Tasseled Cap single band export in GEE

Question

Based on the mentioned code please suggest me how can I export single band image (either brightness band or greenness band) in google earth engine.

var sanfrancisco = ee.Feature(
    ee.Geometry.Polygon(
        [[[-122.5150959435926, 37.78159122861445],
          [-122.5150959435926, 37.715353209066016],
          [-122.39012646117072, 37.715353209066016],
          [-122.39012646117072, 37.78159122861445]]], null, false),
    {
    "id": "San Francisco",
    "system:index": "0"
  });
var sacremento = ee.Feature(
    ee.Geometry.Polygon(
        [[[-121.57931330173767, 38.66249153917632],
          [-121.57931330173767, 38.449857622479634],
          [-121.29641535251892, 38.449857622479634],
          [-121.29641535251892, 38.66249153917632]]], null, false),
    {
      "id": "Sacramento",
      "system:index": "0"
    });

var boxes = ee.FeatureCollection([sanfrancisco,sacremento]);
  var calculateTasseledCap = function (image){
  var b = image.select("B2", "B3", "B4", "B5", "B6", "B7");
  //Coefficients are only for Landsat 8 TOA
    var brightness_coefficents= ee.Image([0.3029, 0.2786, 0.4733, 0.5599, 0.508, 0.1872])
  var greenness_coefficents= ee.Image([-0.2941, -0.243, -0.5424, 0.7276, 0.0713, -0.1608]);
  var wetness_coefficents= ee.Image([0.1511, 0.1973, 0.3283, 0.3407, -0.7117, -0.4559]);
  var fourth_coefficents= ee.Image([-0.8239, 0.0849, 0.4396, -0.058, 0.2013, -0.2773]);
  var fifth_coefficents= ee.Image([-0.3294, 0.0557, 0.1056, 0.1855, -0.4349, 0.8085]);
  var sixth_coefficents= ee.Image([0.1079, -0.9023, 0.4119, 0.0575, -0.0259, 0.0252]);

    var brightness = image.expression(
            '(B * BRIGHTNESS)',
            {
                'B':b,
                'BRIGHTNESS': brightness_coefficents
                }
            );
  var greenness = image.expression(
    '(B * GREENNESS)',
            {
                'B':b,
                'GREENNESS': greenness_coefficents
                }
            );
  var wetness = image.expression(
    '(B * WETNESS)',
            {
                'B':b,
                'WETNESS': wetness_coefficents
                }
            );
  var fourth = image.expression(
      '(B * FOURTH)',
        {
          'B':b,
          'FOURTH': fourth_coefficents
          }
        );
  var fifth = image.expression(
      '(B * FIFTH)',
        {
          'B':b,
          'FIFTH': fifth_coefficents
          }
        );
  var sixth = image.expression(
    '(B * SIXTH)',
    {
      'B':b,
      'SIXTH': sixth_coefficents
      }
    );
  brightness = brightness.reduce(ee.call("Reducer.sum"));
    greenness = greenness.reduce(ee.call("Reducer.sum"));
    wetness = wetness.reduce(ee.call("Reducer.sum"));
    fourth = fourth.reduce(ee.call("Reducer.sum"));
    fifth = fifth.reduce(ee.call("Reducer.sum"));
  sixth = sixth.reduce(ee.call("Reducer.sum"));
  var tasseled_cap = ee.Image(brightness).addBands(greenness).addBands(wetness)
                             .addBands(fourth)
                             .addBands(fifth)
                             .addBands(sixth).rename('brightness','greenness','wetness','fourth','fifth','sixth')
  return tasseled_cap;
};

var start_date = "2018-12-30"
var end_date = "2018-12-31"
var cloud_cover = 10

var select_2018 = ee.Image("LANDSAT/LC08/C01/T1_RT_TOA/LC08_217073_20180613");
var BRD = boxes.geometry();
Map.centerObject(BRD);

var landsat8_collection = ee.ImageCollection('LANDSAT/LC08/C01/T1_TOA')
        .filterDate('2013-09-01', '2013-12-31')
        .filterMetadata('CLOUD_COVER', 'less_than', cloud_cover)
        .filterBounds(BRD)


var landsat8_tasseled_cap = landsat8_collection.map(calculateTasseledCap);

// reduce tasseled cap collection to an image so we can use .reduceRegion()
var tasseledcapImg = landsat8_tasseled_cap.mosaic()

var reducer = ee.Reducer.mean() // change to whichever reducer you would like to use

// map over each feature in the city collection
var city_stats = boxes.map(function(feature){
  // reduce the feature to get band statistics
  var zonalStats = tasseledcapImg.reduceRegion({
    reducer: reducer,
    geometry:feature.geometry(),
    scale:30
  })
  // return same feature but with the zonal stat results
  return feature.set(zonalStats)
})

print(city_stats)

Map.addLayer(landsat8_tasseled_cap,{},'Landsat 8 Tasseled Cap');
Map.addLayer(landsat8_tasseled_cap,{min: 0, max:1, bands:['brightness']},'brightness');
Map.addLayer(landsat8_tasseled_cap,{min: 0, max:1, bands:['greenness']},'greenness');
Map.addLayer(landsat8_tasseled_cap,{min: 0, max:1, bands:['wetness']},'wetness');
Map.addLayer(boxes,{color:'yellow'},'Cities');

Answer 1

Use .select() to extract a band then export it.

// To extract brightness band from the Image Collection
var brightness = landsat8_tasseled_cap.select('brightness')

// Image collection to Image (Extract the latest data, as displayed on your code)
var brightness_Image = brightness.reduce(ee.Reducer.last());

// Export the image
Export.image.toDrive({
   image: brightness_Image,
   description: 'brightness',
   scale: 30
 });