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.

Planting sweet potato branches with the appropriate bud number and disposition, below and above ground, can favor vegetative growth and yield that better fit the marketable standards. This study aimed to explore the influence of the number of buds and their distribution ratio, above and below ground level, on the agronomic and marketable components of sweet potato tuberous roots. The experiment was carried out in a randomized complete block design with three replications. The treatments were arranged in a factorial scheme (3 x 5), with 2, 4, and 8 above-ground buds combined with 2, 4, 6, 8, and 10 below-ground buds. Branches from the UZBD 06 accession (Canadense standard) were used. Vegetative, productive, and marketable traits of roots were evaluated. The use of branches with a greater number of buds above and below ground increased shoot dry biomass. Planting seed branches with 8 buds above and 8 buds below ground provided a greater number and production of marketable roots. The use of 10 buried buds increased root number and yield in the 150-450 g marketable classes, which the consumer market values the most.

This study was conducted under controlled conditions to investigate the response of two tomato cultivars and influence of the moment of application of Bacillus subtilis in the control of Meloidogyne incognita in tomato. The treatments consisted of susceptible and resistant tomato cultivars and moment of applying Bacillus subtilis before and after planting the tomato seedlings. Were evaluated plant growth, nutrition, nematode reproduction, colonisation and genetic diversity of the genus Bacillus spp. in rhizosphere and substrate. Inoculation of B. subtilis after planting reduced the number of nematodes and both moments of applications promoted reduction of M. incognita eggs in tomato roots. Inoculation of rhizobacteria increased the colonisation of Bacillus sp. in the rhizosphere of both cultivars. The integration of genetic and biological methods did not increase parasite control. B. subtilis inoculated after planting exerts efficient biocontrol against M. incognita reducing the nematode reproduction factor only in the susceptible cultivar.