The role of the biochemical composition of soybean seeds in the tolerance to deterioration under natural and artificial aging.

The fast decline in the physiological quality of seeds during storage is a serious problem. It is known that the reduction of seed quality may be related to its biochemical constitution. However, the relationship between the composition and the mechanisms linked to the loss of vigor of soybean seeds during aging has not been elucidated yet. Thus, the aim of this work was to analyze the role of the biochemical composition of soybean seeds in the physiological quality and in the tolerance to deterioration due to natural and artificial aging. Seeds of six soybean genotypes were analyzed initially and after being submitted to natural aging, storage for eight months, and artificial aging, using the temperature of 41 °C and 100 % relative humidity for 96 h. Moisture content, germination and vigor tests were carried out. Also, there were measured the content of oil, total protein, soluble protein, malonaldehyde, and fatty acids palmitic, stearic, oleic, linoleic, and linolenic. It was verified that the physiological quality of soybean seeds decreased with both kinds of aging. However, the deterioration process occurs by distinct mechanisms. The biochemical composition of the seeds is associated with the physiological quality and their storage potential is changed by natural and artificial aging. The tolerance of the seed to deterioration is related to soluble protein and fatty acids content. Oleic fatty acid and soluble protein can be used as indicators of physiological quality in soybean seeds.

FT-NIR and linear discriminant analysis to classify chickpea seeds produced with harvest aid chemicals.

Spectroscopy and machine learning (ML) algorithms have provided significant advances to the modern food industry. Instruments focusing on near-infrared spectroscopy allow obtaining information about seed and grain chemical composition, which can be related to changes caused by field pesticides. We investigated the potential of FT-NIR spectroscopy combined with Linear Discriminant Analysis (LDA) to discriminate chickpea seeds produced using different desiccant herbicides at harvest anticipation. Five herbicides applied at three moments of the plant reproductive stage were utilized. The NIR spectra obtained from individual seeds were used to build ML models based on LDA algorithm. The models developed to identify the herbicide and the plant phenological stage at which it was applied reached 94% in the independent validation set. Thus, the LDA models developed using near-infrared spectral data provided to be efficient, quick, non-destructive, and accurate to identify differences between seeds due to pre-harvest herbicides application.

Machine Learning for Seed Quality Classification: An Advanced Approach Using Merger Data from FT-NIR Spectroscopy and X-ray Imaging.

Optical sensors combined with machine learning algorithms have led to significant advances in seed science. These advances have facilitated the development of robust approaches, providing decision-making support in the seed industry related to the marketing of seed lots. In this study, a novel approach for seed quality classification is presented. We developed classifier models using Fourier transform near-infrared (FT-NIR) spectroscopy and X-ray imaging techniques to predict seed germination and vigor. A forage grass (Urochloa brizantha) was used as a model species. FT-NIR spectroscopy data and radiographic images were obtained from individual seeds, and the models were created based on the following algorithms: linear discriminant analysis (LDA), partial least squares discriminant analysis (PLS-DA), random forest (RF), naive Bayes (NB), and support vector machine with radial basis (SVM-r) kernel. In the germination prediction, the models individually reached an accuracy of 82% using FT-NIR data, and 90% using X-ray data. For seed vigor, the models achieved 61% and 68% accuracy using FT-NIR and X-ray data, respectively. Combining the FT-NIR and X-ray data, the performance of the classification model reached an accuracy of 85% to predict germination, and 62% for seed vigor. Overall, the models developed using both NIR spectra and X-ray imaging data in machine learning algorithms are efficient in quickly, non-destructively, and accurately identifying the capacity of seed to germinate. The use of X-ray data and the LDA algorithm showed great potential to be used as a viable alternative to assist in the quality classification of U. brizantha seeds.

