the quality of the seeds. The existence of new markers that effectively screen peanut seed quality was confirmed. The combination of physical properties (area, length, width, and coat brightness), pigments (chlorophyll fluorescence and anthocyanin), and light reflectance (660, 690, and 780 nm), is highly efficient to identify peanut seedlots with superior quality (98% accuracy).

Pre-germination treatments of Paricá (Schizolobium amazonicum) seeds / Tratamentos pré-germinativos de sementes de Paricá (Schizolobium amazonicum)

Paricá seeds have dormancy and, even after mechanical scarification, these seeds show slow and uneven germination. Pre-germination treatments can be used to increase seed germination performance. Thus, the aimed to evaluate the physiological potential and initial growth of paricá seeds after pre-germination treatments, using different substances as plant regulators and nutrients, in addition to mechanical scarification. The experimental design was completely randomized, in a 2x7 factorial scheme, consisting of the following pre-germination treatments: mechanical scarification (10% and 50% of the seed coat) and seed pre-soaking [control-water, KNO3 0.2%,Ca(NO3)2 0.2%, gibberellin 0.02%, cytokinin 0.02%, and mixture of gibberellin + cytokinin (1:1)] besides a control group without pre-soaking, with four replicates. The study evaluated germination and emergence rates, germination and emergence speed indices, collar diameter, plant height, seedling dry mass, hypocotyl and seedling length, and electrical conductivity. It was observed that pre-soaking the seeds in gibberellin after mechanical scarification at 50% as a pre-germination treatment resulted in seeds with higher vigor expression and greater initial seedling growth.

Sementes de paricá apresentam dormência e após superada pela escarificação mecânica, as sementes apresentam germinação lenta e desuniforme. Tratamentos pré-germinativos podem ser utilizados para incrementar a performance de germinação de sementes. Assim, o objetivo foi avaliar o potencial fisiológico de sementes, crescimento inicial de Paricá após tratamentos pré-germinativos, utilizando diferentes substâncias como reguladores vegetais e nutrientes, além da intensidade da escarificação mecânica. O delineamento experimental empregado foi o inteiramente casualizado, em esquema fatorial 2x7, constituído pelos tratamentos pré-germinativos: escarificação mecânica (10% e 50% do tegumento) e pré-embebição das sementes [controle- água, KNO3 0,2%,Ca(NO3)2 0,2%, giberelina 0,02%, citocinina 0,02%, e a mistura da solução de giberelina + citocinina (1:1)] além de um grupo controle sem pré-embebição, com quatro repetições. Avaliou-se a porcentagem de germinação e emergência, índice de velocidade de germinação e emergência, diâmetro, altura e fitomassa seca de plantas, comprimento de plântulas e hipocótilo e condutividade elétrica. A pré-embebição das sementes com giberelina após escarificação mecânica de 50% como tratamento pré-germinativo é recomendado para obtenção de sementes com maior expressão de vigor e crescimento inicial de plântulas.