Abstract
Maize ( Zea mays L.) yield and its response to nitrogen (N) are affected by the spatial variability of the interaction between weather, management, and soil properties. The objectives of this study were (i) to evaluate the response of spatial variability of maize yield by homogeneous zones (HZs) to different N fertilizer rates under rainfed conditions, (ii) to test the ability of the SALUS (System Approach to Land Use Sustainability) model to simulate the effects of N rates on maize yield under rainfed and irrigated conditions, and (iii) to estimate spatial and temporal N fertilizer response risk in maize through the use of long‐term simulations. In two field experiments in Parana, Argentina (−31.8333°, −60.5167°) in 2011 (Field 1) and 2012 (Field 2), four fertilization treatments (0, 70, 140, and 210 kg ha −1 ) were evaluated in different HZs. The SALUS model was used to evaluate spatial variability in yield, N response, and net revenue over the long‐term period (1971–2012). Results showed that yield was significantly affected by N rate ( p < 0.01) in both fields and by HZ in Field 2 ( p < 0.05), whereas N response was only affected by N rate. Simulated yield was significantly affected by N. The model accounted for the spatial variability, showing HZ effect ( p < 0.001) and a significant HZ × N interaction ( p < 0.0001). The optimal economic return N rate differed between HZs in both fields. Our procedure demonstrated the ability to improve N management by the selection of appropriate N rates across the field, thereby improving N use efficiency and growers’ profits and reducing the potential for negative environmental impacts. Core Ideas Model‐based approach accounted for spatio‐temporal variability of maize N response. Temporal variability of grain yield, N response, and net revenue increased with N rate. The N rate required to reach the highest net revenue differed between homogenous zones within fields. Selecting N rate by homogenous zones might reduce environmental and economic risk.
Abstract from the paper’s OpenAlex record, shown for indexing and research. Copyright remains with the authors or the publisher. Read at the source ↗
The text the model read, with the source record’s inline markup (italics, sub- and superscripts) rendered and its character entities decoded; quote offsets refer to the raw text.
Claims 9
Claim · model-written summary
Nitrogen rate significantly affected maize yield in both fields.
Zea maysNot reportedComparatorDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Results showed that yield was significantly affected by N rate ( p < 0.01) in both fields and by HZ in Field 2 ( p < 0.05), whereas N response was only affected by N rate.”
t0“Maize”
Claim · model-written summary
Homogeneous zone significantly affected maize yield in Field 2.
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Results showed that yield was significantly affected by N rate ( p < 0.01) in both fields and by HZ in Field 2 ( p < 0.05), whereas N response was only affected by N rate.”
t0“Maize”
Claim · model-written summary
Nitrogen response was affected only by nitrogen rate.
Not reportedComparatorDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Results showed that yield was significantly affected by N rate ( p < 0.01) in both fields and by HZ in Field 2 ( p < 0.05), whereas N response was only affected by N rate.”
t0“Maize”
Claim · model-written summary
Simulated maize yield was significantly affected by nitrogen.
Not reportedComparatorDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Simulated yield was significantly affected by N.”
t0“Maize”
Claim · model-written summary
The model accounted for spatial variability, with an HZ effect and HZ-by-nitrogen interaction.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The model accounted for the spatial variability, showing HZ effect ( p < 0.001) and a significant HZ × N interaction ( p < 0.0001).”
t0“Maize”
Claim · model-written summary
The economic optimum nitrogen rate differed among homogeneous zones in both fields.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The optimal economic return N rate differed between HZs in both fields.”
t0“Maize”
Claim · model-written summary
Temporal variability of grain yield, nitrogen response and net revenue increased with nitrogen rate.
- Treatment
- N ratee0
- Outcome
- Temporal variability of grain yield, N response, and net revenuee0
- Direction
- increasede0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Temporal variability of grain yield, N response, and net revenue increased with N rate.”
t0“Maize”
Claim · model-written summary
The authors propose zone-specific nitrogen rates to improve nitrogen use efficiency and grower profits and reduce environmental impacts.
- Outcome
- selection of appropriate N rates across the fielde0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Our procedure demonstrated the ability to improve N management by the selection of appropriate N rates across the field, thereby improving N use efficiency and growers’ profits and reducing the potential for negative environmental impacts.”
t0“Maize”
Claim · model-written summary
The authors suggest selecting nitrogen rate by homogeneous zone to reduce environmental and economic risk.
- Outcome
- Selecting N rate by homogenous zonese0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Selecting N rate by homogenous zones might reduce environmental and economic risk.”
t0“Maize”