ABSTRACT

Obtaining image-based information is a powerful approach to capture and quantify seed vigor data. However, commercial systems that facilitate the processing and acquisition of images are often cost prohibitive. This study aimed to evaluate the efficiency of the Seedling Analysis System (Sistema de Análise de Plântulas - SAPL^®), in order to analyze the physiological potential of soybean seeds, in comparison with the information provided by vigor tests which are traditionally recommended for this species. Nine lots of soybean seeds were submitted to germination, germination speed, seedling emergence, cold test and electrical conductivity tests. In the SAPL^® analyzes, seedlings of four and six days, counted from the beginning of the germination test, were evaluated, resulting in values ​​for seedling length, growth, development uniformity, vigor index and corrected vigor index. The evaluated lots with emergence greater than 90 % showed a vigor index higher than 600 and 800, respectively in the fourth and sixth days. The indexes generated by SAPL^®, except for the uniformity index, presented positive and high correlations with the traditional tests (> 0.80). SAPL^® is efficient in identifying differences in the vigor of soybean seed lots.

KEYWORDS:
Glycine max (L.) Merill; physiological seed quality; seed technology

RESUMO

A obtenção de informações baseadas em imagens é uma abordagem poderosa para capturar e quantificar dados sobre o vigor de sementes. No entanto, sistemas comerciais que facilitam o processamento e a aquisição de imagens são, muitas vezes, de custo proibitivo. Objetivou-se avaliar a eficiência do Sistema de Análise de Plântulas (SAPL^®), para analisar o potencial fisiológico de sementes de soja, em comparação com informações fornecidas por testes de vigor tradicionalmente recomendados para a espécie. Nove lotes de sementes de soja foram submetidos a avaliações de germinação, velocidade de germinação, emergência de plântulas, teste de frio e condutividade elétrica. Nas análises com o SAPL^®, foram avaliadas plântulas com quatro e seis dias, contados a partir do início do teste de germinação, que resultaram em valores de comprimento de plântulas, crescimento, uniformidade de desenvolvimento, índice de vigor e índice de vigor corrigido. Os lotes avaliados com emergência superior a 90 % apresentaram índice de vigor superior a 600 e 800, no quarto e sexto dias, respectivamente. Os índices gerados pelo SAPL^®, exceto o índice de uniformidade, apresentaram correlações positivas e altas com os testes tradicionais (> 0,80). O SAPL^® é eficiente para identificar diferenças no vigor de lotes de sementes de soja.

PALAVRAS-CHAVE:
Glycine max (L.) Merill; qualidade fisiológica de sementes; tecnologia de sementes

INTRODUCTION

The use of computerized procedures capable of providing image-based information has been heralded as a powerful approach to capture and quantify data on physiological seed quality.

This type of procedure enables increasing the agility of the seed evaluation process, as well as providing a greater reliability in the obtained results (Marcos Filho 2015MARCOS FILHO, J. Seed vigor testing: an overview of the past, present and future perspective. Scientia Agricola , v. 72, n. 4, p. 363-374, 2015.). The use of computerized analyzes to determine seed vigor has been successfully reported for several species, such as pumpkin (Silva et al. 2017SILVA, P. P. da et al. Assessment of squash seed vigor using computerized image analysis. Journal of Seed Science, v. 39, n. 2, p. 159-165, 2017.), peanut (Barbosa et al. 2016BARBOSA, R. M. et al. Image analysis and peanut seeds performance during the production process. Científica, v. 44, n. 3, p. 412-420, 2016. ), corn (Castan et al. 2018CASTAN, D. O. C. et al. Vigor-S, a new system for evaluating the physiological potential of maize seeds. Scientia Agricola, v. 75, n. 2, p. 167-172, 2018. ), wheat (Brunes et al. 2016BRUNES, A. P. et al. Seedling length in wheat determined by image processing using mathematical tools. Revista Ciência Agronômica, v. 47, n. 2, p. 374-379, 2016.), sunflower (Rocha et al. 2015ROCHA, C. R. M. da et al. Avaliação do vigor de sementes de girassol por meio de análise de imagens de plântulas. Ciência Rural, v. 45, n. 6, p. 970-976, 2015. ), bean (Gomes Junior et al. 2014CALDEIRA, C. M. et al. Sunflower seed vigor determined by computerized seedling analysis. Científica, v. 42, n. 4, p. 346-353, 2014. ) and soybean (Marcos Filho et al. 2009MARCOS FILHO, J. et al. Métodos para avaliação do vigor de sementes de soja, incluindo a análise computadorizada de imagens. Revista Brasileira de Sementes, v. 31, n. 1, p. 102-112, 2009., Wendt et al. 2014WENDT, L. et al. Avaliação do potencial fisiológico de sementes de soja por meio de imagens. Pesquisa Agropecuaria Tropical, v. 44, n. 3, p. 280-286, 2014. and 2017WENDT, L. et al. Relação entre testes de vigor com a emergência a campo em sementes de soja. Revista Brasileira de Ciências Agrárias, v. 12, n. 2, p. 166-171, 2017., Yagushi et al. 2014YAGUSHI, J. T. et al. Saturated salt accelerated aging and computerized analysis of seedling images to evaluate soybean seed performance. Journal of Seed Science, v. 36, n. 2, p. 213-221, 2014.), among others.

