Row-crop planter performance to support variable-rate seeding of maize.
- Published in:
- Precision Agriculture, 2020, v. 21, n. 3, p. 603, doi. 10.1007/s11119-019-09685-3
- By:
- Publication type:
- Article
Works matching IS 13852256 AND DT 2020 AND VI 21 AND IP 3
Results: 13
1
2
Mapping sub-field maize yields in Nebraska, USA by combining remote sensing imagery, crop simulation models, and machine learning.
- Published in:
- Precision Agriculture, 2020, v. 21, n. 3, p. 678, doi. 10.1007/s11119-019-09689-z
- By:
- Publication type:
- Article
3
Delineation of management zones and optimization of irrigation scheduling to improve irrigation water productivity and revenue in a farmland of Northwest China.
- Published in:
- Precision Agriculture, 2020, v. 21, n. 3, p. 655, doi. 10.1007/s11119-019-09688-0
- By:
- Publication type:
- Article
4
Golf course superintendents' knowledge of variability within fairways: a tool for precision turfgrass management.
- Published in:
- Precision Agriculture, 2020, v. 21, n. 3, p. 637, doi. 10.1007/s11119-019-09687-1
- By:
- Publication type:
- Article
5
Delineating site-specific management zones on pasture soil using a probabilistic and objective model and geostatistical techniques.
- Published in:
- Precision Agriculture, 2020, v. 21, n. 3, p. 620, doi. 10.1007/s11119-019-09686-2
- By:
- Publication type:
- Article
6
Variable-rate application of high spatial resolution can improve cotton N-use efficiency and profitability.
- Published in:
- Precision Agriculture, 2020, v. 21, n. 3, p. 695, doi. 10.1007/s11119-019-09690-6
- By:
- Publication type:
- Article
7
Field scale row unit vibration affecting planting quality.
- Published in:
- Precision Agriculture, 2020, v. 21, n. 3, p. 589, doi. 10.1007/s11119-019-09684-4
- By:
- Publication type:
- Article
8
Linking weed patterns with soil properties: a long-term case study.
- Published in:
- Precision Agriculture, 2020, v. 21, n. 3, p. 569, doi. 10.1007/s11119-019-09682-6
- By:
- Publication type:
- Article
9
Examining the social and biophysical determinants of U.S. Midwestern corn farmers' adoption of precision agriculture.
- Published in:
- Precision Agriculture, 2020, v. 21, n. 3, p. 549, doi. 10.1007/s11119-019-09681-7
- By:
- Publication type:
- Article
10
Using data on soil ECa, soil water properties, and response of tree root system for spatial water balancing in an apple orchard.
- Published in:
- Precision Agriculture, 2020, v. 21, n. 3, p. 522, doi. 10.1007/s11119-019-09680-8
- By:
- Publication type:
- Article
11
Detection and counting of flowers on apple trees for better chemical thinning decisions.
- Published in:
- Precision Agriculture, 2020, v. 21, n. 3, p. 503, doi. 10.1007/s11119-019-09679-1
- By:
- Publication type:
- Article
12
Modelling DUALEM-2 measured soil conductivity as a function of measuring depth to correlate with soil moisture content and potato tuber yield.
- Published in:
- Precision Agriculture, 2020, v. 21, n. 3, p. 484, doi. 10.1007/s11119-019-09678-2
- By:
- Publication type:
- Article
13
The novel use of proximal photogrammetry and terrestrial LiDAR to quantify the structural complexity of orchard trees.
- Published in:
- Precision Agriculture, 2020, v. 21, n. 3, p. 473, doi. 10.1007/s11119-019-09676-4
- By:
- Publication type:
- Article