Non-destructive identification of physical damage in mung bean (Vigna radiata L. ) seeds by X-ray image analysis / Identificação não destrutiva de danos físicos em sementes de feijão-mungo (Vigna radiata L. ) por análise de imagem de raios-X

Global demand for pulses such as the mung bean has grown in the last years. For successful production of these crops it is necessary to use high quality seeds. Methodologies based on X-ray image analysis have been used as a complementary tool to evaluate the physical quality of seeds due to their speed and potential for automation. The aim of this study was to evaluate the efficiency of X-ray analysis for non-destructive evaluation of the physical quality of Vigna radiata seeds and to relate the variables obtained with their physiological potential. For this, seeds from eight lots were X-rayed and subsequently subject to germination test. In total, 18 physical and physiological parameters were determined. The X-ray image analysis was efficient for evaluating the internal morphology of Vigna radiata seeds and allowed the identification of various damage types. However, it was not possible to relate the physical variables to the seed quality as the lots presented similar germination percentage. Physical variables such as solidity and circularity are related to percentage of root protrusion and length of seedling hypocotyl. Low relative densities indicate deteriorated tissues, related to severe morphological damage and non-viable seeds.

A demanda mundial por leguminosas como o feijão mungo tem crescido nos últimos anos. Para o sucesso da produção destas culturas é necessário a utilização de sementes de alta qualidade. Metodologias baseadas na análise de imagens de raios X têm sido utilizadas como ferramenta complementar para avaliação da qualidade física de sementes em função da sua rapidez e potencial de automatização. O objetivo deste trabalho foi avaliar a eficiência da análise de raios X para avaliação não destrutiva da qualidade física de sementes de Vigna radiata, e relacionar as variáveis obtidas com o seu potencial fisiológico.Para tal, sementes de oito lotes foram radiografadas e submetidas ao teste de germinação. Por meio dessas avaliações foram determinadas 18 variáveis, distribuídas entre físicas e fisiológicas. A análise de imagens de raios X foi eficiente para a avaliação da morfologia interna das sementes Vigna radiata e permitiu a identificação de vários tipos de danos. Porém, não foi possível relacionar as variáveis físicas com a qualidade das sementes, pois os lotes apresentaram porcentagens de germinação semelhantes. Variáveis físicas como solidez e circularidade estão relacionadas com a percentagem de protrusão radicular e o comprimento de hipocótilo das plântulas. Densidades relativas baixas indicam tecidos deteriorados, tendo relação com danos morfológicos graves e sementes inviáveis.

Teste de frio para avaliação do potencial fisiológico de sementes de pinhão manso (Jatropha curcas L) / Cold test methodology for evaluation of the physiological potential of Jatropha curcas seeds

O pinhão manso (Jatropha curcas L.) é uma planta de grande destaque entre as oleaginosas promissoras para a produção de biodiesel. Contudo, para a comercialização segura de lotes são necessárias informações sobre a qualidade das sementes, especialmente vigor. Objetivou-se, neste trabalho, adequar a metodologia do teste de frio para a avaliação do vigor de sementes de pinhão manso. Sementes de cinco lotes de pinhão manso foram inicialmente submetidas a testes para avalição da qualidade fisiológica e, em seguida, submetidas ao teste de frio. Para isso, foram semeadas em papel toalha, tipo germitest, com e sem solo, sendo confeccionados rolos que foram mantidos a 10 oC, por cinco, sete, nove e 11 dias. Após cada período, os rolos foram transferidos para germinador a 25 oC, realizando-se a avaliação da germinação aos 5 e 7 dias. O experimento foi conduzido em delineamento inteiramente casualizado e as médias dos tratamentos comparadas pelo teste de Tukey (p < 0,05) e correlacionadas com os resultados dos demais testes. O teste de frio é eficiente para a estratificação dos lotes de sementes de pinhão manso em níveis de vigor. Recomenda-se utilizar a metodologia do rolo de papel sem solo e manter as sementes em BOD a 10 ºC por sete dias, seguida por um período de cinco dias em germinador a 25 ºC.