The commercial systems developed for this purpose are powerful tools for collecting image data and making inferences about seed vigor. However, commercial systems are cost-restrictive for many laboratories, institutions and producers. To make high-performance computerized analysis methods more accessible, free software programs and low-cost equipment can be used.

The Seedling Analysis System (Sistema de Análise de Plântulas - SAPL^®) appears as a free option for this type of analysis. SAPL^® is based on the automated evaluation of seed vigor from seedling performance through digital image processing, which generates information about the length of the primary root, hypocotyl and total seedling length, as well as the root/hypocotyl ratio and parameters based on growth speed and uniformity. To do so, images obtained through photographs of the seedlings taken by smartphones or low-cost cameras are used. The software will soon be available for free download at the website of the Study Group on Seed Technology of the Universidade Federal do Rio Grande do Norte, along with a complete database.

This study aimed to evaluate the efficiency of SAPL^® to analyze the physiological potential of soybean seeds, in comparison with the information provided by vigor tests which have been traditionally recommended for this species.

MATERIAL AND METHODS

The present research was conducted at the Universidade Federal do Rio Grande do Norte, in Macaíba, Rio Grande do Norte state, Brazil, in 2017. Nine lots of soybean seeds (BRS 7570 IPRO cultivar) from the region of Unaí (Minas Gerais state, Brazil) were evaluated through the following tests:

Images were acquired through photographs, using a DV300F Samsung digital camera. The images were then transferred to a computer and saved into folders identified for each repetition. The analysis was performed with the SAPL^® software, installed on a HP Compaq Pro 6305 SFF computer, as shown in the sequence in Figure 1.

After analyzing and evaluating the seedlings, the software provided values related to the shoot, primary root and whole seedling length, as well as uniformity, growth, vigor and corrected vigor indices. These indices were defined by Sako et al. (2001)SAKO, Y. et al. A system for automated seed vigour assessment. Seed Science and Technology, v. 29, n. 3, p. 625-636, 2001., except for the corrected vigor index (CVI), introduced by the software developers based on the adaptive vigor index proposed by Sako et al. (2001)SAKO, Y. et al. A system for automated seed vigour assessment. Seed Science and Technology, v. 29, n. 3, p. 625-636, 2001., expressed by the following equation: CVI = (0.70 * G + 0.30 * U) * (germ/100), where CVI is the corrected vigor index, G the growth index, U the uniformity index and germ the germination percentage.

The statistical analysis was performed in a completely randomized design with a unifactorial model, in which the factor lot contained nine levels with four replicates each. The data were submitted to analysis of variance (Anova). After confirming the normal distribution of errors by the Shapiro-Wilk test, the means were compared by the Scott-Knott test (p < 0.05). Data from traditional analyzes and SAPL^® were also correlated by the Pearson's test (r; p < 0.05). The R statistical software was used in all analyzes (R Development Core Team 2014R DEVELOPMENT CORE TEAM. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing, 2014. ).

RESULTS AND DISCUSSION

Small differences were observed in the moisture content of the seeds, which varied between 8.5 % and 9.5 % (Table 1). This is considered a low variation and, according to Marcos Filho (2016)MARCOS FILHO, J. Seed physiology of cultivated plants. Londrina: Abrates, 2016., indicates that the seed lots can have their physiological quality compared to each other, since they are within the tolerable moisture limits for comparison, without being compromised by this factor.

For the germination test, it was observed that most of the lots presented a high viability, so that seven (lots 1, 2, 3, 4, 5, 8 and 9) of the nine evaluated lots presented values higher than 80 % for germination, being the minimum value established for commercialization of soybean seeds in Brazil (Brasil 2013BRASIL. Ministério da Agricultura Pecuária e Abastecimento. Padrões para a produção e a comercialização de sementes de soja (Glycine max). Diário Oficial da República Federativa do Brasil, Poder Executivo, Brasília, DF, 17 set. 2013. Seção 1, p. 28.). Lots 6 and 7 obtained germination percentages below 50 %, being considered as having a low physiological potential.

