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1.
Plants (Basel) ; 11(9)2022 May 01.
Artículo en Inglés | MEDLINE | ID: mdl-35567230

RESUMEN

Integrated management of rice-maize systems is an emerging challenge in southern India due to improper rice residues and tillage management in maize crops. Conservation agriculture (CA) practices such as a reduced tillage and maintaining stubble mulch may hold the potential to increase yields, reduce crop establishment costs and increase farm incomes. A five-year trial was performed to study the effect of different CA and establishment methods in rice on system productivity, profitability, and soil carbon status in a rice-maize system. In the rainy season, the trial consisted of two main treatments: (i) normal manual transplanting and (ii) direct-wet seeding, and three sub-main treatments at different sowing dates with fifteen day intervals. In addition, in the winter season, two tillage treatments (conventional and minimum tillage) were imposed over the rainy season treatments. Both rice and maize were grown under irrigated conditions. The results showed that sowing times at 15 day intervals did not impact the yield significantly. Transplanted rice obtained a significantly higher grain yield during the first four years, but in the last year, the yield was similar in both of the establishment methods. In the winter season, conventional tilled maize recorded a higher cob yield than under the minimum tilled treatment, except for the last year, where both the tillage treatment effects were the same. System productivity of CA-based minimum tilled rice-maize was inferior during the first three years but was superior to the conventionally tilled method in the fourth and fifth year. Pooled analysis revealed that the conventionally tilled rice-maize system resulted in a similar system productivity as that of the CA during the study period. The cost-benefit analysis revealed that transplanted rice and conventionally tilled maize fetched higher net returns of INR 111,074 and INR 101,658/ha, respectively, over the direct-wet seeded rice and CA. In addition, the 15 July rice sown followed by the maize system led to an increase in irrigation water productivity by 15.7%, and the total water (irrigation + rainfall) productivity by 27.1% in the maize crop compared with the 30 July sown system. The CA-based rice-maize system resulted in a significantly higher very labile (0.194%) and labile (0.196%) carbon concentration at a 0-5 cm depth of soil compared to those under the conventional system. Thus, CA can be recommended for southern India and similar agro-ecological tropic and sub-tropic conditions. This system can be followed with appropriate location-specific modification in South-Asian countries, where crop yields and soil health are declining as a result of continuous cereal-cereal crop rotation.

2.
Plants (Basel) ; 11(6)2022 Mar 08.
Artículo en Inglés | MEDLINE | ID: mdl-35336599

RESUMEN

Salinization of soils and freshwater resources by natural processes and/or human activities has become an increasing issue that affects environmental services and socioeconomic relations. In addition, salinization jeopardizes agroecosystems, inducing salt stress in most cultivated plants (nutrient deficiency, pH and oxidative stress, biomass reduction), and directly affects the quality and quantity of food production. Depending on the type of salt/stress (alkaline or pH-neutral), specific approaches and solutions should be applied to ameliorate the situation on-site. Various agro-hydrotechnical (soil and water conservation, reduced tillage, mulching, rainwater harvesting, irrigation and drainage, control of seawater intrusion), biological (agroforestry, multi-cropping, cultivation of salt-resistant species, bacterial inoculation, promotion of mycorrhiza, grafting with salt-resistant rootstocks), chemical (application of organic and mineral amendments, phytohormones), bio-ecological (breeding, desalination, application of nano-based products, seed biopriming), and/or institutional solutions (salinity monitoring, integrated national and regional strategies) are very effective against salinity/salt stress and numerous other constraints. Advances in computer science (artificial intelligence, machine learning) provide rapid predictions of salinization processes from the field to the global scale, under numerous scenarios, including climate change. Thus, these results represent a comprehensive outcome and tool for a multidisciplinary approach to protect and control salinization, minimizing damages caused by salt stress.

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