Modeling the hyperspectral response of vegetables is important for estimating water stress through a noninvasive approach. This article evaluates the hyperspectral response of water-stress induced lettuce (Lactuca sativa L.) using artificial neural networks (ANN). We evenly split 36 lettuce pots into three groups: control, stress, and bacteria. Hyperspectral response was measured four times, during 14 days of stress induction, with an ASD Fieldspec HandHeld spectroradiometer (325–1075 nm). Both reflectance and absorbance measurements were calculated. Different biophysical parameters were also evaluated. The performance of the ANN approach was compared against other machine learning algorithms. Our results show that the ANN approach could separate the water-stressed lettuce from the non-stressed group with up to 80% accuracy at the beginning of the experiment. Additionally, this accuracy improved at the end of the experiment, reaching an accuracy of up to 93%. Absorbance data offered better accuracy than reflectance data to model it. This study demonstrated that it is possible to detect early stages of water stress in lettuce plants with high accuracy based on an ANN approach applied to hyperspectral data. The methodology has the potential to be applied to other species and cultivars in agricultural fields.

Water stress is one important abiotic stress with negative impacts on plant productivity. In order to ameliorate abiotic stress, plant growth-promoting rhizobacteria (PGPR), such as Bacillus subtilis, can be used due to their positive effects on plant physiology. The present study aimed to evaluate the effects of B. subtilis on the performance of maize and common bean under water deficit conditions. The study was performed in a plant growth chamber and the growth, gas exchange parameters and antioxidant activity were evaluated. B. subtilis promoted the growth of common bean and maize, and also increased the water use efficiency. The inoculation with B. subtilis increased leaf water content and the regulation of stomata, without damaging photosynthetic rates. Overall, B. subtilis decreased antioxidant activities in both plants. The results suggest that B. subtilis could be used as inoculants for common bean and maize to protect against water stress. ARTICLE HISTORY

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RESUMOA execução do trabalho ocorreu no laboratório de sementes do Centro de Ciências Agrárias (CCA) e na horta da Universidade do Oeste Paulista (UNOESTE), Presidente Prudente -SP em 2016. No experimento, foram empregados 35 quilos de tomate (Lycopersicon esculentum Mill.), pertencente ao grupo Saladete, cultivar Juliane. As doses de cal hidratada aplicadas foram T1= 0,0 g, T2= 50 g, T3= 100 g e T4= 150 g respectivamente. As sementes depois de secas foram armazenadas em condições de câmara fria por 14 dias. Em seguida foi avaliado a % de germinação, índice de velocidade de germinação (IVG) e teste de emergência. A remoção da mucilagem de tomate grupo Saladete, foi mais eficiente com a utilização de 50 g de cal hidratada, proporcionando reduzir o processo de obtenção de sementes de tomate em dois dias e, aumentando em 25 % o crescimento de plântulas. Palavras-chave: Sarcotesta; Cal hidratada, Germinação, Altura de Plântuas, Produção COST OF PRODUCTION AND SUSTAINABILITY OF LETTUCE ABSTRACTThe work was carried out in the seed laboratory of the Center of Agricultural Sciences (CCA) and in the garden of the Universidade do Oeste Paulista (UNOESTE), Presidente Prudente -SP in 2016. In the experiment, 35 kg of tomato (Lycopersicon esculentum Mill.), belonging to the group Saladete, cultivar Juliane. The doses of hydrated lime applied were T1 = 0.0 g, T2 = 50 g, T3 = 100 g and T4 = 150 g respectively. The dried seeds were stored under cold chamber conditions for 14 days. Then the germination%, germination rate index (IVG) and emergency test were evaluated. The removal of Saladete group tomato mucilage was more efficient with the use of 50 g of hydrated lime, reducing the process of obtaining tomato seeds in two days and increasing the seedling growth by 25%.