It is understood that significant differences in viability among lots are sufficient to infer about physiological quality disparities and, in this case, it is not necessary to complement them with vigor tests. However, this study aimed to use lots with different levels of physiological quality to verify the efficiency of the vigor evaluation methods, in this case making it important to contrast them.

Among the lots previously considered as having a high viability, the seedling emergence test classified the lots 1 and 3 as being superior, in relation to the others. Lots such as 2 and 9, with a previous germination equal to 90 %, presented a significant reduction in the number of normal seedlings, when submitted to the emergence test of 68 % and 79 %, respectively, indicating the low vigor of these lots. The emergence test seeks to identify vigorous seeds from conditions which are close to those observed at the field level, meaning uncontrolled conditions. In this sense, the information obtained from this test are valuable to predict the true physiological potential of the seeds.

Still in Table 1, it was possible to observe a close relation between the cold test and electrical conductivity. Both tests ranked the lots at six vigor levels, with the lot 3 achieving the highest performance in both tests. Moreover, significant differences were found among lots for the germination speed index, allowing a categorization into five vigor levels. As a priority, vigor tests seek to obtain complementary responses to those provided by the germination test (Ohlson et al. 2010OHLSON, O. de C. et al. Teste de envelhecimento acelerado em sementes de trigo. Revista Brasileira de Sementes, v. 32, n. 4, p. 118-124, 2010. ), enabling the acquisition of reliable information to determine the seed physiological potential, but some adjustments related to standardization, precision and speed, in obtaining results, are still necessary (Silva et al. 2017SILVA, P. P. da et al. Assessment of squash seed vigor using computerized image analysis. Journal of Seed Science, v. 39, n. 2, p. 159-165, 2017.).

In this research, the seedling image analysis generally allowed a greater agility in the evaluations, reducing the time spent to obtain the results. In the first evaluation performed on the fourth day after starting the germination test, physiological potential differences were identified among lots by means of seedling length (Table 2). Lot 3 was identified as having the highest length values; in contrast, lots 6 and 7 obtained lower growth rates. In evaluating the growth index, a grouping in seven vigor levels was verified, thereby allowing a more precise stratification of the lots, regarding physiological quality. The growth results corroborate those obtained by traditional physiological characterization tests for the lots tested in this study. This result is important, because one of the basic requirements for introducing new seed vigor evaluation procedures is their equivalence to other routinely used laboratory tests (Gomes Junior et al. 2014GOMES JUNIOR, F. G. et al. Automated image analysis of seedlings for vigor evaluation of common bean seeds. Acta Scientiarum Agronomy, v. 36, n. 2, p. 195-200, 2014. ), or even in finding a greater sensitivity, in relation to the characterization of more vigorous lots.

There was no statistical difference for the uniformity variable between the tested lots in the two evaluated periods, since it is understood that, although they presented different lengths within the same lot, they maintained a homogeneous growth rate, which reflected in their non-differentiation, when the uniformity index was used. Studies by Caldeira et al. (2014)CALDEIRA, C. M. et al. Sunflower seed vigor determined by computerized seedling analysis. Científica, v. 42, n. 4, p. 346-353, 2014. , Chiquito et al. (2012)CHIQUITO, A. A. et al. Assessment of physiological potential of cucumber seeds using the software Seedling Vigor Imaging System® (SVIS®). Revista Brasileira de Sementes, v. 34, n. 2, p. 255-263, 2012. and Marchi & Cicero (2017)MARCHI, J. L. de; CICERO, S. M. Use of the software Seed Vigor Imaging System (SVIS®) for assessing vigor of carrot seeds. Scientia Agricola, v. 74, n. 6, p. 469-473, 2017. also did not demonstrate success in using the uniformity index for evaluating sunflower, cucumber or carrot seeds, respectively.