The physic nut has great potential for biodiesel production. However, for safe comercialization of the lots, information about seed quality is necessary, especially about vigor. This work aimed to adapt the cold test methodology for evaluation of the physiological quality of Jatropha curcas seeds. Seeds of five lots were initially characterized and then tested with cold test. For this, seeds were sown on germitest paper, with and without soil, and rollers were made. Then, the seeds were exposed to 10 oC during five, seven, nine and 11 days. After the cold period, the seed were transferred to germinator with temperature adjusted to 25 oC for later evaluation at 5 and 7 days. The statistical design was completely randomized and the treatment means were compared by Tukey test (p < 0,05) and correlated with the results of other tests. The cold test proved to be efficient for the lots stratification on levels of vigor. It is recommended to use paper roll without soil and keep the seeds in BOD at 10 ºC for seven days and then transfer them to germinator with temperature adjusted to 25 °C for five days.

Nodulation and growth of soybean plants as a function of coating the seeds with phosphorous / Nodulação e crescimento de plantas de soja em função do recobrimento das sementes com fósforo

The increase of phosphorous concentration in soybean seed enhances the subsequent potential plant yield. The objective was to evaluate the effect of coating the seeds with phosphorous on the nodulation and growth of soybean plants. Seeds from two lots of cultivar Pioneer ­ P98R31 were treated with monobasic phosphate sodium in doses of 0.0; 0.2; 0.4; 0.8 and 1.2 g hg-1 of seeds and, with the inoculant 'turfoso Microxisto' using 3.0 millions cells of bacteria (Bradyrhizobium japonicum) by seed. The experiment was carried out in a totally randomized block design with five replications in a factorial scheme of 2x2x5+4, consisting of seeds with different phosphorus content, two levels of phosphorus fertilizer in the soil, five levels of P used in the coating of seeds, and four controls. After treatments, the seeds were sowed in pots with 3.0 dm3 of red yellow Latosol, which received P doses of 200 and 400 mg kg-1 having triple superphosphate as the source. In the stage R2 of plant development, the P and N concentration in the third trifoliate was evaluated. In the initial stage of strings formation (R3), the plant height, whole shoot, root and the dry matter of viable nodules were evaluated. Independently of the endogenous P concentration in the seed, coating soybean seeds with P did not increase nodulation and growth of plants in soil with higher high P availability, whereas in soil with less P available, the coating of seeds increased the nodulation and growth of soybean plants.

O incremento da concentração de fósforo na semente de soja aumenta o potencial de rendimento da planta subsequente. O objetivo do trabalho foi estudar o efeito do fósforo, via recobrimento das sementes, na nodulação e no crescimento das plantas de soja. Utilizaram-se sementes de soja de dois lotes, cultivar Pioneer P98R31, com diferentes teores de fósforo. As sementes foram recobertas com fosfato de sódio monobásico nas doses de 0,0; 0,2; 0,4; 0,8 e 1,2 g hg-1 de sementes e, em seguida, com inoculante turfoso com 3,0 milhões de células de bactéria (Bradyrhizobium japonicum) por semente. O experimento foi instalado em delineamento de blocos ao acaso com cinco repetições, em esquema fatorial 2x2x5 + 4, combinando os dois níveis de P nas sementes, dois níveis de fertilizante no solo, cinco níveis de P usados no recobrimento das sementes, além de quatro controles. Após os tratamentos, as sementes foram semeadas em vasos plásticos contendo 3,0 dm3 de Latossolo Vermelho Amarelo, sendo adicionado fósforo nas doses de 200 e 400 mg kg-1 como superfosfato triplo. No estádio R2 de desenvolvimento das plantas, foi avaliado o teor de fósforo e nitrogênio no terceiro trifólio, e no estádio R3, a altura de plantas, a matéria seca da parte aérea, da raiz e dos nódulos. Independente da concentração original de fósforo na semente, o recobrimento das sementes com fósforo não aumentou a nodulação e o crescimento das plantas de soja sob maior disponibilidade de fósforo no solo. Já sob menor disponibilidade de fósforo no solo, o recobrimento das sementes aumentou a nodulação e o crescimento das plantas de soja.