<p class="MDPI17abstract">Currently, there is increasing interest in the cultivation of alternative grain crops, such as amaranth (<em>Amaranthus cruentus </em>L.)<em> </em>in Italy. However, few information exist for the most optimal sowing date (SD) of amaranth especially under rainfed conditions. A field-trial was conducted in Tuscany during 2018 to evaluate SD effects on amaranth genotypes (‘Kharkov’ and two new breeding lines coded ‘A-61’ and ‘A67’). The three SD were March 27 (first), April 20 (second), June 4 (third). Only the first and second SD coincided with increasing photoperiod. Cumulative Growing Degree Days (GDD) for ripening were 2282, 1990 and 1480 for the first, second and third SD, respectively. Compared to the first two SD, ground-cover was 20 % less  from panicle formation in the third SD, therefore potentially less competitive towards weeds. A-67 was more “palatable” to the incidence of sugar beet flea beetle (<em>Chaenoctema tibialis</em> Illinger) from the earliest stages of growth. In contrast, ‘Kharkov’, was significantly less attacked by the insect over all three SD.</p><p class="MDPI12title">‘Kharkov’, demonstrated greater flexibility with stable yields of 1.3 t ha^-1 for the first and second SD. In contrast, significant yield reductions (1.5 to 1.2 t ha^-1, from the first to second SD, respectively) were evident for both lines of amaranth in response to SD delay. Adverse effects of the third SD, included significant decline in yield, protein content and 1000 seed mass. In conclusion, amaranth,  March-April SD may be recommended for obtaining optimal grain yield of amaranth along with making it successful as a viable alternative grain crop under  under agro-ecological conditions of Central Italy.</p>

The global agricultural sector needs to implement good soil management practices, in particular to prevent erosion and to improve water-retention capacity. The introduction of tillage techniques along particular theoretical lines, called keylines, can make a significant contribution to improving the management of the soil and agricultural crops. The keyline system has been around for less than 100 years. With this preliminary work, we performed a comparative analysis of two small river basins (less than 100 ha) before and after keyline application, based on GIS computational models (TWI and SIMWE). The calculation models were elaborated starting from a DTM with 2 m resolution, obtained from a LIDAR survey. The comparative analysis, in qualitative terms, showed a positive effect of the keylines, both in terms of erodibility and infiltration of runoff water. The use of GIS models to verify the effectiveness in the planning phase can constitute a decision support system that guides agronomists, technicians, and farmers.

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