In the second evaluation performed on the sixth day after starting the germination test, it was observed that lots 1 and 3 (Table 2) presented a higher physiological potential than the others for seedling length and for all the evaluated indices. The analysis performed on the sixth day presented a lower stratification, if compared to the evaluation performed on the fourth day. This result may indicate that an earlier evaluation allows a greater refinement in the process of identifying quality differences among the tested lots, in addition to significantly reducing the time spent to perform the test. Researches with crambe (Leão-Araújo et al. 2017LEÃO-ARAÚJO, E. F. et al. Controlled deterioration test and use of the Seed Vigor Imaging System (SVIS®) to evaluate the physiological potential of crambe seeds. Journal of Seed Science, v. 39, n. 4, p. 393-400, 2017. ), pumpkin (Silva et al. 2017SILVA, P. P. da et al. Assessment of squash seed vigor using computerized image analysis. Journal of Seed Science, v. 39, n. 2, p. 159-165, 2017.), bean (Gomes Junior et al. 2014GOMES JUNIOR, F. G. et al. Automated image analysis of seedlings for vigor evaluation of common bean seeds. Acta Scientiarum Agronomy, v. 36, n. 2, p. 195-200, 2014. ) and soybean seeds (Marcos Filho et al. 2009MARCOS FILHO, J. et al. Métodos para avaliação do vigor de sementes de soja, incluindo a análise computadorizada de imagens. Revista Brasileira de Sementes, v. 31, n. 1, p. 102-112, 2009., Wendt et al. 2014WENDT, L. et al. Avaliação do potencial fisiológico de sementes de soja por meio de imagens. Pesquisa Agropecuaria Tropical, v. 44, n. 3, p. 280-286, 2014. and 2017WENDT, L. et al. Relação entre testes de vigor com a emergência a campo em sementes de soja. Revista Brasileira de Ciências Agrárias, v. 12, n. 2, p. 166-171, 2017.), among other crops, have also demonstrated promising results in earlier evaluations.

Regarding the use of the vigor index and corrected vigor index for the two evaluation periods (Table 2), both were able to rank the lots for their physiological quality. The corrected vigor was able to achieve promising results, showing itself to be sensitive for categorizing the lots for vigor. Corrected vigor is an index made up of the product of the vigor index with the germination percentage, and thus a more efficient beaconing of the vigor results is obtained. According to Nakagawa et al. (1999)NAKAGAWA, J. et al. Testes de vigor baseados no desempenho das plântulas. In: KRZYANANOWSKI, F. C.; VIEIRA, R. D.; FRANÇA-NETO, J. B. (Eds.). Vigor de sementes: conceitos e testes. Londrina: Abrates, 1999. p. 9-13. , this adjustment is important, because, in order to correctly perform a lot quality evaluation together with the results obtained in the seedling length test, the germination percentage should be taken into account, since there are cases in which the lot presents a low germination percentage and a high average seedling length value, or the opposite. In this situation, the few normal seedlings formed (low germination percentage) present a high growth rate, a fact that cannot be transposed for the whole sample or the whole lot, in considering it to be vigorous. Therefore, it is necessary to take into account the length and uniformity of the seedlings in the lot in question, thereby also having the germination value as a parameter.

From the correlation analysis presented in Table 3, the limitation of the uniformity index is evident for classifying the lots and to express a univocal relation with other variables. Thus, this index should not be considered in the digital physiological quality analysis of the seeds. The other variables generated from SAPL^® showed a high correlation with the traditional tests, indicating a close relationship between them. According to Albuquerque et al. (2008)ALBUQUERQUE, C. J. B. et al. Produtividade de híbridos de milho verde experimentais e comerciais. Bioscience Journal, v. 24, n. 2, p. 69-76, 2008., the number of tests evaluated in future experiments may be reduced with linear correlation analysis, as a great dependence between the variables is observed.

One of the difficulties to determine the seedling length is the tendency for a hypocotyl curvature of the seedlings (Gomes Junior et al. 2014GOMES JUNIOR, F. G. et al. Automated image analysis of seedlings for vigor evaluation of common bean seeds. Acta Scientiarum Agronomy, v. 36, n. 2, p. 195-200, 2014. ). However, automating these determinations significantly contributes to reduce errors made by analysts in seed laboratories, who routinely work intensively at evaluating a high number of replicates. Figure 2 shows the print screen of the individual seedling processing window in SAPL^®, in which the shape of each seedling is evaluated.

Important information about the growth potential and uniformity of seed germination are fundamental pillars for successfully establishing plants in the field. Thus, the results from this study are promising for evaluating the quality of soybean seeds via the SAPL^® software and, based on this research, it could easily be included in the analyzes performed by laboratories, institutions and by rural producers themselves. According to Gomes Junior et al. (2014)GOMES JUNIOR, F. G. et al. Automated image analysis of seedlings for vigor evaluation of common bean seeds. Acta Scientiarum Agronomy, v. 36, n. 2, p. 195-200, 2014. , in addition to the consistency of results, the analysis of seedling images to obtain lot vigor contributes to the information management and to store images and numerical results for future studies.

CONCLUSIONS

REFERENCES

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