The need to promote a sustainable land management (SLM) approach for land degradation neutrality (LDN) is a global challenge, and we must rely on local assessments of how rural participants are conducting their work. Therefore, the objectives of the present research are as follows: 1) evaluate the fruit culture of the guava producers (Psidium guajava, L.) in Calvillo, Aguascalientes, Mexico; and 2) to show whether it is possible to detect key variables in SLM by using an artificial neural network to improve productivity.

The study unit (SU) was located in the community of San Tadeo (21.917 °N and 102.701 °W) in the municipality of Calvillo, Aguascalientes. We considered a total of 430 ha established with this fruit and nine orchards that consisted of 9.05 ha, which is equivalent to 2.09% of the total area. Each hectare was randomly sampled, with a significance of 95% (α ≥ 0.05). The information was collected by using empirical field techniques and a questionnaire sent to the producers. The results revealed that the productive success of the SU is based on the knowledge and ability of the fruit farmers to take advantage of bioclimatic and biophysical conditions for guava cultivation. It was demonstrated in approximately 90% of the analyzed cases that the producer’s SLM was between regular and excellent.