SHEET

Developer: Leibniz-Institut für Agrartechnik

Category: Libraries & Demo

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100 installs

ratings

+17 weekly installs

+21 monthly installs

ASO Keyword Dashboard

Tracking 78 keywords for SHEET in Google Play

Developer: Leibniz-Institut für Agrartechnik und Bioökonomie Category: libraries_and_demo

SHEET tracks 78 keywords (no keywords rank yet; 78 need traction). Key metrics: opportunity 71.2, difficulty 43.2.

SUNBURN AND HEAT PREDICTION IN CANOPIES FOR EVOLVING A WARNING TECH SOLUTION

Tracked keywords

0 ranked • 78 not ranking yet

Top 10 coverage

—

Best rank — • Latest leader —

Avg opportunity

71.2

Top keyword: tech

Avg difficulty

43.2

Lower scores indicate easier wins

Opportunity leaders

tech

Opportunity: 74.0 • Difficulty: 42.4 • Rank —

Competitors: 660
65.6
institute

Opportunity: 74.0 • Difficulty: 37.3 • Rank —

Competitors: 71
61.8
apple

Opportunity: 74.0 • Difficulty: 42.7 • Rank —

Competitors: 676
63.7
university

Opportunity: 74.0 • Difficulty: 40.8 • Rank —

Competitors: 173
66.1
recognized

Opportunity: 74.0 • Difficulty: 39.4 • Rank —

Competitors: 182
59.6

Unranked opportunities

tech

Opportunity: 74.0 • Difficulty: 42.4 • Competitors: 660
institute

Opportunity: 74.0 • Difficulty: 37.3 • Competitors: 71
apple

Opportunity: 74.0 • Difficulty: 42.7 • Competitors: 676
university

Opportunity: 74.0 • Difficulty: 40.8 • Competitors: 173
recognized

Opportunity: 74.0 • Difficulty: 39.4 • Competitors: 182

High competition keywords

mobile

Total apps: 280,368 • Major competitors: 11,033

Latest rank: — • Difficulty: 55.7
designed

Total apps: 264,190 • Major competitors: 8,571

Latest rank: — • Difficulty: 53.7
using

Total apps: 224,577 • Major competitors: 12,364

Latest rank: — • Difficulty: 57.0
data

Total apps: 177,234 • Major competitors: 7,067

Latest rank: — • Difficulty: 56.6
provides

Total apps: 167,241 • Major competitors: 5,651

Latest rank: — • Difficulty: 54.1

All tracked keywords

Includes opportunity, difficulty, rankings and competitor benchmarks

							Major Competitors
sheet	73	100	36	57 3,916 competing apps Median installs: 3,104 Avg rating: 2.4	—	—	149 major competitor apps
support	67	100	55	83 164,833 competing apps Median installs: 1,609 Avg rating: 2.6	—	—	7,891 major competitor apps
within	68	100	51	80 103,943 competing apps Median installs: 1,509 Avg rating: 2.3	—	—	4,171 major competitor apps
tech	74	100	42	66 13,119 competing apps Median installs: 1,371 Avg rating: 2.5	—	—	660 major competitor apps
radiation	70	100	28	45 684 competing apps Median installs: 2,939 Avg rating: 2.5	—	—	27 major competitor apps
designed	65	100	54	86 264,190 competing apps Median installs: 798 Avg rating: 2.2	—	—	8,571 major competitor apps
institute	74	100	37	62 7,507 competing apps Median installs: 576 Avg rating: 1.7	—	—	71 major competitor apps
list	69	100	52	78 81,810 competing apps Median installs: 2,563 Avg rating: 2.4	—	—	3,559 major competitor apps
using	66	100	57	85 224,577 competing apps Median installs: 2,832 Avg rating: 2.5	—	—	12,364 major competitor apps
life	68	100	54	81 112,583 competing apps Median installs: 2,537 Avg rating: 2.5	—	—	6,554 major competitor apps
call	70	100	54	75 47,995 competing apps Median installs: 3,974 Avg rating: 2.5	—	—	3,115 major competitor apps
food	69	100	49	77 69,888 competing apps Median installs: 430 Avg rating: 2.2	—	—	2,276 major competitor apps
option	70	100	49	74 47,099 competing apps Median installs: 3,034 Avg rating: 2.5	—	—	2,519 major competitor apps
mobile	65	100	56	87 280,368 competing apps Median installs: 1,392 Avg rating: 2.4	—	—	11,033 major competitor apps
apple	74	100	43	64 9,877 competing apps Median installs: 2,478 Avg rating: 2.5	—	—	676 major competitor apps
requests	72	100	42	69 21,245 competing apps Median installs: 554 Avg rating: 2.2	—	—	452 major competitor apps
university	74	100	41	66 14,015 competing apps Median installs: 1,710 Avg rating: 1.9	—	—	173 major competitor apps
community	69	100	51	78 83,647 competing apps Median installs: 547 Avg rating: 2.3	—	—	2,678 major competitor apps
provides	67	100	54	83 167,241 competing apps Median installs: 1,409 Avg rating: 2.3	—	—	5,651 major competitor apps
tool	68	100	50	80 99,892 competing apps Median installs: 1,333 Avg rating: 2.4	—	—	4,053 major competitor apps
approach	73	100	47	68 18,664 competing apps Median installs: 886 Avg rating: 2.2	—	—	470 major competitor apps
advanced	69	100	53	79 85,249 competing apps Median installs: 2,117 Avg rating: 2.6	—	—	5,150 major competitor apps
please	67	100	53	81 129,568 competing apps Median installs: 4,943 Avg rating: 2.6	—	—	7,082 major competitor apps
address	72	100	46	71 26,591 competing apps Median installs: 2,188 Avg rating: 2.3	—	—	1,323 major competitor apps
recognized	74	100	39	60 5,506 competing apps Median installs: 1,942 Avg rating: 2.3	—	—	182 major competitor apps

App Description

SUNBURN AND HEAT PREDICTION IN CANOPIES FOR EVOLVING A WARNING TECH SOLUTION

This mobile App provides a tool for using a risk model for fruit damage due to exposure to global radiation in viticulture and apple production. The SHEET App is intended to support the decision making on measures for avoidance of heat damage in orchards and vineyards. This App is designed to address growers, extension service, and research.
Present version: The model was developed in experimental grape production in Bologna, Italy, and experimental apple production in Bologna and Potsdam, Germany. The models were developed for the particular growing conditions and need to be adapted to your location!

A. Check out: The SHEET App provides probability models for heat damage in grape and apple production. The two probability models are based on deep learning approach, which requests to be validated and adapted to specific fields. Please compare the risk recognized by this mobile App with own experiences.

B. Contribute: The SHEET App will be further developed in a community approach targeting the use of thermodynamic model and advanced deep learning approach. This SHEET App, therefore, provides the option to upload own data from the fruit production. Your participation in the further development will be recognized in a list of contributors.

The project was supported by the ICT-AGRI-FOOD call (funders: MIPAAF, Italy, BMEL, Germany, NRDIO, Hungary), within the project SHEET (https://ictagrifood.eu/node/44656). The SHEET project is coordinated by Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Germany. Project partners are Hungarian University of Agriculture and Life Sciences / Magyar Agrár- és Élettudományi Egyetem (MATE); Alma Mater University Bologna / Department of Agricultural and Food Sciences (UNIBO), and Cloudflight.